Modelling and Simulation in Engineering
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Acceptance rate10%
Submission to final decision84 days
Acceptance to publication21 days
CiteScore3.000
Journal Citation Indicator0.530
Impact Factor3.2

Theoretical Hydrodynamic Modeling of the Fluidized Bed Photoreactor (FBP) Using Computational Fluid Dynamics (CFD): Fluidization Conditions for TiO2-CuO Immobilized on Beach Sand Granules

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Modelling and Simulation in Engineering aims to provide a forum for the discussion of formalisms, methodologies and simulation tools which relate to the modelling and simulation of human-centred engineering systems.

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Modelling and Simulation in Engineering maintains an Editorial Board of practicing researchers from around the world, to ensure manuscripts are handled by editors who are experts in the field of study.

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We currently have a number of Special Issues open for submission. Special Issues highlight emerging areas of research within a field, or provide a venue for a deeper investigation into an existing research area.

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Research Article

Parametric and Nonparametric Approaches of Reid Vapor Pressure Prediction for Gasoline Containing Oxygenates: A Comparative Analysis Using Partial Least Squares, Nonlinear, and LOWESS Regression Modelling Strategies with Physical Properties

This study provides insights into the challenges involved in predicting the Reid vapor pressure (RVP) of gasoline-oxygenate blends (GOB), which is an important indicator of fuel quality and compliance with environmental and performance standards. Given the enormous variety of gasoline compositions and ratios available, there is a significant demand for a fast, straightforward, and cost-effective technique to predict RVP without relying on costly instruments or complicated spectral measurements that involve numerous input variables. A comparative performance analysis has been performed for different regression modelling strategies for predicting RVP in GOB, which is valuable for researchers and practitioners in the petroleum industry for saving time and money. Parametric and nonparametric approaches were compared using partial least squares regression (PLSR), nonlinear regression (NLR), and nonparametric regression (NPR) models. Locally weighted scatterplot smoothing (LOWESS) approach was applied to the NPR model. The gasoline’s physical characteristics (distillation curves and density) formed the basis for the analysis of these models’ performances. Acceptable error metrics have been reached for root mean square error of calibration and prediction (RMSEC and RMSEP) values, for the PLSR, NLR, and NPR models, which are 4.790, 6.235, 4.739, 6.149, 3.968, and 6.029, respectively, which are close for those reported in literature. The NPR model eliminates parametric constraints and allows for a different kind of data structure to emerge. The established models here demonstrate a sound ability to overcome barriers by omitting the use of inconvenient spectral measurements to save expense and simplify data calibration, making them a promising approach for RVP detection of GOB. This finding aids in the development of more accurate RVP prediction models and contributes to the optimization of fuel formulations.

Research Article

Maximizing Electric Power Recovery through Advanced Compensation with MPPT Algorithms

The present investigation introduces an advanced methodology for maximum power point tracking (MPPT) applied to a piezo harvester scheme. A comprehensive rectifier circuit, equipped with an embedded MPPT component, is established to optimize energy production by monitoring a DC-DC inverter connected to the rectifier. Furthermore, the system’s sensitivity error has been finely tuned to dynamically adjust its impedance unit in real time, thereby optimizing load acquisition. This innovative approach seamlessly integrates the MPPT algorithm into the piezo harvester circuit. Moreover, the vehicle’s road handling is significantly augmented through the incorporation of a robust steering front and an active differential control system. Leveraging the MPPT module, the rectifier consistently achieves a power recovery efficiency exceeding 85%, independent of varying load conditions. Additionally, a DC-DC converter circuit has been seamlessly integrated to finely adjust the output voltage to meet specified levels. Numerical simulations demonstrate the effectiveness of the harvesting scheme, extracting a substantial output power of 90 W with an overall efficiency of 70%. The improved MPPT approach, employing angles of arrival (AoA) DV-Hop control strategies, minimizes the system’s power consumption based on the Global Positioning System (GPS). The utilization of Harris Hawks optimization (HHO) and the generation of quadrants in the four-quadrant operation mode of DC motors in the wireless sensor network (RCSFs) have been significantly enhanced in this study. Simulations reveal that, at a velocity of 50 km/h, shock absorbers utilizing the received signal strength indication (RSSI) can harvest between 60 and 90 W on a class C road, based on the time of arrival (TOA). Striking a balance in ride comfort using the time difference of arrival (TDOA) as a trade-off constitutes approximately 30% of the piezoelectric harvester (PEH) system’s power consumption when operating in active suspension mode, optimized by particle swarm optimization (PSO).

