Journal Description
Modelling
Modelling
is an international, peer-reviewed, open access journal on theory and applications of modelling and simulation in engineering science, published quarterly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 21.5 days after submission; acceptance to publication is undertaken in 3.4 days (median values for papers published in this journal in the second half of 2022).
- Recognition of Reviewers: APC discount vouchers, optional signed peer review, and reviewer names published annually in the journal.
Latest Articles
Machine Learning Methods for Diabetes Prevalence Classification in Saudi Arabia
Modelling 2023, 4(1), 37-55; https://doi.org/10.3390/modelling4010004 - 25 Jan 2023
Abstract
Machine learning algorithms have been widely used in public health for predicting or diagnosing epidemiological chronic diseases, such as diabetes mellitus, which is classified as an epi-demic due to its high rates of global prevalence. Machine learning techniques are useful for the processes
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Machine learning algorithms have been widely used in public health for predicting or diagnosing epidemiological chronic diseases, such as diabetes mellitus, which is classified as an epi-demic due to its high rates of global prevalence. Machine learning techniques are useful for the processes of description, prediction, and evaluation of various diseases, including diabetes. This study investigates the ability of different classification methods to classify diabetes prevalence rates and the predicted trends in the disease according to associated behavioural risk factors (smoking, obesity, and inactivity) in Saudi Arabia. Classification models for diabetes prevalence were developed using different machine learning algorithms, including linear discriminant (LD), support vector machine (SVM), K -nearest neighbour (KNN), and neural network pattern recognition (NPR). Four kernel functions of SVM and two types of KNN algorithms were used, namely linear SVM, Gaussian SVM, quadratic SVM, cubic SVM, fine KNN, and weighted KNN. The performance evaluation in terms of the accuracy of each developed model was determined, and the developed classifiers were compared using the Classification Learner App in MATLAB, according to prediction speed and training time. The experimental results on the predictive performance analysis of the classification models showed that weighted KNN performed well in the prediction of diabetes prevalence rate, with the highest average accuracy of 94.5% and less training time than the other classification methods, for both men and women datasets.
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Open AccessEditorial
Acknowledgment to the Reviewers of Modelling in 2022
Modelling 2023, 4(1), 35-36; https://doi.org/10.3390/modelling4010003 - 18 Jan 2023
Abstract
High-quality academic publishing is built on rigorous peer review [...]
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Open AccessArticle
IndShaker: A Knowledge-Based Approach to Enhance Multi-Perspective System Dynamics Analysis
Modelling 2023, 4(1), 19-34; https://doi.org/10.3390/modelling4010002 - 23 Dec 2022
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Decision making as a result of system dynamics analysis requires, in practice, a straightforward and systematic modeling capability as well as a high-level of customization and flexibility to adapt to situations and environments that may vary very much from each other. While in
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Decision making as a result of system dynamics analysis requires, in practice, a straightforward and systematic modeling capability as well as a high-level of customization and flexibility to adapt to situations and environments that may vary very much from each other. While in general terms a completely generic approach could be not as effective as ad hoc solutions, the proper application of modern technology may facilitate agile strategies as a result of a smart combination of qualitative and quantitative aspects. In order to address such complexity, we propose a knowledge-based approach that integrates the systematic computation of heterogeneous criteria with open semantics. The holistic understanding of the framework is described by a reference architecture and the proof-of-concept prototype developed can support high-level system analysis, as well as being suitable within a number of applications contexts—i.e., as a research/educational tool, communication framework, gamification and participatory modeling. Additionally, the knowledge-based philosophy, developed upon Semantic Web technology, increases the capability in terms of holistic knowledge building and re-use via interoperability. Last but not least, the framework is designed to constantly evolve in the next future, for instance by incorporating more advanced AI-powered features.
