Mathematical Modeling Simulation Research Articles

Kinetic Modelling of Ralstonia eutropha H16 Growth on Different Substrates

Due to environmental pollution and the depletion of fossil fuels, there is growing interest in the development and use of biofuels as environmentally friendly alternatives. One of the most promising biofuels is biohydrogen, hydrogen produced through sustainable processes using microorganisms such as bacteria and algae. One of the most interesting bacteria for hydrogen production is Ralstonia eutropha H16, known for its ability to produce oxygen-tolerant hydrogenases. These enzymes play a crucial role in biohydrogen metabolism and production. The aim of this work was to determine the optimal conditions (reactor type and synthetic medium composition) for the cultivation of R. eutropha H16. The culture media contained different concentrations of fructose and glycerol (mono- or double-substrate cultivation) and the experiments were carried out in a batch reactor. The initial experiments were carried out with 4 g/L fructose or glycerol in the culture medium at pH 7, T = 30 °C, and 120 rpm. The mathematical model, consisting of the growth kinetics (described by the Monod’s model) and the corresponding mass balances, was proposed. The developed model was validated using two independent experiments with different initial substrate concentrations: 2 g/L glycerol and fructose in one medium and 4 g/L fructose and 1 g/L glycerol in the second. In order to propose the optimal cultivation procedure for future research, the mathematical model simulations were performed for different reactor types (batch, fed-batch, and continuous stirred tank reactors) and different initial substrate concentrations. The most successful experiment was the one with 4 g/L glycerol, where γX = 0.485 ± 0.001 g/L of biomass was achieved. Further calculations showed that the most biomass would be produced at higher glycerol concentrations (at γG = 6.358 g/L, γX = 1.311 g/L should be achieved after 200 h of cultivation) and when using a fed-batch reactor (γX = 0.944 g/L after 200 h of cultivation).

A simple yet effective ALE-FE method for the nonlinear planar dynamics of variable-length flexible rods

With recent advances in variable-length structures for use in soft actuation, energy harvesting, energy dissipation and metamaterials, the mathematical modelling and numerical simulation of physical systems with time-varying domains is becoming increasingly important. The planar nonlinear dynamics of one-dimensional elastic structures with variable domain is formulated from a Lagrangian approach by using a non-material reference frame. An Arbitrary Lagrangian-Eulerian (ALE) scheme is proposed where the domain is reparametrized based on a priori unknown configuration parameters. Based on this formulation, a Finite Element (FE) method is developed for theoretically predicting the evolution of a rod constrained at its ends by one or two sliding-sleeves, whose position and inclination can be varied in time, and under external loadings. Finally, case studies and instability problems are investigated to assess the reliability of the proposed formulation against others available and to demonstrate its effectiveness. With respect to previously developed methods for this type of structural problems, the present ALE-FE approach shows a strong theoretical and implementation simplicity, maintaining an efficient and fast convergence according to the cases analyzed. An open source code realized for the present ALE-FE model is made available for solving the nonlinear dynamics of planar systems constrained by one or two independent sliding sleeves. The present research paves the way for further extensions to easily implement solvers for the three-dimensional dynamics of flexible one- and two-dimensional structural systems with moving boundary conditions.

MODERN METHODS OF QUANTITATIVE ASSESSMENT OF THE STRUCTURE OF HYDROCARBON RESOURCES OF LARGE PETROLEUM BASINS

The article discusses modern methods of quantitative assessment of the elements of hydrocarbon resource structure in large oil and gas (petroleum) basins. The assessment is based on the law of mass distribution of hydrocarbon accumulations, i.e., the truncated Pareto distribution. The procedure developed is used for: estimation of the truncated Pareto distribution parameters and cumulative hydrocarbon volumes concentrated in pools, prediction of their number and size distribution and total resources within each size-class interval; simulation of spatial distributions of hydrocarbon accumulations with transformation of a population of HC pools into a population of fields; prediction of the number and size-class distribution of total HC resources in pools and fields, and fields distribution by the number of HC pools. The involved analytical approach based on the simulation mathematical modeling is described.

