Journal Description
Computation
Computation
is a peer-reviewed journal of computational science and engineering published monthly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, ESCI (Web of Science), CAPlus / SciFinder, Inspec, dblp, and other databases.
- Journal Rank: CiteScore - Q2 (Applied Mathematics)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 18 days after submission; acceptance to publication is undertaken in 4.4 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
2.2 (2022);
5-Year Impact Factor:
2.2 (2022)
Latest Articles
Accelerating Conjugate Heat Transfer Simulations in Squared Heated Cavities through Graphics Processing Unit (GPU) Computing
Computation 2024, 12(5), 106; https://doi.org/10.3390/computation12050106 (registering DOI) - 19 May 2024
Abstract
This research develops an innovative framework for accelerating Conjugate Heat Transfer (CHT) simulations within squared heated cavities through the application of Graphics Processing Units (GPUs). Although leveraging GPUs for computational speed improvements is well recognized, this study distinguishes itself by formulating a tailored
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This research develops an innovative framework for accelerating Conjugate Heat Transfer (CHT) simulations within squared heated cavities through the application of Graphics Processing Units (GPUs). Although leveraging GPUs for computational speed improvements is well recognized, this study distinguishes itself by formulating a tailored optimization strategy utilizing the CUDA-C programming language. This approach is specifically designed to tackle the inherent challenges of modeling squared cavity configurations in thermal simulations. Comparative performance evaluations reveal that our GPU-accelerated framework reduces computation times by up to 99.7% relative to traditional mono-core CPU processing. More importantly, it demonstrates an increase in accuracy in heat transfer predictions compared to existing CPU-based models. These results highlight not only the technical feasibility but also the substantial enhancements in simulation efficiency and accuracy, which are crucial for critical engineering applications such as aerospace component design, electronic device cooling, and energy system optimization. By advancing GPU computational techniques, this work contributes significantly to the field of thermal management, offering a potential for broader application and paving the way for more efficient, sustainable engineering solutions.
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(This article belongs to the Special Issue 10th Anniversary of Computation—Computational Heat and Mass Transfer (ICCHMT 2023))
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Open AccessArticle
Short Fiber-Reinforced Polymer Polyamide 6 Lugs and Selective Laser-Melted Ti-6Al-4V Bushing Contact Cohesive Zone Model Mode II Parameters’ Evaluation
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Andry Sedelnikov, Evgenii Kurkin, Vitaliy Smelov, Vladislava Chertykovtseva, Vyacheslav Alekseev, Andrey Gavrilov, Evgenii Kishov, Maksim Zvyagincev and Sergey Chernyakin
Computation 2024, 12(5), 105; https://doi.org/10.3390/computation12050105 - 17 May 2024
Abstract
This paper discusses an approach to estimating the parameters of the cohesive zone model (CZM) by mode II by extruding the bushing along the lug axis. This method of evaluation requires small samples, which is particularly relevant when investigating short fiber-reinforced polymers (SFRPs)
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This paper discusses an approach to estimating the parameters of the cohesive zone model (CZM) by mode II by extruding the bushing along the lug axis. This method of evaluation requires small samples, which is particularly relevant when investigating short fiber-reinforced polymers (SFRPs) with additively manufactured embedded elements. Adhesion is investigated on the example of 30% carbon fiber-reinforced polyamide-6 molded to Ti-6Al-4V (VT6) selective laser-melted (SLM) alloy bushing in cases of a roughness Ra = 2.66 μm (vibratory finishing), Ra = 8.79 μm (sandblasting), and Ra = 10.02 (directly from SLM). The values of the maximum equivalent tangential contact stress were in a range from 1.1 MPa to 9.5 MPa, while the critical fracture energy for tangential slip was estimated at 15 N/mm for all cases. Experimental validation of the obtained CZM mode II was carried out by evaluating the load-carrying capacity of the lugs with different bushings. In both the experiment and the calculation, greater bushing roughness provides greater lug load-bearing capacity. The ribbed bushings added significant strength in the experiments, which confirmed the importance of considering the tangential mode in the contact model. The presented models can be used for the preliminary evaluation of short fiber-reinforced polyamide-6 parts with titanium-embedded elements bearing capacity.
