Transport Approach Research Articles

Modified tractive force approach for sediment transport under bank seepage

ABSTRACT The current research focuses on integrating the impact of seepage into the tractive force method for sediment particles situated on porous riverbanks. A formula is developed using the tractive force approach to calculate the critical shear stress acting on sediment particles under steady seepage conditions. The study reveals that the hydraulic gradient influences the critical shear stress, which rises with higher hydraulic gradients. Additionally, application of the derived equation is demonstrated through a hypothetical channel design problem.

A one-field fluid/meso-structure coupling approach for multiscale transport in heterogeneous porous media

Modeling transport phenomena within heterogeneous porous media poses considerable challenges, particularly on account of the complexity of the involved geometries combined with nonlinear transport interactions. In the present study, a novel one-field modeling approach for multiscale fluid–solid interactions is proposed that does not need any a priori information on permeability. This approach implicitly considers the existence of multiscale structures through a penalization function that encompasses merely one single effective parameter. The definition, determination, as well as the response of the effective parameter to influencing factors are elaborated in detail. It is demonstrated that this approach is effective in representing properly the heterogeneity of solids. The method has been successfully applied to both nonlinear porous media flows and Darcian transport problems, exhibiting comparable accuracy but substantial computational savings as opposed to pore-scale simulations. It leads to more accurate interphase mass transfer predictions and lower computational cost in comparison with the Darcy–Brinkmann–Stokes approach. Overall, this method appears to be highly effective in forecasting realistic, industrial-scale porous media transport problems.

An integrated environmental and economic assessment for the disposal of food waste from grocery retail stores towards resource recovery.

Food waste gives rise to many environmental problems. A large amount of food waste is produced by grocery retail stores. It is therefore important to apply efficient food waste treatment technologies with minimal environmental impact and investigate the optimal approach for food waste collection, transportation, and treatment. In the present study, a life cycle impact assessment (LCIA) was conducted to analyze different food waste disposal scenarios, including incineration, landfilling, composting, anaerobic digestion, and bioconversion. The impacts of the five scenarios on the environmental, economic, and social aspects were assessed. The results suggested that the landfilling scenario has the lowest net cost for the treatment of food waste, followed by the incineration scenario. The bioconversion treatment cost has the most significant positive effect on the net cost of the bioconversion scenario, and both the price and yield of compost have a significant negative effect on the net cost. The rankings of the five scenarios are the same under both weight determination methods, with the bioconversion scenario performing the best, followed by the composting scenario. The results of this study can help improve the disposal of food waste in grocery retail stores in the framework of sustainability and the circular economy.

Advancing urban mobility in developing countries: A mobile RSU approach for sustainable transportation

AbstractThe rapid and uncontrolled urbanization of cities in developing countries has engendered a plethora of urban mobility issues, including traffic congestion, accidents, and air pollution. To address these challenges, contemporary urban mobility trends are incorporating innovative technologies and sustainable governance practices. This article investigates how urban managers can leverage the opportunities presented by cost‐effective technologies and the management of urban data to enhance urban mobility in developing countries. Within this discourse, an RSU‐based approach is proposed that employs motorbike taxis for inter‐vehicular communication, given their status as the most widely used form of public transportation. This approach substantially diminishes investment costs and reinforces the sustainability of urban mobility. Through the implementation of this solution, a noteworthy reduction is anticipated in the emission of gases such as CO2, and NOx, known contributors to climate change and various respiratory diseases. To validate the efficacy of the proposed solution, four distinct scenarios are scrutinized in a case study centered on the city of Douala in Cameroon, utilizing tools such as OMNET++, SUMO, Veins, and INET. The proposed framework offers significant benefits in terms of environmental sustainability and operational efficiency. It enables a 10% reduction in CO2 emissions, a 15% reduction in NOx emissions, an 11% drop in fuel consumption, and a 15% reduction in waiting time in traffic jams. The envisaged solution aims to aid urban managers in their decision‐making processes, specifically in advancing sustainable urban mobility. Through the adoption of this approach, cities in developing countries can mitigate challenges associated with urban mobility and enhance the overall well‐being of their residents.