Separation Time of Aluminothermic Reduction Products for Sustainable Silicon Production

Background This work was carried out within the framework of the SisAl Pilot project, which is devoted to the environmentally friendly production of silicon. This new method relies on the aluminothermic reduction of quartz in slag, offering a more sustainable alternative to the traditional reduction of silica with carbon in submerged arc furnaces. Methods The process takes place in a rotary kiln producing silicon (Si) and alumina slag (actually, a CaO – Al2O3 slag), which must be separated at the end to extract the silicon. This separation process is analyzed through mathematical modelling and numerical simulation, as it is of industrial interest to know how much time it takes for Si and CaO – Al2O3 slag to separate once the process has ended. Generally, a multiphase flow model is used to estimate the separation time of the two components once aluminothermic reduction has ended. Results Several scenarios are considered for the numerical simulation of the separation time, namely different initial configurations and material properties of both fluids are covered. Moreover, the separation times obtained with two distinct multiphase flow models -VOF (volume of fluid) and Eulerian- are compared. Conclusions The separation times resulting from simulations using the multiphase Eulerian model are more realistic compared to those from the VOF model, which clearly tends to underestimate separation times. Furthermore, apart from the selected multiphase flow model, the density difference between silicon and alumina slag plays a critical role in determining the separation time.

Modeling and Dynamic Characteristics of Tracked Vehicle Equipped with Symmetrical Suspensions Based on Multi-Body Dynamics and Discrete Element Coupling Method

For improving the adaptability of a tracked vehicle equipped with a symmetrical suspension system on complex hilly terrain, based on the coupling method of multi-body dynamics (MBD) and discrete element method (DEM), an MBD-DEM coupling model was built and verified to explore its dynamic behaviors on soil. Firstly, according to the basic parameters of the tracked vehicle equipped with a symmetrical suspension system, a corresponding MBD model was built in Recurdyn V9R4 software. Based on the Euler–Lagrange method, the mathematical structure of the symmetrical suspension system was analyzed, and a corresponding mathematical simulation model was built in Matlab2016/Simulink to verify the MBD model. Secondly, based on the DEM theory and the parameter of the soil in a hilly area, a granular pavement model was built. Then, based on the coupling method of MBD and DEM, the corresponding MBD-DEM coupling model was built. Finally, using the MBD-DEM coupling model, the dynamic behaviors of the tracked vehicle equipped with a symmetrical suspension system under horizontal condition, the climbing condition and the obstacle crossing condition were obtained and discussed. The study results show that the proposed MBD-DEM coupling model could be used effectively to analyze the dynamic characteristics of the tracked vehicle. In addition, according to the analysis of the dynamic characteristics of the proposed tracked vehicle, the tracked vehicle equipped with a symmetrical suspension presents good adaptabilities under various working conditions.

Optimizing alkalinity control in recirculating aquaculture systems (RAS): A dynamic modelling approach

Maintaining good water quality is essential for successful fish production in land-based recirculating aquaculture systems (RAS). Numerous interdependent factors influence water quality parameters, making it difficult to evaluate which operational strategies are most favorable. Mathematical models and model simulations have proven to be powerful tools to evaluate how RAS design and operation are linked to RAS dynamics, but these models rarely implement pH and carbonate species as dynamic variables. Here, we present a dynamic model for RAS (dynRAS) that combines rates of TAN (total ammonia nitrogen) removal, fish growth, and CO2 and TAN excretion, with a reaction model for pH and the carbonate system formulated based on the law of mass action. A novel aspect of our approach is the incorporation of a dosage system modelled by a Hill-function, enabling the exploration of diverse dosing strategies for pH and alkalinity management. The model was validated based on empirical data from a pilot scale RAS system operated with a feeding regime involving 12 h of feeding per day. We found that model simulations could be used to accurately predict diurnal cycling patterns in RAS water quality parameters. Furthermore, we made use of simulations to assess how diurnal cycling varies with changing pH and alkalinity levels. Model results emphasize the complexity of pH and alkalinity control in RAS in relation to overall water quality management. Based on our simulations, we argue that what should be considered as optimal pH and alkalinity in RAS depends on the state of the system. Accordingly, optimal pH and alkalinity thresholds may vary between different RAS units and between different time points of a rearing cycle. More generally, we demonstrate how modelling and model simulations can be an effective way of getting insights into the dynamics of complex RAS interactions and provide a valuable tool to efficiently explore effects of different operational strategies on water quality parameters.

