Mathematical Simulation Research Articles

Hydrodynamic Analysis Of Water Hammer Phenomena In Hydropower Stations Under Turbine Extreme Operating Conditions

This research article investigates transient hydraulic effects, particularly water hammer phenomena, in a hydropower plant (HEPP) through a comprehensive mathematical model and simulation analysis. Utilizing methods of characteristics and FORTRAN programming, the study develops a model that incorporates water hammer considerations, including friction, in the water conveyance system of the HEPP. The system layout encompasses an upstream reservoir, penstock, turbine unit, and downstream reservoir. The research explores the influence of guide vane closure and pressure regulating valve (PRV) opening and closing laws on pressure variations, mass oscillations, and water level fluctuations within the system. Numerical results indicate that PRV failure may not significantly impact turbine speed, but it results in excessive pressure oscillations in the spiral casing head, exceeding allowable pressure control values. The study identifies a critical PRV diameter of 0.6m, causing a maximum pressure in the spiral case of 370m, surpassing the acceptable limit of 250m, with a speed rise rate exceeding 50%. Conversely, a PRV diameter greater than or equal to 0.9m leads to unnecessary water energy loss. The findings emphasize the importance of carefully selecting PRV parameters to optimize system stability and efficiency. The study's comprehensive analysis provides valuable insights into the interplay of various parameters, contributing to a scientific basis for optimizing operational parameters and ensuring reliable and efficient hydropower plant performance.
 

Dynamic stability analysis of CFRP sandwich structure reinforced by advanced nanocomposites via both machine learning method and mathematical simulation

This work introduces a quasi-3D refined theory for assessing the transient dynamic reactions of a sandwich annular sector plate subjected to mechanical shock loading. The sandwich structure has two facesheets composed of graphene origami (GOri)-enabled auxetic metal metamaterials (GOEAMs) and a core composed of carbon fiber reinforced polymer. The auxetic quality of the annular plates is mainly determined by the quantity of graphene and the level of folding in the GOri material. The elements are assessed layer by layer across the thickness of the plates. Micromechanical models supported by genetic programming may be used to predict the position-dependent Poisson’s ratio and other material parameters. The concept of Hamiltonian is used to deduce the governing equations of the structure. The equations of motion, which vary with time, are solved using the numerical solution process and the Laplace transform. A comprehensive parametric study is carried out to examine the influence of various geometric and physical parameters on the time-dependent behavior of annular sector plates. The current mathematical modeling results are being compared to the findings of previous works, as well as a machine learning technique. By using this machine learning methodology, it is feasible to computationally solve differential equations at a reduced expense, while simultaneously surmounting the challenge of formulation. To use machine learning techniques, a dependable dataset acquired from either experimental or numerical analysis is necessary. The dataset was created using the quantitative findings of the investigation. Furthermore, the machine learning technique demonstrates its capacity to provide very precise outcomes when predicting the transient behavior of the existing structure under novel loading and boundary circumstances.

Transition to the Fluid Dynamic Limit: Mathematical Models and Simulation Results

Numerical simulations of standard situations in the transition region from gas kinetics to fluid dynamics at small Mach numbers indicate a clear dependence of the simulation results on the underlying kinetic model (here: nonlinear and linearized Boltzmann collision operator vs. BGK relaxation model). We develop an improved mathematical framework (trace theory) to explain these differences. In particular we reveal certain deficiencies for the classical BKG system as well as for the standard Navier Stokes approach.

Mathematical simulation modeling analysis of sub-sea tunnel blasting based on grey correlation

Blasting in the ocean tunnel has a great impact on Marine life and seabed vegetation, so it is necessary to control the impact of blasting vibration on the surrounding Marine environment. In this paper, taking Xiamen Tunnel as an example, the blasting vibration response characteristics of undersea tunnel are studied, and the velocity attenuation rules of tunnel structure in different directions are obtained. The grey correlation theory is innovatively applied to analyze the correlation degree of factors affecting the blasting vibration effect of the undersea tunnel, and the key factors and secondary factors affecting the blasting vibration effect of the tunnel are determined. The grey correlation theory is used to analyze the correlation degree between the blasting vibration effect of the cross-tunnel, which is conducive to improving the safety and stability of tunnel construction. It provides a new idea and method for vibration control of similar projects.