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(This article belongs to the Section Computational Engineering)
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Relation Models of Surface Parameters and Backscattering (or Radiation) Fields as a Tool for Solving Remote Sensing Problems
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Kseniia Nezhalska, Valerii Volosyuk, Kostiantyn Bilousov, Denys Kolesnikov and Glib Cherepnin
Computation 2024, 12(5), 104; https://doi.org/10.3390/computation12050104 - 16 May 2024
Abstract
In this paper, an analysis of existing models for describing surfaces of various types is performed, and the possibilities of their application at the level of mathematical modeling are analyzed. Moreover, due to the large number of models and the complexity of selecting
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In this paper, an analysis of existing models for describing surfaces of various types is performed, and the possibilities of their application at the level of mathematical modeling are analyzed. Moreover, due to the large number of models and the complexity of selecting the appropriate model, e.g., when conducting a practical experiment, an algorithm for choosing a specific model depending on the initial data is proposed. According to the algorithm, a software prototype that implements this algorithm (written in Python) is proposed.
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(This article belongs to the Special Issue Integrated Computer Technologies in Mechanical Engineering—Synergetic Engineering III)
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Open AccessArticle
On the Features of Numerical Simulation of Hydrogen Self-Ignition under High-Pressure Release
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Alexey Kiverin, Andrey Yarkov and Ivan Yakovenko
Computation 2024, 12(5), 103; https://doi.org/10.3390/computation12050103 - 16 May 2024
Abstract
The paper is devoted to the comparative analysis of different CFD techniques used to solve the problem of high-pressure hydrogen release into the air. Three variations of a contemporary low-dissipation numerical technique (CABARET) are compared with each other and a conventional first-order numerical
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The paper is devoted to the comparative analysis of different CFD techniques used to solve the problem of high-pressure hydrogen release into the air. Three variations of a contemporary low-dissipation numerical technique (CABARET) are compared with each other and a conventional first-order numerical scheme. It is shown that low dissipation of the numerical scheme defines better resolution of the contact surface between released hydrogen and ambient air. As a result, the spatial structures of the jet and the reaction wave that arise during self-ignition are better resolved, which is useful for predicting the local effects of high-pressure hydrogen release. At the same time, the dissipation has little effect on the induction delay, so critical conditions of self-ignition can be reliably reproduced even via conventional numerical schemes. The test problem setups formulated in the paper can be used as benchmarks for compressible CFD solvers.
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(This article belongs to the Special Issue Recent Advances in Numerical Simulation of Compressible Flows)
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Open AccessArticle
Design and Development of an Electronic Controller for Accurate Temperature Management for Storage of Biological and Chemical Samples in Healthcare
by
Svetozar Ilchev
Computation 2024, 12(5), 102; https://doi.org/10.3390/computation12050102 - 16 May 2024
Abstract
This paper presents the design and development of an electronic controller for accurate temperature management for the storage of biological and chemical samples in healthcare applications. In the introduction, some important application aspects related to the use of temperature control devices in healthcare
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This paper presents the design and development of an electronic controller for accurate temperature management for the storage of biological and chemical samples in healthcare applications. In the introduction, some important application aspects related to the use of temperature control devices in healthcare are discussed. Keeping these aspects in mind, a brief overview of some related works is presented. The findings are then translated to specific requirements for an electronic controller, which is to be used in a temperature control device. These requirements made necessary the development of a custom controller, as no readily available solutions could be obtained. The paper proceeds with the design of a suitable architecture and discusses some of the design choices. Then, some implementation details are presented and the prototype controller, together with its user interface, is illustrated. Experiments are conducted and several points for improvement are identified. Overall, the main task of keeping accurate, traceable temperature at all times is accomplished successfully, and the electronic controller proves to be a viable solution that conforms to the identified requirements. Future versions will improve the speed of the temperature adaptation and include better user interface and wireless connectivity for remote monitoring and control.