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Open AccessArticle
Damage Evolution Prediction during 2D Scale-Model Tests of a Rubble-Mound Breakwater: A Case Study of Ericeira’s Breakwater
Modelling 2023, 4(1), 1-18; https://doi.org/10.3390/modelling4010001 - 20 Dec 2022
Abstract
Melby presents a formula to predict damage evolution in rubble-mound breakwaters whose armour layer is made of rock, based on the erosion measured in scale-model tests and the characteristics of the incident sea waves in such tests. However, this formula is only valid
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Melby presents a formula to predict damage evolution in rubble-mound breakwaters whose armour layer is made of rock, based on the erosion measured in scale-model tests and the characteristics of the incident sea waves in such tests. However, this formula is only valid for armour layers made of rock and for the range of tested sea states. The present work aims to show how the Melby methodology can be used to establish a similar formula for the armour layer damage evolution in a rubble-mound breakwater where tetrapods are employed. For that, a long-duration test series is conducted with a 1:50 scale model of the quay section of the Ericeira Harbour breakwater. The eroded volume of the armour layer was measured using a Kinect position sensor. The damage parameter values measured in the experiments are lower than those predicted by the formulation for rock armour layers. New and coefficients for the Melby formula for the tested armour layer were established based on the minimum root mean square error between the measured and the predicted damage. This work shows also that it is possible to assess the damage evolution in scale-model tests with rubble-mound breakwaters by computing the eroded volume and subsequently, the dimensionless damage parameter based on the equivalent removed armour units.
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(This article belongs to the Special Issue Ocean and Coastal Modelling)
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Open AccessArticle
Empirical Modeling of Transverse Displacements of Single-Sided Transversely Cracked Prismatic Tension Beams
Modelling 2022, 3(4), 481-498; https://doi.org/10.3390/modelling3040031 - 16 Dec 2022
Abstract
While the effects of axial compression on beams have long been known, the effect of tensile axial loads on one-sided transversely cracked beams is less known. The crack namely shifts the position of the resultant of the axial normal stresses deeper into the
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While the effects of axial compression on beams have long been known, the effect of tensile axial loads on one-sided transversely cracked beams is less known. The crack namely shifts the position of the resultant of the axial normal stresses deeper into the uncracked part of the cross-section, and the crack tends to open, causing a transverse displacement. Therefore, this paper focuses on empirical modeling of the considered phenomenon for slender prismatic beams in order to establish a suitable 1D computational model based on detailed 3D FE mesh results. This goal can be achieved through the already established simplified model, where the crack is represented by an internal hinge endowed with a rotational spring. Several analyses of various beams differing in geometry, crack locations, and boundary conditions were executed by implementing 3D FE meshes to establish the appropriate model’s bending governing differential equation. After that, the corresponding parameter definitions were calibrated from the database of 3D FE models. By redefining the model’s input parameters, a suitable solution is achieved, offering a good balance between the results’ accuracy and the required computational effort. The functionality of the newly obtained solutions was verified through some comparative case studies that supplement the derivations.
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(This article belongs to the Special Issue Modeling Dynamic Fracture of Materials)
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Open AccessArticle
Efficient Hydrodynamic Modelling of Urban Stormwater Systems for Real-Time Applications
Modelling 2022, 3(4), 464-480; https://doi.org/10.3390/modelling3040030 - 17 Nov 2022
Cited by 1
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Urban water drainage systems represent complex networks with nonlinear dynamics and different types of interactions. This yields an involved modeling problem for which different off-line simulation approaches are available. Nevertheless, these approaches cannot be used for real-time simulations, i.e., running in parallel to
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Urban water drainage systems represent complex networks with nonlinear dynamics and different types of interactions. This yields an involved modeling problem for which different off-line simulation approaches are available. Nevertheless, these approaches cannot be used for real-time simulations, i.e., running in parallel to weather now- and forecasts and enabling the monitoring and automatic control of urban water drainage systems. Alternative approaches, used commonly for automation purposes, involve parameterized linear delay systems, which can be used in real-time but lack the necessary level of detail, which, in particular, is required for adequate flood risk prognostics. Given this setup, in the present paper, an approach for the effective modeling of detailed water drainage systems for real-time applications implemented with the open-source Storm Water Management Model (SWMM) software is addressed and exemplified for a part of the water drainage system of the city of Flensburg in northern Germany. Additionally, a freely available early-warning system prototype is introduced and used to combine weather forcast information on a 2-h prediction horizon with the developed model and available measurements. This prototype is subsequently used for data assimilation using the ensemble Kalman filter (EnKF) for the considered area in Flensburg.