Inherently integrated microfiber-based flexible proprioceptive sensor for feedback-controlled soft actuators

For the accurate and continuous control of soft actuators in dynamic environments, the movements of the soft actuators must be monitored in real-time. To this end, various soft actuators capable of self-monitoring have been developed by separately integrating sensing devices into actuators. However, integrating such heterogeneous sensing components into soft actuators results in structural complexity, high manufacturing costs, and poor interfacial stability. Here, we report on intelligent pneumatic fiber-reinforced soft actuators with an inherent flexible proprioceptive sensor that uses only the essential components of typical fiber-reinforced soft actuators. The inherent flexible proprioceptive sensor is achieved by leveraging two parallel conductive microfibers around an elastomeric chamber of the soft actuator, which simultaneously acts as both a capacitive bending sensor and radial expansion limiting fibers of typical fiber-reinforced soft actuators. The proprioceptive soft actuator exhibits excellent mechanical actuation up to 240° bending motion and proprioceptive sensing performance with high sensitivity of 1.2 pF rad−1. Mathematical analysis and simulations of the soft actuator can effectively predict the bending actuation and capacitive responses against input pressures. We demonstrate that proprioceptive soft actuators can be used to construct a soft gripping system and prosthetic hand which express various hand gestures and perform dexterous manipulation with real-time proprioceptive sensing capability.

Comparison of pollutant emissions from various types of vehicles

This article compares the equivalent emissions from battery electric vehicles (BEVs) with those of internal combustion engines vehicles (ICEVs) and and hybrid vehicles (HV). The considerations focused on the dependence of the equivalent emission from electric cars on the official/national Polish energy mix (which is still mainly based on hard coal). The results of mathematical simulations of the impact of the fuel type on pollutants’ emissions are presented. The article also focuses on the effects of the fuel used in internal combustion engines vehicles (LPG, CNG, petrol, diesel, hydrogen) and the official/national Polish energy mix for battery electric vehicles on carbon dioxide (CO2), nitrogen oxides (NOX), particulate matter (PM), carbon monoxide (CO) and sulphur dioxide (SO2) emissions.

Application of quantitative protein mass spectrometric data in the early predictive analysis of membrane-bound target engagement by monoclonal antibodies.

Model-informed drug discovery advocates the use of mathematical modeling and simulation for improved efficacy in drug discovery. In the case of monoclonal antibodies (mAbs) against cell membrane antigens, this requires quantitative insight into the target tissue concentration levels. Protein mass spectrometry data are often available but the values are expressed in relative, rather than in molar concentration units that are easier to incorporate into pharmacokinetic models. Here, we present an empirical correlation that converts the parts per million (ppm) concentrations in the PaxDb database to their molar equivalents that are more suitable for pharmacokinetic modeling. We evaluate the insight afforded to target tissue distribution by analyzing the likely tumor-targeting accuracy of mAbs recognizing either epidermal growth factor receptor or its homolog HER2. Surprisingly, the predicted tissue concentrations of both these targets exceed the Kd values of their respective therapeutic mAbs. Physiologically based pharmacokinetic (PBPK) modeling indicates that in these conditions only about 0.05% of the dosed mAb is likely to reach the solid tumor target cells. The rest of the dose is eliminated in healthy tissues via both nonspecific and target-mediated processes. The presented approach allows evaluation of the interplay between the target expression level in different tissues that determines the overall pharmacokinetic properties of the drug and the fraction that reaches the cells of interest. This methodology can help to evaluate the efficacy and safety properties of novel drugs, especially if the off-target cell degradation has cytotoxic outcomes, as in the case of antibody-drug conjugates.

A hybrid step-up converter for PV integration with wide input variation acceptability: comprehensive performance and reliability assessment

Abstract A high-step-up DC–DC converter (DDC) is commonly used in micro-grids, renewable energy source (RES) integration, uninterruptible power supplies, hybrid vehicles, and other applications to deal with intermittency in power sources. Solar photovoltaic (SPV) is a prominent RES due to its many benefits, but its output voltage must be enhanced for high-voltage (HV) applications; hence, various topologies are suggested for desirable gain in the literature. Nevertheless, contemporary topologies exhibit restricted gain, higher device stress, analysis on restricted performance metrics, constrained handling capacity for input variations, relatively lower reliability, and suboptimal device utilization. This work investigates a new Z-source with switched-capacitor (HZSSC)-based hybrid step-up converter to solve the aforementioned restrictions and adapt PV voltage dynamics. Additionally, this paper presents MIL-HDBK-217F-based methodology for evaluating converter-level reliability, assessing the implications of device parametric variation on overall reliability, conducting a detailed analysis of figure of merits, performing thermal modeling, and executing small-signal-modeling to demonstrate operational efficacy. In-depth mathematical analysis of both continuous conduction mode (CCM) and discontinuous conduction mode (DCM) are conducted. The detailed comparison analysis shows that the suggested converter outperforms traditional converters in voltage-gain, voltage-stress, device-utilization, and reliability. Additionally, a 400 W, 220 V laboratory-scaled prototype shows 68 % reliability after 20 years. The hardware test outcomes validate the accuracy of both the mathematical investigation and simulation findings.