Simulation optimization and experimental validation of hydraulic impact in pruning machines

Abstract This study addresses the instability caused by hydraulic shocks in fruit tree pruning machines during operation and proposes an optimization scheme that combines simulation with experimentation. We investigated the mechanisms of load shock in the hydraulic system through mathematical modeling and LS-DYNA simulation analysis. The optimal operating parameters were determined using mechanical and orthogonal analyses: a forward speed of 4 km h−1, a pruning tool angle of 60°, and a saw blade rotation speed of 1200 r min−1. Additionally, we employed AMESim simulation to optimize the hydraulic system of the pruning machine by designing a dual accumulator configuration to effectively suppress hydraulic shocks. We validated the optimized system through simulations and experimental tests, demonstrating significant reductions in pressure fluctuations, with cutting efficiency improved by 30% and pressure fluctuations reduced by 26.7%. This study not only presents an innovative dual accumulator design but also validates its effectiveness in pruning machines through simulations and experiments, thereby enhancing the operational efficiency and stability of agricultural machinery.

Mathematical Modeling and Simulation of 1,3-Propanediol Production by Klebsiella pneumoniae BLh-1 in a Batch Bioreactor Using Bayesian Statistics.

Mathematical modeling and computer simulation are fundamental for optimizing biotechnological processes, enabling cost reduction and scalability, thereby driving advancements in the bioindustry. In this work, mathematical modeling and estimation of fermentative kinetic parameters were carried out to produce 1,3-propanediol (1,3-PDO) from residual glycerol and Klebsiella pneumoniae BLh-1. The Markov chain Monte Carlo method, using the Metropolis-Hastings algorithm, was applied to experimental data from a batch bioreactor under aerobic and anaerobic conditions. Sensitivity analysis and parameter evolution studies were conducted. The root-mean-square error (rRMSE) was chosen as the validation and calibration metric for the developed mathematical model. The results indicated that the average tolerance of glycerol was 174.68 and 44.85 g L-1, the inhibitory products was 150.95 g L-1 for ethanol and 35.56 g L-1 for 1,3-PDO, and the maximum specific rate of cell growth was 0.189 and 0.275 h-1, for aerobic and anaerobic cultures, respectively. The model presented excellent fits in both crops, with rRMSE values between 0.09 - 33.74% and 3.58 - 31.82%, for the aerobic and anaerobic environment, respectively. With this, it was possible to evaluate and extract relevant information for a better understanding and control of the bioprocess.

Frictional loss and permeability estimation of sediment in salt cavern: A combined approach of mathematical model, experimental validation, and numerical simulations

Harnessing gas storage in sediment voids presents a promising trajectory for the future construction of large-scale underground gas reservoirs in low-grade salt mines. This approach not only augments the effective gas volume but also enhances the stability of the cavern. In contrast to traditional gas injection and brine discharge process, where brine is expelled from the upper pure brine space without involving brine seepage in sediment voids, gas storage in sediment voids entails expelling brine from these spaces, thus necessitating an understanding of the brine seepage characteristics in the sediment, which remains unclear. This study presents a comprehensive approach for estimating sediment frictional loss and permeability in interconnected wells, integrating mathematical modeling, experimental validation, and numerical simulation. The mathematical principles governing sediment behavior during in-situ gas/brine injection and brine discharge tests are theoretically elucidated, accompanied by derived formulas. Experimental verification is conducted in the horizontal interconnected wells (Ha4-5) of the Huaian salt mine in Jiangsu, yielding the sediment frictional loss (0.53 MPa) and permeability (6.9 × 10−11 m2). Subsequently, a 2D cross-sectional numerical model is established using the COMSOL software, considering the measured and predicted well morphologies. The model provides insights into the relationship between sediment frictional losses and permeability, yielding an inverse calculation of the average permeability (1.016 × 10−10 m2). Simulation results depict laminar brine flow characteristics in the cavern during gas/brine injection and brine discharge processes, with frictional loss occurring as brine passes through sediment. Examination of the brine seepage and pressure fields in the sediment reveals consistent brine flow velocity after passing through the sediment. This combined approach focuses on investigating the seepage characteristics of sediment at the bottom of salt caverns, offering valuable insights for estimating frictional losses and permeability in similar salt mines.