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(This article belongs to the Special Issue Applications of Statistics and Machine Learning in Electronics)
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Open AccessArticle
Unveiling AI-Generated Financial Text: A Computational Approach Using Natural Language Processing and Generative Artificial Intelligence
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Muhammad Asad Arshed, Ștefan Cristian Gherghina, Christine Dewi, Asma Iqbal and Shahzad Mumtaz
Computation 2024, 12(5), 101; https://doi.org/10.3390/computation12050101 - 15 May 2024
Abstract
This study is an in-depth exploration of the nascent field of Natural Language Processing (NLP) and generative Artificial Intelligence (AI), and it concentrates on the vital task of distinguishing between human-generated text and content that has been produced by AI models. Particularly, this
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This study is an in-depth exploration of the nascent field of Natural Language Processing (NLP) and generative Artificial Intelligence (AI), and it concentrates on the vital task of distinguishing between human-generated text and content that has been produced by AI models. Particularly, this research pioneers the identification of financial text derived from AI models such as ChatGPT and paraphrasing tools like QuillBot. While our primary focus is on financial content, we have also pinpointed texts generated by paragraph rewriting tools and utilized ChatGPT for various contexts this multiclass identification was missing in previous studies. In this paper, we use a comprehensive feature extraction methodology that combines TF–IDF with Word2Vec, along with individual feature extraction methods. Importantly, combining a Random Forest model with Word2Vec results in impressive outcomes. Moreover, this study investigates the significance of the window size parameters in the Word2Vec approach, revealing that a window size of one produces outstanding scores across various metrics, including accuracy, precision, recall and the F1 measure, all reaching a notable value of 0.74. In addition to this, our developed model performs well in classification, attaining AUC values of 0.94 for the ‘GPT’ class; 0.77 for the ‘Quil’ class; and 0.89 for the ‘Real’ class. We also achieved an accuracy of 0.72, precision of 0.71, recall of 0.72, and F1 of 0.71 for our extended prepared dataset. This study contributes significantly to the evolving landscape of AI text identification, providing valuable insights and promising directions for future research.
Full article
(This article belongs to the Special Issue Computational Approaches in Corporate Finance, Risk Management and Financial Markets)
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Open AccessArticle
Quasi-Interpolation on Chebyshev Grids with Boundary Corrections
by
Faisal Alsharif
Computation 2024, 12(5), 100; https://doi.org/10.3390/computation12050100 - 13 May 2024
Abstract
Quasi-interpolation is a powerful tool for approximating functions using radial basis functions (RBFs) such as Gaussian kernels. This avoids solving large systems of equations as in RBF interpolation. However, quasi-interpolation with Gaussian kernels on compact intervals can have significant errors near the boundaries.
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Quasi-interpolation is a powerful tool for approximating functions using radial basis functions (RBFs) such as Gaussian kernels. This avoids solving large systems of equations as in RBF interpolation. However, quasi-interpolation with Gaussian kernels on compact intervals can have significant errors near the boundaries. This paper proposes a quasi-interpolation method with Gaussian kernels using Chebyshev points and boundary corrections to improve the approximation near the boundaries. The boundary corrections use a linear approximation of the function beyond the interval to estimate the truncation error and add correction terms. Numerical studies on test functions show that the proposed method reduces errors significantly near boundaries compared to quasi-interpolation without corrections, for both equally spaced and Chebyshev points. The convergence and accuracy with the boundary corrections are generally better with Chebyshev points compared to equally spaced points. The proposed method provides an efficient way to perform quasi-interpolation on compact intervals while controlling the boundary errors. This study introduces a novel approach to quasi-interpolation modification, which significantly enhances convergence rates and minimizes errors at boundary points, thereby advancing the methods for boundary approximation.
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(This article belongs to the Topic Mathematical Modeling)
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Intraplatelet Calcium Signaling Regulates Thrombus Growth under Flow: Insights from a Multiscale Model
by
Anass Bouchnita and Vitaly Volpert
Computation 2024, 12(5), 99; https://doi.org/10.3390/computation12050099 - 12 May 2024
Abstract
In injured arteries, platelets adhere to the subendothelium and initiate the coagulation process. They recruit other platelets and form a plug that stops blood leakage. The formation of the platelet plug depends on platelet activation, a process that is regulated by intracellular calcium
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In injured arteries, platelets adhere to the subendothelium and initiate the coagulation process. They recruit other platelets and form a plug that stops blood leakage. The formation of the platelet plug depends on platelet activation, a process that is regulated by intracellular calcium signaling. Using an improved version of a previous multiscale model, we study the effects of changes in calcium signaling on thrombus growth. This model utilizes the immersed boundary method to capture the interplay between platelets and the flow. Each platelet can attach to other platelets, become activated, express proteins on its surface, detach, and/or become non-adhesive. Platelet activation is captured through a specific calcium signaling model that is solved at the intracellular level, which considers calcium activation by agonists and contacts. Simulations reveal a contact-dependent activation threshold necessary for the formation of the thrombus core. Next, we evaluate the effect of knocking out the P2Y and PAR receptor families. Further, we show that blocking P2Y receptors reduces platelet numbers in the shell while slightly increasing the core size. An analysis of the contribution of P2Y and PAR activation to intraplatelet calcium signaling reveals that each of the ADP and thrombin agonists promotes the activation of platelets in different regions of the thrombus. Finally, the model predicts that the heterogeneity in platelet size reduces the overall number of platelets recruited by the thrombus. The presented framework can be readily used to study the effect of antiplatelet therapy under different physiological and pathological blood flow, platelet count, and activation conditions.