Mathematical simulation of radar scattering characteristics of ultra-short-pulse signals on complex shape objects

The article discusses the method of mathematical modeling of characteristics of scattering of ultrashort-pulse signals of complex shape objects, taking into account the shape of the envelope of the ultrashort-pulse radio signal and the features of radiation of an ultrawideband antenna. To estimate the reflecting properties of objects, the determination of the ultra-short-pulse radar cross section of complex shape objects with their radar location by non-harmonic signals is given. The mathematical model of radar scattering characteristics of location objects under ultra-short-pulse signals takes into account the shape of the envelope of the signal generated by a transmitter of a single-chip microchip NVA 6100 with duration of 300 ps and obtained through direct measurements. The electric scattering field of a location object in the frequency domain is determined on the use of a polygonal model of the object and asymptotic methods of diffraction theory. The transfer function of the Vivaldi antenna to radiation obtained by numerical modeling using the method of moments was used in the electric field calculations. Verification of the developed mathematical model was carried out on the basis of determining the ultra-short pulse radar cross section of perfect electric conductive sphere. A diagram of the ultra-short-pulse radar cross section of the GPS satellite was obtained, taking into account the radiation of the ultra-short-pulse signal by the Vivaldi antenna. The diagram of ultra-short pulse radar cross section of GPS satellite does not contain interference maxima and minima, and the averaged values ultra-short radar cross section of GPS satellite from lateral angles are on average 3..8 times less than radar cross section at the center frequency of the spectrum. The mathematical model of radar scattering characteristics of location objects under ultra-short-pulse signals is intended for preliminary estimates of the ultra-short-pulse radar cross section at an early step of designing ultra-wideband radars. The obtained estimates of the ultra-short-pulse radar cross section of the GPS satellite make it possible to identify the main features in the scattering of ultra-short-pulse signals at the location of extended targets.

Mathematical Simulation and Technical Feasibility of Floating Solar Systems Installation in Hydroelectric Power Reservoirs in Brazil

Mathematical Simulation and Technical Feasibility of Floating Solar Systems Installation in Hydroelectric Power Reservoirs in Brazil

A new CO2 refrigeration system with two-phase ejector and parallel compression for supermarkets

This study explores the integration of parallel compression and a two-phase ejector in transcritical CO2 refrigeration systems, aiming to improve efficiency and performance. This innovative approach bridges the gap between conventional approaches and explores new energy-saving potential. The study uses thermodynamic modeling, mathematical simulation, and in-depth analysis to look at energy and exergy performance in a new configuration for applications in the retail sector at medium evaporation temperatures. The work investigates thermodynamic phenomena in a novel cycle with steady-state conditions, low pressure differentials, and adiabatic efficiency. The model is validated against experimental and theoretical published data, revealing component-specific exergy destruction and key parameters. The novel cycle efficiently extracts heat at higher temperatures, outperforming conventional and parallel cycles. Exergetic efficiency surpasses the standard cycle, with gas cooler pressure and temperature dependence enhancing efficiency by 40%–45%. The distribution of exergy destruction percentages reveals efficiency determinants, emphasizing heat exchange optimization and ejector responsiveness in energy dissipation dynamics. The study investigates the coefficient of performance (COP) dependence on gas cooler pressure and temperature, revealing superior performance compared to conventional cycles. COP increases by 50% at 80 bars, indicating enhanced efficiency. The new cycle offers exceptional efficiency gains, with a COP enhancement of over 75% for evaporator temperature transitions. Comparative analysis shows a COP superiority of up to 53% for lower evaporator temperatures and 20% for higher evaporator temperatures, demonstrating substantial energy savings and improved performance across various operating conditions.