Performance of water quality simulation model for lifting drainage water joints and mixing zone determination

Limited water resources with gradual increase in water demand led to higher dependence on drainage water as one of the non-conventional water resources in Egypt. However, there was no precise approach for using such resource. The practices ranged between stopping lifting drainage water to main canals at many locations due to the water quality degradation in the drains and pure dependence on polluted drainage water by farmers. This implies the importance of applying the mathematical models that provide precise and flexible alternative for the dependence on the drainage water. This procedure could save the big investments that were used in the lifting stations while mitigating the environmental hazards. Cornell Mixing Zone Expert System (CORMIX) model is one of these mathematical simulation models. The study used surface discharge sub-model (CORMIX3) to define the mixing zone between the lifted drainage water from Mehalet Rough drain and the freshwater in Mit Yazid canal, by investigated biochemical oxygen demand (BOD) and total dissolved solids (TDS). The simulation results verified that the two investigated parameters met WQ standards for the Egyptian law 48/1982. BOD standard value was met after 448.36 m, in 723 s. TDS standard value was met after 4.46 m, in 7.8 s. This was far ahead of the first municipal station regardless low quality of these parameters in the drain. This is the first time to apply this model in the irrigation sector in Egypt, and the results were promising for defining the precise approach to reuse the drainage water in Egypt.

Investigation of attitude control actuators for large flexible space structures using inverse simulation

This paper proposes a modular mathematical model and Inverse Simulation methods to investigate a variety of attitude control actuators for Large Space Structures. The modular model is developed to allow for different actuator types to be easily implemented and combined, facilitating investigations into a variety of actuator configurations. The generic Inverse Simulation method allows for the inverse dynamic solution to be found for any configuration of actuators without any modifications to the solution process, facilitating rapid experimentation. Reaction wheels, magnetorquers, and solar pressure torque actuators are all considered with mass scaling laws ensuring that each actuator type is compared realistically. The investigations consider the limitations of each actuator type and the deformations experienced by the structure during a large slew manoeuvre. It is found that the distribution of smaller torques across the Large Space Structure reduces deformation and combinations of different actuator types, instead of a single type of actuator, allow for a good compromise between mass, power and structural deformation.

A novel optimization framework for natural gas transportation pipeline networks based on deep reinforcement learning

Natural gas is an emerging and reliable energy source in transition to a low-carbon economy. The natural gas transportation pipeline network systems are crucial when transporting natural gas from the production endpoints to processing or consuming endpoints. Optimizing the operational efficiency of compressor stations within pipeline networks is an effective way to reduce energy consumption and carbon emissions during transportation. This paper proposes an optimization framework for natural gas transportation pipeline networks based on deep reinforcement learning (DRL). The mathematical simulation model is derived from mass balance, hydrodynamics principles of gas flow, and compressor characteristics. The optimization control problem in steady state is formulated into a one-step Markov decision process (MDP) and solved by DRL. The decision variables are selected as the discharge ratio of each compressor. By the comprehensive comparison with dynamic programming (DP) and genetic algorithm (GA) in three typical element topologies (a linear topology with gun-barrel structure, a linear topology with branch structure, and a tree topology), the proposed method can obtain 4.60% lower power consumption than GA, and the time consumption is reduced by 97.5% compared with DP. The proposed framework could be further utilized for future large-scale network optimization practices.