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Open AccessArticle
Mathematical Modeling of Electrical Circuits and Practical Works of Increasing Difficulty with Classical Spreadsheet Software
Modelling 2022, 3(4), 445-463; https://doi.org/10.3390/modelling3040029 - 17 Nov 2022
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This paper presents a modeling practical works project of electrical engineering, proposed to the first-year students of the University Institute of Technology in France, during the COVID-19 pandemic. The objective of this paper is twofold. The first objective is to present to the
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This paper presents a modeling practical works project of electrical engineering, proposed to the first-year students of the University Institute of Technology in France, during the COVID-19 pandemic. The objective of this paper is twofold. The first objective is to present to the students the opportunities of modeling and calculation development of a spreadsheet software in their professional lives. The second objective is to create a file that automatically calculates all the current and voltage values at each point of any alternative electrical circuit. The aim of this paper, geared toward students, is to bring them to build their own numerical remote lab, autonomously. Therefore, pedagogical keys are given along the reading of this document to help them to progress, both on electrical circuits conceptual understanding with series and parallel RLC circuits and on their computation in a spreadsheet software. As a conclusion, this paper can be used as a base to develop remote modeling practical works of many and different devices, as well as a database starting point of such analytical models.
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Open AccessArticle
Numerical Analysis of the Radial Load, Pressure and Velocity Fields of a Single Blade Pump
Modelling 2022, 3(4), 434-444; https://doi.org/10.3390/modelling3040028 - 25 Oct 2022
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The centrifugal screw-type pump is a type of pump which, due to its hydraulic and mechanical properties, is used in several areas of the industry (e.g., for sludge and rainwater disposal). To avoid impeller passage clogging, the 3D impeller geometry is designed as
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The centrifugal screw-type pump is a type of pump which, due to its hydraulic and mechanical properties, is used in several areas of the industry (e.g., for sludge and rainwater disposal). To avoid impeller passage clogging, the 3D impeller geometry is designed as a helically curved blade added to a conical hub. The passability through the fluid canal of the modelled impeller is 100 mm. In this paper, the magnitude of the radial force on an impeller blade is investigated as a function of the flow rate. The digital model was designed in Catia V5 and calculated using the commercial Ansys CFX software. A numerical computational fluid dynamics (CFD) method was used to investigate the performance characteristics of the pump, specifically discussing internal flow conditions such as velocity, pressure and the radial force mentioned above.
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Open AccessSystematic Review
Discrete-Event Simulation in Healthcare Settings: A Review
by
and
Modelling 2022, 3(4), 417-433; https://doi.org/10.3390/modelling3040027 - 14 Oct 2022
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We review and define the current state of the art as relating to discrete event simulation in healthcare-related systems. A review of published literature over the past five years (2017–2021) was conducted, building upon previously published work. PubMed and EBSCOhost were searched for
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We review and define the current state of the art as relating to discrete event simulation in healthcare-related systems. A review of published literature over the past five years (2017–2021) was conducted, building upon previously published work. PubMed and EBSCOhost were searched for journal articles on discrete event simulation in healthcare resulting in identification of 933 unique articles. Of these about half were excluded at the title/abstract level and 154 at the full text level, leaving 311 papers to analyze. These were categorized, then analyzed by category and collectively to identify publication volume over time, disease focus, activity levels by country, software systems used, and sizes of healthcare unit under study. A total of 1196 articles were initially identified. This list was narrowed down to 311 for systematic review. Following the schema from prior systematic reviews, the articles fell into four broad categories: health care systems operations (HCSO), disease progression modeling (DPM), screening modeling (SM), and health behavior modeling (HBM). We found that discrete event simulation in healthcare has continued to increase year-over-year, as well as expand into diverse areas of the healthcare system. In addition, this study adds extra bibliometric dimensions to gain more insight into the details and nuances of how and where simulation is being used in healthcare.