Electric Traction System Technology as a Solution to African Transportation Industries

The electric traction system in the case of Africa is highly advantageous in terms of transportation. The electric traction system is designed to provide a DC output source from an AC source of 33kV/230V for suitable mobility of tract devices without minimum frequency change. In this work, electric traction system analysis was obtained using mathematical models and simulation of tracts system components using MATLAB. Due to the application of FACTs devices, a 12-pulse thyristor rectifier is used for rectification. The system components are an energy source, harmonic filter, step-down transformer, rectifier substation, and DC load. The maximum current of total harmonic distortion obtained is certified with the IEEE standard 5% total harmonic distortion. the output voltage is purely stable, and the power factor quality is improved.

Mathematical Simulation for Right of Way Corridor for Overhead Transmission Line

Transmission lines play a vital role in the operation of a reliable electrical power system and that is why the transmission line system is considered as a lifeline system for power supply. The transmission line traverses across the length and breadth of the country, and it crosses all the natural reserves like forests, rivers, vegetation, mountains, etc., to make the system effective, Right of Way (ROW) plays a decisive role in the transmission line. But in today’s growing population and economy, land acquisition for the construction of transmission lines is a major bottleneck. This leads to huge compensations for the utilities and a threat to the natural resources. This paper attempts to arrive at a mathematical simulation for effective ROW by studying different codal provisions and utility practices. The approach is made to make efficient use of the land available without compromising any relevant parameters for ROW.

Mathematical Simulation of Isotope Exchange in Flexible Manufacturing Systems with Electrochemical Phase Flux Reversal

Mathematical Simulation of Isotope Exchange in Flexible Manufacturing Systems with Electrochemical Phase Flux Reversal

Power Management Strategy of a PEM Fuel Cell-Battery Powered Electric Vehicle

A MATLAB-Simulink based mathematical vehicle simulation model is developed in this investigation to analyze power management strategy of a proton exchange membrane (PEM) fuel cell and battery powered electric vehicle. The vehicle simulation model incorporated a real-world commercial passenger vehicle operator’s drive cycle inputs and associated vehicle dynamics to determine accurate estimation of total onboard power requirements and withdrawal of power from the fuel cell and battery sources to meet the demand. The power management strategy is designed to meet the vehicle’s onboard power demand based on the availability of hybrid combination of fuel cell and battery power sources. The fuel cell stack is the primary power source of the vehicle. The fuel cell is also charging the battery with excess power produced onboard and hence controls the state-of-charge of the battery. Battery is used as a supplemental power source for meeting the vehicle’s peak power demands. The parameters are optimized to implement the power management strategy by considering the battery state-of-the charge, the drive torque and the vehicle drive performance. The model simulation results with optimized parameters showed that the power requirement of the electric vehicle was significantly affected by the combination of fuel cell and battery power management system as well as the operating behaviors of the end user (driver).

Construction and Analysis of a New Resting-State Whole-Brain Network Model.

Mathematical modeling and computer simulation are important methods for understanding complex neural systems. The whole-brain network model can help people understand the neurophysiological mechanisms of brain cognition and functional diseases of the brain. In this study, we constructed a resting-state whole-brain network model (WBNM) by using the Wendling neural mass model as the node and a real structural connectivity matrix as the edge of the network. By analyzing the correlation between the simulated functional connectivity matrix in the resting state and the empirical functional connectivity matrix, an optimal global coupling coefficient was obtained. Then, the waveforms and spectra of simulated EEG signals and four commonly used measures from graph theory and small-world network properties of simulated brain networks under different thresholds were analyzed. The results showed that the correlation coefficient of the functional connectivity matrix of the simulated WBNM and empirical brain networks could reach a maximum value of 0.676 when the global coupling coefficient was set to 20.3. The simulated EEG signals showed rich waveform and frequency-band characteristics. The commonly used graph-theoretical measures and small-world properties of the constructed WBNM were similar to those of empirical brain networks. When the threshold was set to 0.22, the maximum correlation between the simulated WBNM and empirical brain networks was 0.709. The constructed resting-state WBNM is similar to a real brain network to a certain extent and can be used to study the neurophysiological mechanisms of complex brain networks.

Computational Rhinology: Unraveling Discrepancies between In Silico and In Vivo Nasal Airflow Assessments for Enhanced Clinical Decision Support.