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(This article belongs to the Special Issue 10th Anniversary of Computation—Computational Biology)
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An Optimization Model for Flight Rescheduling from an Airport’s Centralized Perspective for Better Management of Demand and Capacity Utilization
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Abbas Seifi, Kumaraswamy Ponnambalam, Anna Kudiakova and Lisa Aultman-Hall
Computation 2024, 12(5), 98; https://doi.org/10.3390/computation12050098 - 11 May 2024
Abstract
Over-capacity flight scheduling by commercial airlines due to the surging demand in recent years creates congestion and significant delays at major airports. This attitude towards maximizing throughput calls for tactical flight rescheduling to comply with airports’ capacity limitations and distribute the peak hour
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Over-capacity flight scheduling by commercial airlines due to the surging demand in recent years creates congestion and significant delays at major airports. This attitude towards maximizing throughput calls for tactical flight rescheduling to comply with airports’ capacity limitations and distribute the peak hour demand over the course of a day. Such displacements of flights may cause significant problems and costs for airlines and some cancellations or missed connections for passengers. This paper presents an optimization model for flight rescheduling at a schedule-coordinated airport to minimize congestion and flight delays at peak hours. The optimization model is used to make better scheduling intervention decisions considering airport resource constraints and safety of operation. A simulation algorithm is also developed to replicate arrival and departure processes in such an airport. The simulation adheres to a first come first served (FCFS) discipline and enforces runway capacity constraints and minimum turnaround times. We compare the delays caused by an ad hoc FCFS operation with those of the optimization model. Computational results from a case study demonstrate that a reduction of 52.6% and 61% in total delay times for arrival and departure flights, respectively, can be achieved. The optimization model also facilitates the implementation of a collaborative decision-making system for better coordination of airport traffic flow management with commercial airlines.
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(This article belongs to the Section Computational Engineering)
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Open AccessReview
Review of Modeling Approaches for Conjugate Heat Transfer Processes in Oil-Immersed Transformers
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Ivan Smolyanov, Evgeniy Shmakov, Denis Butusov and Alexandra I. Khalyasmaa
Computation 2024, 12(5), 97; https://doi.org/10.3390/computation12050097 - 11 May 2024
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This review addresses the modeling approaches for heat transfer processes in oil-immersed transformer. Electromagnetic, thermal, and hydrodynamic thermal fields are identified as the most critical aspects in describing the state of the transformer. The paper compares the implementation complexity, calculation time, and details
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This review addresses the modeling approaches for heat transfer processes in oil-immersed transformer. Electromagnetic, thermal, and hydrodynamic thermal fields are identified as the most critical aspects in describing the state of the transformer. The paper compares the implementation complexity, calculation time, and details of the results for different approaches to creating a mathematical model, such as circuit-based models and finite element and finite volume methods. Examples of successful model implementation are provided, along with the features of oil-immersed transformer modeling. In addition, the review considers the strengths and limitations of the considered models in relation to creating a digital twin of a transformer. The review concludes that it is not feasible to create a universal model that accounts for all the features of physical processes in an oil-immersed transformer, operates in real time for a digital twin, and provides the required accuracy at the same time. The conducted research shows that joint modeling of electromagnetic and thermal processes, reducing the dimensionality of models, provides the most comprehensive solution to the problem.
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Optimizing Hadoop Scheduling in Single-Board-Computer-Based Heterogeneous Clusters
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Basit Qureshi
Computation 2024, 12(5), 96; https://doi.org/10.3390/computation12050096 - 9 May 2024
Abstract
Single-board computers (SBCs) are emerging as an efficient and economical solution for fog and edge computing, providing localized big data processing with lower energy consumption. Newer and faster SBCs deliver improved performance while still maintaining a compact form factor and cost-effectiveness. In recent
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Single-board computers (SBCs) are emerging as an efficient and economical solution for fog and edge computing, providing localized big data processing with lower energy consumption. Newer and faster SBCs deliver improved performance while still maintaining a compact form factor and cost-effectiveness. In recent times, researchers have addressed scheduling issues in Hadoop-based SBC clusters. Despite their potential, traditional Hadoop configurations struggle to optimize performance in heterogeneous SBC clusters due to disparities in computing resources. Consequently, we propose modifications to the scheduling mechanism to address these challenges. In this paper, we leverage the use of node labels introduced in Hadoop 3+ and define a Frugality Index that categorizes and labels SBC nodes based on their physical capabilities, such as CPU, memory, disk space, etc. Next, an adaptive configuration policy modifies the native fair scheduling policy by dynamically adjusting resource allocation in response to workload and cluster conditions. Furthermore, the proposed frugal configuration policy considers prioritizing the reduced tasks based on the Frugality Index to maximize parallelism. To evaluate our proposal, we construct a 13-node SBC cluster and conduct empirical evaluation using the Hadoop CPU and IO intensive microbenchmarks. The results demonstrate significant performance improvements compared to native Hadoop FIFO and capacity schedulers, with execution times 56% and 22% faster than the best_cap and best_fifo scenarios. Our findings underscore the effectiveness of our approach in managing the heterogeneous nature of SBC clusters and optimizing performance across various hardware configurations.