Targeting the undruggable in glioblastoma using nano-based intracellular drug delivery.

Glioblastoma (GBM) is a highly prevalent and aggressive brain tumor in adults with limited treatment response, leading to a 5-year survival rate of less than 5%. Standard therapies, including surgery, radiation, and chemotherapy, often fall short due to the tumor's location, hypoxic conditions, and the challenge of complete removal. Moreover, brain metastases from cancers such as breast and melanoma carry similarly poor prognoses. Recent advancements in nanomedicine offer promising solutions for targeted GBM therapies, with nanoparticles (NPs) capable of delivering chemotherapy drugs or radiation sensitizers across the blood-brain barrier (BBB) to specific tumor sites. Leveraging the enhanced permeability and retention effect, NPs can preferentially accumulate in tumor tissues, where compromised BBB regions enhance delivery efficiency. By modifying NP characteristics such as size, shape, and surface charge, researchers have improved circulation times and cellular uptake, enhancing therapeutic efficacy. Recent studies show that combining photothermal therapy with magnetic hyperthermia using AuNPs and magnetic NPs induces ROS-dependent apoptosis and immunogenic cell death providing dual-targeted, immune-activating approaches. This review discusses the latest NP-based drug delivery strategies, including gene therapy, receptor-mediated transport, and multi-modal approaches like photothermal-magnetic hyperthermia combinations, all aimed at optimizing therapeutic outcomes for GBM.

SMASH as an event generator for heavy-ion collisions

In this article we present an overview of the SMASH hadronic transport approach that is applied for non-equilibrium dynamics of hadrons in heavy-ion collisions. We will give an overview about the ingredients of the approach and the applications for the dynamical description of heavy-ion collisions and for calculations of fundamental properties of the hadron gas. The main emphasis of the article will be the infrastructure for sustainable software development that we have developed over the last 10 years including extensive unit tests and continuous integration. We will also provide one section about the performance of the code and how it can be analyzed and improved in the future.

Hydro-Thermal Coupled Behaviors in Free Zones and Matrix of Porous Media: Insights from a Micro-Continuum Transport Approach

Hydro-Thermal Coupled Behaviors in Free Zones and Matrix of Porous Media: Insights from a Micro-Continuum Transport Approach

A modeling approach for water and sediment transport in Jezero crater on Mars based on new geomorphological evidence

A modeling approach for water and sediment transport in Jezero crater on Mars based on new geomorphological evidence

Logistics Performance Index-driven in operational planning for logistics companies: A smart transportation approach

The responsibility of Logistics Companies (LCs) extends beyond simply handling logistical processes and choosing transportation routes; they focus on being competitive and efficient in their operations. In multiple origins and destinations networks, LCs attempt to select the most optimal routes from each point. To address this challenge and reduce the time needed to identify potential routes, a novel method has been developed in this research for LCs. In operational planning, additional factors need to be considered to increase efficiency, customer satisfaction, and competitiveness. To confront this issue, the study proposes a novel model and contributions, inspired by the LPI, to apply the transformative impact of smart ports, the integration of smart containers, the choices of clearing and forwarding agents and port operators, and time uncertainty in the multi-objective framework. Specifically, the mathematical model's objectives include cost, time, customer satisfaction, and environmental impact in the periodic multimodal network. An innovative customer satisfaction function is introduced by integrating the selection of smart containers and smart ports, emphasizing their impact on enhancing customer satisfaction, while addressing time uncertainty through a chance-constrained approach and coefficients of variation. The model is solved using goal programming, and the results show that smart ports and smart containers can majorly affect transportation time and customer satisfaction. Furthermore, comparing the results to other studies demonstrates its superiority in decision-making for LCs, particularly by including time uncertainty and the role of clearing and forwarding agents and port operators. Therefore, the model holds practical significance in lowering costs, enhancing customer satisfaction, and facilitating smart international logistics. This research offers insights that are not only useful for the LCs but also for other stakeholders in the transport industry.