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Open AccessArticle
Derivation of Cyclic Stiffness and Strength Degradation Curves of Sands through Discrete Element Modelling
by
and
Modelling 2022, 3(4), 400-416; https://doi.org/10.3390/modelling3040026 - 30 Sep 2022
Cited by 1
Abstract
Cyclic degradation in fully saturated sands is a liquefaction phenomenon characterized by the progressive variation of the soil strength and stiffness that occurs when the soil is subjected to cyclic loading in undrained conditions. An evaluation of the relationships between the degradation of
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Cyclic degradation in fully saturated sands is a liquefaction phenomenon characterized by the progressive variation of the soil strength and stiffness that occurs when the soil is subjected to cyclic loading in undrained conditions. An evaluation of the relationships between the degradation of the soil properties and the number of loading cycles is essential for deriving advanced cyclic constitutive soil models. Generally, the calibration of cyclic damage models can be performed through controlled laboratory tests, such as cyclic triaxial testing. However, the undrained response of soils is dependent on several factors, such as the fabric, sample preparation, initial density, initial stress state, and stress path during loading; hence, a large number of tests would be required. On the other hand, the Discrete Element Method offers an interesting approach to simulating the complex behavior of an assembly of particles, which can be used to perform simulations of geotechnical laboratory testing. In this paper, numerical triaxial analyses of sands with different consistencies, loose and medium-dense states, were performed. First, static triaxial testing was performed to characterize the sand properties and validate the results with the literature data. Then, cyclic undrained triaxial testing was performed to investigate the impact of the number of cycles on the cyclic degradation of the soil stiffness and strength. Laws that can be used in damage soil models were derived.
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(This article belongs to the Section Modelling in Engineering Structures)
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Open AccessArticle
Modelling the Energy Consumption of Driving Styles Based on Clustering of GPS Information
Modelling 2022, 3(3), 385-399; https://doi.org/10.3390/modelling3030025 - 02 Sep 2022
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This paper presents a novel approach to distinguishing driving styles with respect to their energy efficiency. A distinct property of our method is that it relies exclusively on the global positioning system (GPS) logs of drivers. This setting is highly relevant in practice
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This paper presents a novel approach to distinguishing driving styles with respect to their energy efficiency. A distinct property of our method is that it relies exclusively on the global positioning system (GPS) logs of drivers. This setting is highly relevant in practice as these data can easily be acquired. Relying on positional data alone means that all features derived from them will be correlated, so we strive to find a single quantity that allows us to perform the driving style analysis. To this end we consider a robust variation of the so-called "jerk" of a movement. We give a detailed analysis that shows how the feature relates to a useful model of energy consumption when driving cars. We show that our feature of choice outperforms other more commonly used jerk-based formulations for automated processing. Furthermore, we discuss the handling of noisy, inconsistent, and incomplete data, as this is a notorious problem when dealing with real-world GPS logs. Our solving strategy relies on an agglomerative hierarchical clustering combined with an L-term heuristic to determine the relevant number of clusters. It can easily be implemented and delivers a quick performance, even on very large, real-world datasets. We analyse the clustering procedure, making use of established quality criteria. Experiments show that our approach is robust against noise and able to discern different driving styles.
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Open AccessArticle
A Numerical Study on the Electrochemical Treatment of Chloride-Contaminated Reinforced Concrete
Modelling 2022, 3(3), 374-384; https://doi.org/10.3390/modelling3030024 - 22 Aug 2022
Cited by 1
Abstract
Electrochemical treatment, specified as electrochemical chloride extraction (ECE), is one of the common techniques developed for the rehabilitation of chloride-contaminated reinforced concrete. In practice, ECE is time-consuming; for instance, the treatment duration could last several weeks or even longer. In order to reduce
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Electrochemical treatment, specified as electrochemical chloride extraction (ECE), is one of the common techniques developed for the rehabilitation of chloride-contaminated reinforced concrete. In practice, ECE is time-consuming; for instance, the treatment duration could last several weeks or even longer. In order to reduce the laboratory work, this paper presents some results about a numerical study of the ECE. It is to solve a series of physical equations governing multiple ionic transport making use of a finite difference method. The effects of some critical factors are discussed in detail, such as the treatment duration, the current density and the cover thickness. In addition, for the sake of validation, the numerical results are also compared with those obtained from an experimental test.