Development of a control algorithm for a boost converter with the possibility of dynamic correction of control system parameters

RELEVANCE of the study lies in the development of an algorithm for controlling a DC voltage converter capable of providing a high-quality transient process with a wide change in the input parameters of the control object, affecting its nonlinear properties. purpose. THE PURPOSE. To consider methods for the development of continuous and discrete control systems for a step-up DC voltage converter and to obtain an analytical dependence of accounting for the nonlinear properties of the converter that affect the quality of regulation of the output voltage of the voltage stabilizer METHODS. The method of the average geometric root was chosen as a method for calculating the coefficients of the DC voltage converter control system, and the current circuit is adjusted using the technical optimum method, and the voltage circuit using the symmetric optimum method. The obtained analytical solutions of mathematical models and simulation models were compared in the SimInTech software environment. results. RESULTS. The simulation results show that the analytical solution of the mathematical model of the voltage stabilization system has a shorter transition time than the simulation results. This is due to the fact that in the mathematical model according to which the continuous control algorithm was synthesized, the presence of a power input filter, as well as the degree of their precharge, is not taken into account. Because of this, the transition time on simulation models is slower, applied 4 times than in the mathematical model. conclusion. CONCLUSION. When comparing the algorithms with each other, it can be seen that the algorithm obtained by converting a continuous algorithm by the Tusten method has the shortest transition time than all other algorithms. The continuous algorithm and the algorithm obtained by the inverse Euler transformation method have a speed close to each other, and the algorithm obtained by the direct Euler transformation turns out to be the slowest.

Theoretical analysis of the forming process of closed die forging with flash and optimization design method of flash gutter

The subject of this article is the forming process of closed die forging with flashes and the optimal design of the flash gutter dimensions. The goal is to conduct an in-depth theoretical analysis of the forming process of closed die forging with flash and to research the optimal design of the flash gutter dimension, aiming to improve the scientificity and efficiency of the forging process, guide the optimization of process parameters in actual production, extend the service life of dies, reduce material waste, and enhance product quality and production efficiency. The tasks were to establish an accurate mathematical model for closed die forging with flash to analyze metal plastic deformation and stress distribution, to conduct in-depth research on key factors such as stress distribution, position of the neutral plane, and flash gutter design during the forming process, and to validate the mathematical model through finite element simulation using DEFORM-2D software. The methods used include theoretical analysis, mathematical modeling, and finite element simulation validation. The theoretical analysis provides a foundation for understanding the forming process and stress distribution, whereas the mathematical model allows for quantitative analysis. Validation of the finite element simulation provides a means to test and refine the theoretical analysis and mathematical model. The following results were obtained: the existing mathematical model underestimates the height of the main deformation zone, which results in an unreasonable flash gutter design. After verification and correction, the error in the optimized mathematical model did not exceed 10 %, and the flash amount was significantly reduced. Additionally, a stress analysis of difficult-to-fill cavity positions revealed that the entrance radius of the cavity significantly affects the final filling. Conclusions. The scientific novelty of the results obtained is as follows: A mathematical model of closed die forging with flash was established to analyze the metal plastic deformation and stress distribution, providing theoretical support for die design optimization, forging quality improvement, cost reduction, and productivity improvement. Using the Deform-2D finite element simulation, the optimal design criterion for the flash was refined, resulting in a substantial reduction in the flash amount and material savings.