Alkyl-linked TiO2@COF heterostructure facilitating photocatalytic CO2 reduction by targeted electron transport

Targeted electron transfer to catalytically active site for CO2 reduction is promising for enhancing the efficiency of artificial photosynthesis. Here, we demonstrate a design of an alkyl-linked heterostructure composing of TiO2 and a Cu-porphyrin-based covalent organic framework (TiO2@CuPorTT-COF) for the photoreduction of CO2 with H2O. Through specific coordination effect, the alkyl chain bridges TiO2 and Cu moiety in COF. Upon light illumination, the photoinduced electrons in TiO2 can be directionally transported across the interface along the alkyl chain to the Cu active sites to reduce adsorbed CO2, while the left holes are consumed by the H2O oxidation, enhancing the spatial separation and utilization of electron-hole pairs. Accordingly, the TiO2@CuPorTT-COF enables remarkably superior catalytic activities over the counterpart without the alkyl bridge for electron transfer with 5 times of CO production rate. An apparent quantum efficiency of 0.455% at 380 nm was achieved. Moreover, a dynamic evolution of Cu active site for CO2 reduction is revealed, which can be promoted by the targeting electron transport approach. This work provides a targeted electron transport strategy for constructing photocatalysts.

Enhancement of CO gas sensing with ZnO nanostructures on MWCNTs films

CO gas sensing properties of 1-D ZnO nanostructures deposited on films of Multi-Wall carbon nanotubes were investigated using a vapor transport approach. X-ray powder diffraction, scanning electron microscopy, transmission electron microscopy, high resolution transmission electron microscopy, energy dispersive X-ray, Raman spectroscopy, diffused reflectance spectroscopy, and photoluminescence, techniques were used to carry out the structural, morphological, and optical characterizations. The development of carbon-doped hybrid MWCNTs/ZnO nanostructures was demonstrated by the current results. The synthesized nanostructures were dense tapering belts and pedal-like crystalline structures as evidenced by their structural and morphological characteristics. Multiple networks of pure ZnO and hybrid MWCNTs-ZnO nanostructures were used to synthesize the gas sensors. Doped ZnO nanostructures sensing technique for CO gas detection was investigated in the present study. The combined impact of ZnO and MWCNTs was shown to be beneficial in boosting the response towards CO gas, as the response to CO gas at a concentration of 20 parts per million (ppm) was found to be five-times greater than that of ZnO sensors with good stability.

Field‐Induced Butterfly‐Like Anisotropic Magnetoresistance in a Kagome Semimetal Co3In2S2

AbstractWith the interplay between magnetism and topological bands, magnetic kagome semimetals provide promising platforms for exploring exotic correlated electronic states and quantum phenomena such as anomalous Hall effect, quantum spin liquid, and unconventional magnetoresistance, as well as driving advances in electronic and spintronic applications. Here, a field‐induced butterfly‐like anomalous anisotropic magnetoresistance (AMR) effect in an intriguing kagome semimetal Co3In2S2 is reported. The kagome‐lattice Co3In2S2 single crystals are synthesized via a polycrystal‐source chemical vapor transport approach, possessing a high carrier mobility reaching 104 cm2V−1s−1. The Co3In2S2 single crystal exhibits a canted antiferromagnetic state below 5 K, but intriguingly, it is easily transformed into a ferromagnetic state under a small external magnetic field. Furthermore, the planar Hall effect (PHE) is detected, stemming from the complex contribution of field‐induced ferromagnetism and orbital magnetoresistance. Remarkably, as the magnetic field increases, the low‐temperature magnetoresistance behavior of the Co3In2S2 reveals a butterfly‐like AMR effect with a maximum value of 850%, exhibiting a superposition of the two‐, four‐, and six‐fold AMR terms. Band structure calculations suggest that such a field‐induced butterfly‐like AMR effect may originate from the modulations of the electronic structure near the Fermi level by the magnetic moment. The findings offer a valuable platform for understanding the anomalous AMR effect and for the development of advanced spintronic devices.