Research Article

Enhanced Noise Suppression in Partial Discharge Signals via SVD and VMD with Wavelet Thresholding

Partial discharge evaluation is a principal method for assessing insulation conditions in power transformers. Traditional singular value decomposition (SVD) approaches, however, face issues like high residual noise and loss of signal details in white noise suppression. This article introduces an advanced denoising algorithm integrating SVD, variational mode decomposition (VMD), and wavelet thresholding to effectively address mixed noise in on-site power transformer assessments. The algorithm initially employs SVD to suppress mixed noise, specifically targeting narrowband interference by decomposing the noisy signal and nullifying the corresponding singular values. Post-SVD, the signal is further processed through VMD, with its modal components refined via wavelet thresholding. The final reconstruction of these denoised components effectively eliminates white noise. Applied to an input signal with a signal-to-noise ratio of -27.593 dB, the proposed method achieves a postdenoising ratio of 13.654 dB. Comparative analysis indicates its superiority over existing algorithms in mitigating white noise and narrowband interference and more accurately restoring the partial discharge signal.

Research Article

Experimental Analysis of Static and Dynamic Performance for Continuous Warren Truss Steel Railway Bridge in Heavy Haul Railway

Continuous Warren truss steel railway bridges are one of the main forms of railway bridges. Due to the deterioration of materials and the long-term effect of loads, the bridges will inevitably experience performance degradation, which may lead to the failure of the bridge structure to continue to operate. In order to study the mechanical properties of steel structure bridges after material deterioration and long-term loads, a continuous Warren truss steel railway bridge that has been in operation for nearly 30 years (built in 1996) is used as the research object, and a combination of field tests and finite element (FE) simulations are used to carry out research on its mechanical properties under different loads. The research results show that after nearly 30 years of operation, the steel structure bridge has local damage, but the bearing capacity still meets the requirements of heavy-duty traffic. At this stage, the corrosion of the steel structure and the damage of the bearing should be repaired in time to prevent the damage from expanding.

Research Article

A Virtual Fabrication and High-Performance Design of 65 nm Nanocrystal Floating-Gate Transistor

Floating-gate transistor lies at the heart of many aspects of semiconductor applications such as neural networks, analog mixed-signal, neuromorphic computing, and especially in nonvolatile memories. The purpose of this paper was to design a high-performance nanocrystal floating-gate transistor in terms of a large memory window, low power, and extraordinary erasing speeds. Besides, the transistor achieves a thin thickness of the tunnel gate oxide layer. In order to obtain the high-performance design, this work proposed a set of structure parameters for the device such as the tunnel oxide layer thickness, Interpoly Dielectric (IPD), dot dimension, and dot spacing. Besides, this work was successful in the virtual fabrication process and methodology to fabricate and characterize the 65 nm nanocrystal floating-gate transistor. Regarding the results, while the fabrication process solves the limitation of the tunnel oxide layer thickness with the small value of 6 nm, the performance of the transistor has been significantly improved, such as 2.8 V of the memory window with the supply voltage of ±6 V at the control gate. In addition, the operation speeds are compatible, especially the rapid erasing speeds of 2.03 μs, 28.6 ns, and 1.6 ns when the low control gate voltages are ±9 V, ±12 V, and ±15 V, respectively.

Research Article

Modeling and Parametric Analysis of a Large-Scale Solar-Based Absorption Cooling System

This study investigates the thermodynamic performance of a solar-powered absorption cooling system. The system uses a lithium bromide-water (LiBr-H2O) absorption refrigeration system (ARS) integrated with evacuated solar collectors (ETSC) and thermal energy storage (TES) to provide a 3 kTR cooling capacity for a university campus. The paper examines the performance of the integrated system under different design and operating conditions as well as the performance of each subsystem, i.e., ETSC, TES, and ARS. Furthermore, a parametric energy and exergy analysis is applied, where different parameters are studied, such as the temperatures of the generator, the condenser, the evaporator, and the absorber. In addition, the system performance is examined with the variation in environmental conditions. The coefficient of performance (COP), exergetic efficiency, exergy destruction, and fuel depletion ratio (FDR) are used to evaluate the system’s performance. The ETSC and the TES are studied under the variation in solar radiation through the day in two seasons: summer and winter. The results revealed that the increase in generator temperature positively impacts the COP of the ARS while lowering the condenser and absorber temperature gives the same positive effect. Furthermore, the main reason for the exergy destruction is found to be the solar collector, which is responsible for destroying 89% of the input solar exergy. Additionally, 4.7% of the inlet exergy is destroyed in the generator, which makes 4.5% of the total exergy loss. The TES destroyed 4.8% of the total solar exergy input. The energy analysis shows that the ARS achieves an energetic COP of about 0.77, while the exergy analysis revealed that the exergetic COP is 0.21.

Modelling and Simulation in Engineering
 Journal metrics
See full report
Acceptance rate10%
Submission to final decision84 days
Acceptance to publication21 days
CiteScore3.000
Journal Citation Indicator0.530
Impact Factor3.2
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