COMPARATIVE STUDY USING CFD OF COUNTER-CURRENT AND CO-CURRENT HYDROTREATING REACTORS USING JATROPHA CURCAS L VEGETABLE OIL

In this work, mathematical modeling and CFD simulation of two countercurrent and cocurrent hydrotreatment reactors were carried out, validating the results with a drained bed reactor (TBR), a commercial CoMo/γ-Al2O3 catalyst was used, the material the raw material was Jatropha Curcas L vegetable oil. The operating conditions were temperature 380 ° C, pressure 8 MPag. The kinetic model that was used considered 13 reactions that involve processes of decarboxylation, decarbonization, hydrodeoxygenation and hydrocracking reactions for triolein and tristearin triglycerides. The CFD simulation was carried out in Fluent 18.2 in a transient state and in 3D, considering the standard κ - ε turbulence models, Eulerian multiphase model and porous medium model, it was shown that the countercurrent reactor has less pressure drop than the countercurrent, the conversion the countercurrent reactor has a greater conversion of reactants of 99%, the generation of products from the countercurrent reactor has higher concentrations than the cocurrent reactor, this is because it has more contact areas between phases in the reactor.

Time scale analysis of enzymatic reduction of uric acid in a microfluidic biomedical device

Time Scale Analysis (TSA) is an investigative tool used in engineering design to identify locations in processes that should be a focus of Process Intensification (PI). Furthermore, TSA points to process variables and parameters that could be used to advance and measure PI improvement. However, TSA cannot suggest any specific design solution to intensify process performance. Instead, design engineers should use their fundamental knowledge and creative intelligence to specify detailed design transformations. TSA will then provide a specific quantitative measure of the improvement. TSA implementation improves an explicitly defined process performance, thus helping achieve process intensification goals. TSA is based on first principles, and it utilizes Characteristic Times (CT) such as diffusion, mean residence, and reaction times to improve an existing process. In this study, we specifically consider microfluidic biomedical devices. To illustrate the genesis of CT and TSA, we start by developing a mathematical model of an enzymatic degradation process in a biomedical device called iCore based on mass, momentum, and kinetic equations. After introducing user-defined scaling parameters, we extract CTs pertinent to the enzymatic degradation of uric acid in this microfluidic biomedical device. Diffusion coefficients, microchannel architectural characteristics, enzyme loading, hydrogel thickness, and characteristic parameters of enzyme kinetics are the parameters and process variables incorporated in this analysis. Finally, we compared the extracted CTs with a COMSOL Multiphysics parametric study to demonstrate how time scale analysis as a design tool and adjusting design parameters, such as diffusion coefficient, hydrogel layer thickness, substrate concentration, and enzyme concentration, can enhance the enzymatic reaction process without a need for complex computational modeling. It is crucial to recognize that pertinent CTs can be determined by understanding the type and nature of the observed process, previous experience, published data, and other foundational engineering design work. There is no need for mathematical modeling and numerical simulations to identify and acknowledge the CTs relevant and essential to the observed process; in this work, we only illustrate the principal origin of CTs via a detailed mathematical model of the process, as previously reported by Jovanovic et al. Therefore, in a routine application of TSA, it is important to remember that mathematical modeling and detailed numerical simulations are not necessary. This is a very comforting fact when TSA is deployed as a tool in higher-level process design functions. The investigations on how best to apply TSA in these higher level design functions such as Process Intensification, scale-up/numbering-up, change of device architecture, change of operating conditions, change of process feed characteristics, change of material physical and chemical properties, parametric optimization of the system for various objective functions, and techno-economic analysis, are yet to be studied and reported.

Development of a Mathematical Model of a Highly Maneuverable Robot for Simulation of Robots with Different Types of Designs

The article presents the results of developing a mathematical model and simulation modeling of a three-wheeled highly maneuverable mobile robot. A mathematical model of the robot in the state space has been developed. The possibility of using this robot with rotary modules for analyzing and testing control algorithms for robots of various designs has been considered. The relevance of the study is justified by the high costs of creating physical models of robots for experimental verification of control algorithms. The proposed three-wheeled mobile robot with rotary modules, where each wheel is simultaneously both a driving and a steering wheel, allows reducing these costs, while maintaining the ability to simulate part of the real operating conditions. Simplified diagrams of the robot are given, the main parameters and equations characterizing the change in linear and angular velocity are described. Particular attention is paid to modeling various types of robot drives: automotive type and with a differential drive. In the discrete state space, equations describing the dynamics of the robot were presented, which allows them to be used in software products for modeling. The results of simulation modeling obtained in the SimInTech software environment confirm the effectiveness of the proposed model. The analysis of the obtained results showed that the use of a three-wheeled robot with rotary modules allows successfully simulating the behavior of robots with other types of drives and creating conditions close to real ones for testing control algorithms. The proposed model can be used to improve the quality of design and testing of control algorithms in robotics, while reducing the costs of creating physical models of robots, as well as in the educational process.