On the analysis of static thermal instabilities occurring in two-phase flow systems

In this study, we investigate a novel type of static thermal instability that occurs in two-phase flow systems. The instability is theoretically and experimentally confirmed to occur for flow boiling micro-channel scenarios and flow condensing scenarios. The theory presented is independent of the evaporator geometry as well as flow boiling/condensing situations. A stability criteria is derived using a Reynolds Transport approach applied to the evaporator of a two-phase pumped loop (TPPL) system. The theory is then validated experimentally using a TPPL containing a parallel micro-channel evaporator. The instability is confirmed with pressure, temperature, and void fraction measurements acquired at the exit of the evaporator. The findings reveal that static thermal instabilities can arise when simultaneous heat addition and reduction in system saturation temperature occurs (or vice versa). The implications of the thermal instability result in dramatic changes in evaporator heat flux, as well as a flow transition from stratified laminar flow to vigorous turbulent flow with high void fractions. By identifying the additional instability mechanisms, this work contributes to enhancing system reliability and predictability of TPPL systems.

Far-from-equilibrium attractors with full relativistic Boltzmann approach in boost-invariant and non-boost-invariant systems

We study the universal behavior associated with a Relativistic Boltzmann Transport (RBT) approach with the full collision integral in 0+1D conformal systems. We show that all momentum moments of the distribution function exhibit universal behavior. Furthermore, the RBT approach allows to calculate the full distribution function, showing that an attractor behavior is present in both the longitudinal and transverse momentum dependence. We compare our results to the far-from-equilibrium attractors determined with other approaches, such as kinetic theory in Relaxation Time Approximation (RTA) and relativistic hydrodynamic theories, both in their viscous (DNMR) an anisotropic (aHydro) formulations, finding a very similar evolution, but an even faster thermalization in RBT for higher order moments. For the first time, we extended this analysis also to study the attractor behavior under a temperature-dependent viscosity η/s(T)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\eta /s(T)$$\\end{document}, accounting also for the rapid increase toward the hadronic phase. We find that a partial breaking of the scaling behavior with respect to τ/τeq\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ au /\ au _{eq}$$\\end{document} emerges only at T≈Tc\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$T \\approx T_c$$\\end{document} generating a transient deviation from attractors; interestingly this in realistic finite systems may occur around the freeze-out dynamics. Finally, we investigate for the first time results beyond the boost-invariant picture, finding that also in such a case the system evolves toward the universal attractor. In particular, we present the forward and pull-back attractors at different space-time rapidities including rapidity regions where initially the distribution function is even vanishing.

Sharp Sobolev inequalities on noncompact Riemannian manifolds with Ric≥0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extsf{Ric}\\ge 0$$\\end{document} via optimal transport theory

In their seminal work, Cordero-Erausquin, Nazaret and Villani (Adv Math 182(2):307-332, 2004) proved sharp Sobolev inequalities in Euclidean spaces via Optimal Transport, raising the question whether their approach is powerful enough to produce sharp Sobolev inequalities also on Riemannian manifolds. By using L1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$L^1$$\\end{document}-optimal transport approach, the compact case has been successfully treated by Cavalletti and Mondino (Geom Topol 21:603-645, 2017), even on metric measure spaces verifying the synthetic lower Ricci curvature bound. In the present paper we affirmatively answer the above question for noncompact Riemannian manifolds with non-negative Ricci curvature; namely, by using Optimal Transport theory with quadratic distance cost, sharp Lp\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$L^p$$\\end{document}-Sobolev and Lp\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$L^p$$\\end{document}-logarithmic Sobolev inequalities (both for p>1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$p>1$$\\end{document} and p=1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$p=1$$\\end{document}) are established, where the sharp constants contain the asymptotic volume ratio arising from precise asymptotic properties of the Talentian and Gaussian bubbles, respectively. As a byproduct, we give an alternative, elementary proof to the main result of do Carmo and Xia (Math 140:818-826, 2004) and subsequent results, concerning the quantitative volume non-collapsing estimates on Riemannian manifolds with non-negative Ricci curvature that support Sobolev inequalities.