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(This article belongs to the Section Modelling in Engineering Structures)
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Open AccessArticle
Revisiting the Common Practice of Sellars and Tegart’s Hyperbolic Sine Constitutive Model
Modelling 2022, 3(3), 359-373; https://doi.org/10.3390/modelling3030023 - 08 Aug 2022
Cited by 1
Abstract
The Sellars and Tegart’s hyperbolic sine constitutive model is widely practiced in describing stress–strain curves of metals in hot deformation processes. The acceptance of this phenomenological model is owed to its versatility (working for a wide range of stress values) and simplicity (being
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The Sellars and Tegart’s hyperbolic sine constitutive model is widely practiced in describing stress–strain curves of metals in hot deformation processes. The acceptance of this phenomenological model is owed to its versatility (working for a wide range of stress values) and simplicity (being only a function of strain, strain rate, and temperature). The common practices of this model are revisited in this work, with a few suggestions to improve its results. Moreover, it is discussed that, with the progress of data-driven models, the main reason for using the Sellars and Tegart’s model should be to identify reliable activation energies, and not the stress–strain curves. Furthermore, a piece of code (Hot Deformation Fitting Tool) has been created to automate the analysis of stress–strain curves with various models.
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(This article belongs to the Section Modelling in Engineering Structures)
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Open AccessArticle
Characterizing Computational Thinking in the Context of Model-Planning Activities
Modelling 2022, 3(3), 344-358; https://doi.org/10.3390/modelling3030022 - 02 Aug 2022
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Computational thinking (CT) is a critical skill needed for STEM professionals and educational interventions that emphasize CT are needed. In engineering, one potential pedagogical tool to build CT is modeling, an essential skill for engineering students where they apply their scientific knowledge to
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Computational thinking (CT) is a critical skill needed for STEM professionals and educational interventions that emphasize CT are needed. In engineering, one potential pedagogical tool to build CT is modeling, an essential skill for engineering students where they apply their scientific knowledge to real-world problems involving planning, building, evaluating, and reflecting on created systems to simulate the real world. However, in-depth studies of how modeling is done in the class in relation to CT are limited. We used a case study methodology to evaluate a model-planning activity in a final-year undergraduate engineering classroom to elicit CT practices in students as they planned their modeling approach. Thematic analysis was used on student artifacts to triangulate and identify diverse ways that students used CT practices. We find that model-planning activities are useful for students to practice many aspects of CT, such as abstraction, algorithmic thinking, and generalization. We report implications for instructors wanting to implement model-planning activities into their classrooms.
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Open AccessArticle
Classical Molecular Dynamics Simulations of Surface Modifications Triggered by a Femtosecond Laser Pulse
by
and
Modelling 2022, 3(3), 333-343; https://doi.org/10.3390/modelling3030021 - 29 Jul 2022
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This work is devoted to classical molecular dynamics simulations of surface modifications (craters) drilled by single femtosecond laser pulses in silicon and diamond, materials relevant for numerous industrial applications. We propose a methodology paving the way towards a significant decrease in the simulation
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This work is devoted to classical molecular dynamics simulations of surface modifications (craters) drilled by single femtosecond laser pulses in silicon and diamond, materials relevant for numerous industrial applications. We propose a methodology paving the way towards a significant decrease in the simulation computational costs, which could also enable a precise estimation of the craters’ size and shape.