A comparison of the acoustic waves generated in proton and carbon ion therapy

Hadron therapy, which employs particles such as protons and carbon-ions, is a promising method of cancer treatment due to its unique ability to deliver maximum energy at the Bragg peak near the tumor, sparing surrounding healthy tissue. Ionoacoustic waves, generated by thermal expansion from electronic collisions and localized heating, can be detected to optimize dose delivery and verify particle range, thus improving treatment precision. These waves offer a unique opportunity for comparative studies of different particle therapies. In this study, a mathematical model and computational simulations are used to compare the characteristics of ionoacoustic waves generated in tissue by proton and carbon-ion beams. In particular, we assess the impact of the nuclear fragmentation tail on the ionoacoustic signals generated in carbon-ion therapy. Our approach will allow us to make some important observations to study the comparative effects of proton and carbon-ion therapy. The aim of this work is to perform a comprehensive comparative analysis of ionoacoustic waves from proton and carbon-ion treatments, focusing on their potential for in-vivo range verification. This research addresses the current gap in understanding the use of ionoacoustic signals for range verification in ion beam therapy, which is critical given the growing clinical application of carbon ion therapy and its under-explored acoustic properties. This study pioneers the feasibility of using acoustic imaging from carbon-ion beams to detect the Bragg peak position and measure tumor dose in real-time. Carbon-ion dose mapping and relative biological effectiveness (RBE) assessment can be facilitated by real-time signal monitoring. Our study aims to significantly advance the field by addressing the lack of a verification technique for carbon-ion beams, focusing on the considerable impact of the nuclear fragmentation tail on ionoacoustic signal waveforms, which provides crucial insights into the unique energy deposition properties of carbon-ions.

Effect of infusion direction on convection-enhanced drug delivery to anisotropic tissue.

Convection-enhanced delivery (CED) can effectively overcome the blood-brain barrier by infusing drugs directly into diseased sites in the brain using a catheter, but its clinical performance still needs to be improved. This is strongly related to the highly anisotropic characteristics of brain white matter, which results in difficulties in controlling drug transport and distribution in space. In this study, the potential to improve the delivery of six drugs by adjusting the placement of the infusion catheter is examined using a mathematical model and accurate numerical simulations that account simultaneously for the interstitial fluid (ISF) flow and drug transport processes in CED. The results demonstrate the ability of this direct infusion to enhance ISF flow and therefore facilitate drug transport. However, this enhancement is highly anisotropic, subject to the orientation of local axon bundles and is limited within a small region close to the infusion site. Drugs respond in different ways to infusion direction: the results of our simulations show that while some drugs are almost insensitive to infusion direction, this strongly affects other compounds in terms of isotropy of drug distribution from the catheter. These findings can serve as a reference for planning treatments using CED.

Investigating the Influence of Die Structure on the Transverse Uniformity of Slot Coating

Abstract Transverse uniformity is an important measurement of the coating quality for slot coating. In this paper, the influence of die structure on the transverse uniformity is investigated according to a fully 3D mathematical modelling and numerical simulations. In the modelling part, the coating liquid is regarded as generalized Newtonian fluid and the fluid flow inner the die head is governed by the 3D incompressible Navier-Stokes equations. In solving the model, an efficient fractional step finite element method is used. Four kinds of commonly used die structures are simulated and analysed. The results show that the die structure has great influence on the transverse uniformity. Generally, dies with double cavities can get better transverse uniformity that single cavity.