The electron resistance of a single skyrmion within ballistic approach

An alternative way of skyrmion quasi-particle detection is simulated at low voltage bias. The point contact (PC), attached to the strip with a Néel-type skyrmion, can detect it with a higher efficiency than a magnetic tunnel junction. The method is based on detecting the skyrmion via the ballistic magnetoresistance ratio (BRR). PC's resistance with skyrmion significantly differs from the one without it. BRR is estimated in the framework of the point contact model for two directions of spin-polarized current: perpendicular to the transport direction (case 1) and along one (case 2). Skyrmion's size is assumed to be around 3.6 nm in diameter—smaller, or comparable, to the mean free path of electrons, allowing it to utilize the ballistic transport approach. As a result, resistance values for the considered Néel type skyrmion within the related size are estimated as 157 Ω for case 1 and 452.2 Ω for case 2 with optimistic BRR 101.3% and 291.7%, respectively. BRR for case 2 is higher due to the spin-filtering effect. The method also has the potential to detect the skyrmion type, or other magnetic nano structures such as bimeron, domain wall (DW), etc.

(Invited) A Hybrid Electrochemical and Catalytic Compression System for Direct Generation of High-Pressure Hydrogen at 350 Atmospheric Pressure

Hydrogen is becoming the center piece in the global de-carbonatization efforts in multiple industrial sectors. Gaseous hydrogen at high pressures in gas tanks is the most common approach for H2 storage, transportation and hydrogen refueling for fuel cell vehicles. Gaseous hydrogen at high pressures is also heavily used in the Haber process for ammonia production and hydro-cracking of heavy petroleum. In the long term, low-cost high pressure H2 will also play a critical role in the future long-duration grid storage for deep decarbonization and improved resilience.In this talk, I will share some recent development on a hybrid electrochemical/catalytic approach for direct generation of high-pressure H2 in collaboration with Pacific Northwest National Laboratory (PNNL). The hybrid system oxidizes water to oxygen at the anode, reduces V3+ to V2+ at the cathode, and stores proton in the catholyte during the “electrochemical charging” step. We demonstrated that the charged catholyte is then capable of generating H2 at >350 bar in the subsequent “catalytic discharging” step without any additional energy input. This concept leverages the electrochemical Nernst potential difference between the redox couple (V2+/3+) and the hydrogen evolution reaction and delivers a unique system that is capable of generating H2 at demand and at high pressure without any mechanical or electrochemical compression. We estimate a cost of <$0.19/kg-H2 for compression, representing >80% of the cost reduction compared to the traditional multi-stage compressor approach.

An optimal transport approach to estimating causal effects via nonlinear difference-in-differences

Abstract We propose a nonlinear difference-in-differences (DiD) method to estimate multivariate counterfactual distributions in classical treatment and control study designs with observational data. Our approach sheds a new light on existing approaches like the changes-in-changes estimator and the classical semiparametric DiD estimator, and it also generalizes them to settings with multivariate heterogeneity in the outcomes. The main benefit of this extension is that it allows for arbitrary dependence between the coordinates of vector potential outcomes and includes higher-dimensional unobservables, something that existing methods cannot provide in general. We demonstrate its utility on both synthetic and real data. In particular, we revisit the classical Card &amp; Krueger dataset, which reports fast food restaurant employment before and after a minimum wage increase. A reanalysis with our methodology suggests that these restaurants substitute full-time labor with part-time labor on aggregate in response to a minimum wage increase. This treatment effect requires estimation of the multivariate counterfactual distribution, an object beyond the scope of classical causal estimators previously applied to this data.