Computational rhinology is a specialized branch of biomechanics leveraging engineering techniques for mathematical modelling and simulation to complement the medical field of rhinology. Computational rhinology has already contributed significantly to advancing our understanding of the nasal function, including airflow patterns, mucosal cooling, particle deposition, and drug delivery, and is foreseen as a crucial element in, e.g., the development of virtual surgery as a clinical, patient-specific decision support tool. The current paper delves into the field of computational rhinology from a nasal airflow perspective, highlighting the use of computational fluid dynamics to enhance diagnostics and treatment of breathing disorders. This paper consists of three distinct parts-an introduction to and review of the field of computational rhinology, a review of the published literature on in vitro and in silico studies of nasal airflow, and the presentation and analysis of previously unpublished high-fidelity CFD simulation data of in silico rhinomanometry. While the two first parts of this paper summarize the current status and challenges in the application of computational tools in rhinology, the last part addresses the gross disagreement commonly observed when comparing in silico and in vivo rhinomanometry results. It is concluded that this discrepancy cannot readily be explained by CFD model deficiencies caused by poor choice of turbulence model, insufficient spatial or temporal resolution, or neglecting transient effects. Hence, alternative explanations such as nasal cavity compliance or drag effects due to nasal hair should be investigated.

Coastline stability analysis of Zhoushan-Liuheng lng terminal project based on remote sensing

Seabed evolution research around Zhoushan Liuheng LNG receiving station project, which mainly includes collecting, analyzing and sorting data of environmental investigation, was conducted by the second Institute of Oceanography, MMR. Based on the data of remote sensing and field survey for different years, the comprehensive research methods of dynamic geomorphology, sedimentology, stratigraphy and mathematical simulation are used to carry out the geomorphological investigation of the sea area near the Zhoushan Liuheng LNG terminal project. This paper makes a detailed analysis of the beach dynamics, seabed scouring and silting change characteristics of the project sea area, and makes a prediction of the beach channel scouring and silting adjustment trend caused by sea related projects, which provides a scientific basis for optimizing the plane layout of Zhoushan Liuheng LNG receiving station project and insight for other researchers who focus on coastline change and remote sensing.

Mathematical Simulation of the Influence of Acoustic on the Efficiency of PM 2.5 Coagulation

The particles of micron and submicron sizes (PM 2.5 and less) in gas environments pose a significant danger to humanity due to the emergence of specific and very dangerous diseases of the cardiovascular, respiratory, and immune systems of the human body. Such particles are the most difficult to detect; therefore, their effects on human health have only been discovered in recent decades. Classical ultrasonic coagulation by sinusoidal action turns out to be ineffective for PM 2.5 due to the peculiarities of the physical mechanisms of hydrodynamic and orthokinetic interaction realized in gaseous media. This article presents a theoretical justification for choosing ways to increase the efficiency of ultrasonic coagulation of PM 2.5 by creating special conditions under which nonlinear disturbances of the velocity and pressure of the gas phase in the ultrasonic field occur. The authors performed simulations of ultrasonic coagulation under nonlinear disturbances of the velocity (vortex) and the pressure (shock waves), which has numerical difficulties due to the instability of existing methods. As a result of the numerical analysis, the possibility of increasing the coagulation rate of particles in the submicron size range up to limit values (13 times due to nonlinear pressure disturbances, and an additional increase of at least 2 times due to aerosol compaction in the vortex field of gas velocity) was shown.

Mathematical Simulation of Bio-Heat Transfer in Tissues Having Five Layers in the Presence of a Tumor Zone

A presence of tumor zones within biological tissues can be defined during the analysis of the skin surface temperature. This research is devoted to mathematical simulation of the time-dependent bio-heat transfer in tissues under a tumor influence. The one-dimensional partial differential equation of the Pennes model has been used for description of bio-heat transfer within the biological tissue with five layers, namely, epidermis, papillary dermis, reticular dermis, subcutaneous adipose tissue, and a muscle layer. The formulated boundary-value problem has been solved using the developed in-house computational code based on the finite difference schemes. The developed numerical algorithm has been verified using analytical and numerical solutions of other authors for the simpler test problem. As a result of this study, the temperature distributions have been obtained for the tissue in the presence of tumor zones in different layers of the skin. The influence of five layers of skin on the temperature distribution has been investigated, and the dependence for the skin surface temperature on the tumor zone location has been obtained. The obtained outcomes illustrate the effectiveness of this technique of cancer diagnosis and identify the optimal parameters for its application. Thus, this work represents an important step in the development of cancer diagnosis methods using thermography. The results obtained can be used to improve the accuracy of diagnosis and develop new treatment methods.