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Open AccessArticle
High-Fidelity Digital Twin Data Models by Randomized Dynamic Mode Decomposition and Deep Learning with Applications in Fluid Dynamics
Modelling 2022, 3(3), 314-332; https://doi.org/10.3390/modelling3030020 - 21 Jul 2022
Abstract
The purpose of this paper is the identification of high-fidelity digital twin data models from numerical code outputs by non-intrusive techniques (i.e., not requiring Galerkin projection of the governing equations onto the reduced modes basis). In this paper the author defines the concept
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The purpose of this paper is the identification of high-fidelity digital twin data models from numerical code outputs by non-intrusive techniques (i.e., not requiring Galerkin projection of the governing equations onto the reduced modes basis). In this paper the author defines the concept of the digital twin data model (DTM) as a model of reduced complexity that has the main feature of mirroring the original process behavior. The significant advantage of a DTM is to reproduce the dynamics with high accuracy and reduced costs in CPU time and hardware for settings difficult to explore because of the complexity of the dynamics over time. This paper introduces a new framework for creating efficient digital twin data models by combining two state-of-the-art tools: randomized dynamic mode decomposition and deep learning artificial intelligence. It is shown that the outputs are consistent with the original source data with the advantage of reduced complexity. The DTMs are investigated in the numerical simulation of three shock wave phenomena with increasing complexity. The author performs a thorough assessment of the performance of the new digital twin data models in terms of numerical accuracy and computational efficiency.
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(This article belongs to the Special Issue Synthesis of Computational Mechanics and Machine Learning)
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Open AccessArticle
Comparison of the Effectiveness of Drag Reduction Devices on a Simplified Truck Model through Numerical Simulation
by
and
Modelling 2022, 3(3), 300-313; https://doi.org/10.3390/modelling3030019 - 08 Jul 2022
Abstract
The aerodynamic efficiency of trucks is very low because of their non-streamlined box shape, which is subject to practical constraints, leaving little room for improvement in terms of aerodynamic efficiency. Hence, other means of improving the aerodynamic efficiency of trucks are needed, and
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The aerodynamic efficiency of trucks is very low because of their non-streamlined box shape, which is subject to practical constraints, leaving little room for improvement in terms of aerodynamic efficiency. Hence, other means of improving the aerodynamic efficiency of trucks are needed, and one practical yet relatively simple method to reduce aerodynamic drag is deploying drag reduction devices on trucks. This paper describes a numerical study of flow over a simplified truck with drag reduction devices. The numerical approach employed was Reynolds-averaged Navier–Stokes (RANS). Four test cases with different drag reduction devices deployed around the tractor–trailer gap region were studied. The effectiveness of those drag reduction devices was assessed, and it was demonstrated that in all four cases, the aerodynamic drag was reduced compared with the baseline case without any drag reduction devices. The most effective device was case 4 (about 24% reduction), with a roof deflector, side extenders, and five cross-flow vortex trap devices (CVTDs). Flow field analysis was performed to shed light on drag reduction mechanisms, which confirmed our previous findings that the main reason for the drag reduction was the reduced pressure on the front face of the trailer, while the reduction in the turbulence level in the tractor–trailer gap region contributed much less to the overall drag reduction.
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(This article belongs to the Section Modelling in Engineering Structures)
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Open AccessArticle
A Framework for Interactive Development of Simulation Models with Strategical–Tactical–Operational Layering Applied to the Logistics of Bulk Commodities
by
and
Modelling 2022, 3(3), 272-299; https://doi.org/10.3390/modelling3030018 - 30 Jun 2022
Abstract
CONTEXT–Simulation modelling provides insight into hidden dynamics underlying business processes. However, an accurate understanding of operations is necessary for fidelity of the model. This is challenging because of the need to extract the tacit nature of operational knowledge and facilitate the representation of
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CONTEXT–Simulation modelling provides insight into hidden dynamics underlying business processes. However, an accurate understanding of operations is necessary for fidelity of the model. This is challenging because of the need to extract the tacit nature of operational knowledge and facilitate the representation of complex processes and decision-making patterns that do not depend on classes, objects, and instantiations. Commonly used industrial simulation, such as Arena®, does not natively support the object-oriented constructs available for software development. OBJECTIVE–This paper proposes a method for developing simulation models that allow process-owners and modellers to jointly build a series of evolutionary models that improve conceptual validity of the executable computer model. APPROACH-Software and Systems Engineering principles were adapted to develop a framework that allows a systematic transition from conceptual to executable model, which allows multiple perspectives to be simultaneously considered. The framework was applied to a logistics case study in a bulk commodities distribution context. FINDINGS–The method guided the development of a set of models that served as scaffolds to allow the natural flow of ideas from a natural language domain to Arena® code. In doing so, modeller and process-owners at strategic, tactical, and operational levels developed and validated the simulation model. ORIGINALITY—This work provides a framework for structuring the development of simulation models. The framework allows the use of non-object-oriented constructs, making it applicable to SIMAN-based simulation languages and packages as Arena®.