Demand and supply shocks derived from COVID-19 on the freight transportation system in Mexico

PurposeThis paper's purpose is twofold. First, based on a case study, it aims to comprehend the consequences of COVID-19 on the demand and supply shocks of the freight transportation system in Mexico. Second, it seeks to provide an integrated perspective of four transportation modes, which would help prepare public policies for future global pandemics.Design/methodology/approachAnalyzing the impact of the COVID-19 pandemic on the freight transportation system, which affects national and global economies, is essential to drawing valuable insights for the future. To facilitate international comparative analysis, conducting case studies at a country level was deemed necessary. As a result, a case study was conducted in Mexico using an integrated approach involving four transportation modes.FindingsTo manage disruptions in freight flow during uncertain conditions, a comprehensive perspective on the four modes of transportation and data-driven decision-making is crucial. Under this context, three initiatives can be identified: 1) establishing a National Center for Intelligence in Logistics to improve data-driven governance; 2) appointing the “Integrated Transportation Corridor Management Manager” (ITCMM) function to coordinate multiple authorities with different acting in critical freight transport corridors, and 3) creation of a digital tool based on millions of GPS data to monitor freight flows, allowing for collective intelligence among logistics actors.Research limitations/implicationsThis research's limitations are related to using non-standardized databases to gather information on four transportation modes. However, this limitation is also an interesting discovery. Mexico is becoming a strategic logistics hub between North America and Latin America, especially under the “Nearshoring” trend. Unfortunately, the lack of an integrated public policy in logistics and transportation reduces Mexico's capacity to deal with disruptions and its economic competitiveness.Practical implicationsThis research has identified practices that could be crucial in improving public policies to optimize shipping routes and reduce wait times while minimizing disruptions caused by unforeseen events. A concrete example is the digital platform called “eraclitux,” a computer tool similar to an Enterprise Resource Planning (ERP) system companies use. This tool can enable a “Control Tower” that monitors freight flow in transportation corridors under the supervision of “Integrated Transportation Corridor Management Managers.” The tool can make reactive and predictive decisions that help to enhance the logistics value provided by transportation infrastructure.Social implicationsThe importance of a well-coordinated and integrated public policy for freight transportation was identified to ensure better performance during disruptions. Delays in the flow of goods can significantly impact the supply of essential items such as food and medicine, ultimately affecting the population's quality of life.Originality/valueNumerous studies have been conducted to determine the extent of vulnerability and the impact of COVID-19 on freight transportation. However, most of these studies assume a developed market context or a single-mode transportation approach, which only applies to some situations. To gain a comprehensive understanding of how pandemics-induced demand and supply shocks affected freight transportation in developing countries such as Mexico, this paper offers insights from a four-transportation mode perspective. Mexico is facing a challenging Nearshoring trend in manufacturing, making it a significant logistics node between North and South America.

A distributionally robust optimization approach for the potassium fertilizer product transportation considering transshipment through crossdocks

Potassium fertilizer is an essential input for agricultural productivity, and plays a critical role in various plant processes, influencing water uptake, enzyme activation, and photosynthesis. The efficient delivery of potassium fertilizer products to the end-users, typically farmers and agricultural enterprises, is of utmost importance. Due to the long traveling distance between the supplier and customers, decision makers of supplier normally set up multiple crossdocks to aid in transition and storage of potassium fertilizer products. In this situation, making an optimal transportation plan as well as the inventory level of crossdocks will directly enhance the efficiency and effectiveness of long-distance transportation. In this study, we model this problem as a dynamic transportation problem with transshipment considering the uncertain time-varying customers’ demand. To characterize the demand information, we first construct an ambiguity set of customers’ demand based in limited historical data and then develop a distributionally robust optimization-based (DRO) framework to optimize the transportation plan and related inventory level of crossdocks simultaneously. We also propose a general approach to overcome the computational challenges of DRO by transforming the original DRO into a second-order cone programming based on duality theory. Additionally, we introduce linear decision rules to adjust the optimization strategy based on the new observed demand, thus lead the model to handle the dynamic information flow in real time. In case study, all involved data are collected or derived from a real potassium fertilizer company located at Western China. The results show our model reduces the cost by 18.07% compared to stochastic model (sample average approximation), indicating a significant effectiveness of our model on the improvement of delivery efficiency and cost saving in real dynamic logistic systems. Also, we conclude the managerial insight that decision-makers should develop a comprehensive strategy, including improving communication to ensure order status updates, planning rationally to evenly distribute orders, and proactively allocating resources to meet operational demands.