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(This article belongs to the Special Issue Model Driven Interoperability for System Engineering)
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Open AccessArticle
Modeling of a Three-Stage Cascaded Refrigeration System Based on Standard Refrigeration Compressors in Cryogenic Applications above 110 K
Modelling 2022, 3(2), 255-271; https://doi.org/10.3390/modelling3020017 - 17 Jun 2022
Cited by 2
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More and more applications, such as natural gas liquefaction, LNG reliquefaction, whole body cryotherapy and cryopreservation, require cooling in the temperature range from 110 to 150 K. This can be achieved in systems using standard refrigeration compressors, which are reliable and cost-effective, but
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More and more applications, such as natural gas liquefaction, LNG reliquefaction, whole body cryotherapy and cryopreservation, require cooling in the temperature range from 110 to 150 K. This can be achieved in systems using standard refrigeration compressors, which are reliable and cost-effective, but are subject to certain operating limits. This paper investigates the potential of a three-stage cascaded refrigeration system based on standard refrigeration compressors in this range of temperatures. The investigation takes into account the vital limitations of refrigeration compressors and aims to look for possible refrigerant configurations (taking into account PFCs, HFCs, HCs and HOs); performance limitations such as cooling power temperature and system COP; and the influences of system architecture (single-stage and two-stage compression). The paper investigates whether it is possible to design a three-stage cascaded refrigeration system using standard refrigeration compressors, and if so, at what cost? This investigation shows that the three-stage cascaded refrigeration system can reach the lowest temperature of 127 K with a COP of 0.179, which corresponds to a Carnot efficiency of 0.262. Moreover, systems based on natural refrigerants are found to be advantageous in terms of achieved temperatures compared to those that use synthetic refrigerants. Furthermore, only the application of R50 (methane) is shown to allow temperatures below 130 K to be achieved, and this is possible only in a two-stage compression cascade system. For most of the investigated configurations, the suction pressure must be below atmospheric pressure to thermally couple cascade stages.
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Open AccessArticle
Cost Optimization of Reinforced Concrete Section According to Flexural Cracking
Modelling 2022, 3(2), 243-254; https://doi.org/10.3390/modelling3020016 - 25 May 2022
Abstract
A series of distributed flexural cracks develop in reinforced concrete flexural elements under the working load. The control of cracking in reinforced concrete is an important issue that must be considered in the design of reinforced concrete structures. Crack width and spacing are
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A series of distributed flexural cracks develop in reinforced concrete flexural elements under the working load. The control of cracking in reinforced concrete is an important issue that must be considered in the design of reinforced concrete structures. Crack width and spacing are influenced by several factors, including the steel percentage, its distribution in the concrete cross-section, the concrete cover, and the concrete properties. In practice, however, a compromise must be made between cracking, durability, and ease of construction and cost. This study presents the optimal design of a reinforced concrete cross-section, using the optimization method of mixed-integer nonlinear programming (MINLP) and the Eurocode standard. The MINLP optimization model OPTCON was developed for this purpose. The model contains the objective function of the material cost considering the crack width requirements. The crack width requirements can be satisfied by direct calculation or by limiting the bar spacing. Due to the different crack width requirements, two different economic designs of reinforced concrete sections were proposed. The case study presented in this study demonstrates the value of the presented optimization approach. A direct comparison between different methods for modelling cracking in reinforced concrete cross-sections, which has not been done before, is also presented.
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(This article belongs to the Special Issue Simulation- and Modelling-Aided Structural Integrity and Safety)
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