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(This article belongs to the Section Computational Engineering)
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Analysis and Control of Partially Observed Discrete-Event Systems via Positively Constructed Formulas
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Artem Davydov, Aleksandr Larionov and Nadezhda Nagul
Computation 2024, 12(5), 95; https://doi.org/10.3390/computation12050095 - 9 May 2024
Abstract
This paper establishes a connection between control theory for partially observed discrete-event systems (DESs) and automated theorem proving (ATP) in the calculus of positively constructed formulas (PCFs). The language of PCFs is a complete first-order language providing a powerful tool for qualitative analysis
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This paper establishes a connection between control theory for partially observed discrete-event systems (DESs) and automated theorem proving (ATP) in the calculus of positively constructed formulas (PCFs). The language of PCFs is a complete first-order language providing a powerful tool for qualitative analysis of dynamical systems. Based on ATP in the PCF calculus, a new technique is suggested for checking observability as a property of formal languages, which is necessary for the existence of supervisory control of DESs. In the case of violation of observability, words causing a conflict can also be extracted with the help of a specially designed PCF. With an example of the problem of path planning by a robot in an unknown environment, we show the application of our approach at one of the levels of a robot control system. The prover Bootfrost developed to facilitate PCF refutation is also presented. The tests show positive results and perspectives for the presented approach.
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(This article belongs to the Special Issue Advanced Information, Computation, and Control Systems for Distributed Environments II)
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Open AccessArticle
To Bind or Not to Bind? A Comprehensive Characterization of TIR1 and Auxins Using Consensus In Silico Approaches
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Fernando D. Prieto-Martínez, Jennifer Mendoza-Cañas and Karina Martínez-Mayorga
Computation 2024, 12(5), 94; https://doi.org/10.3390/computation12050094 - 9 May 2024
Abstract
Auxins are chemical compounds of wide interest, mostly due to their role in plant metabolism and development. Synthetic auxins have been used as herbicides for more than 75 years and low toxicity in humans is one of their most advantageous features. Extensive studies
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Auxins are chemical compounds of wide interest, mostly due to their role in plant metabolism and development. Synthetic auxins have been used as herbicides for more than 75 years and low toxicity in humans is one of their most advantageous features. Extensive studies of natural and synthetic auxins have been made in an effort to understand their role in plant growth. However, molecular details of the binding and recognition process are still an open question. Herein, we present a comprehensive in silico pipeline for the assessment of TIR1 ligands using several structure-based methods. Our results suggest that subtle dynamics within the binding pocket arise from water–ligand interactions. We also show that this trait distinguishes effective binders. Finally, we construct a database of putative ligands and decoy compounds, which can aid further studies focusing on synthetic auxin design. To the best of our knowledge, this study is the first of its kind focusing on TIR1.
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(This article belongs to the Special Issue 10th Anniversary of Computation—Computational Chemistry)
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Elasto-Plastic Analysis of Two-Way Reinforced Concrete Slabs Strengthened with Carbon Fiber Reinforced Polymer Laminates
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Zahraa Saleem Sharhan and Majid Movahedi Rad
Computation 2024, 12(5), 93; https://doi.org/10.3390/computation12050093 - 8 May 2024
Abstract
This study explores a technique for enhancing the punching strength of reinforced concrete (RC) flat slabs, namely carbon fiber reinforced polymer (CFRP). Four large-scale RC flat slabs were fabricated, to assess the efficacy of this strengthening method. One slab served as a reference
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This study explores a technique for enhancing the punching strength of reinforced concrete (RC) flat slabs, namely carbon fiber reinforced polymer (CFRP). Four large-scale RC flat slabs were fabricated, to assess the efficacy of this strengthening method. One slab served as a reference and the three other specimens were strengthened with CFRP, as a method of external strengthening. These slabs, featuring identical overall dimensions and flexural steel reinforcement, underwent testing until failure, under the influence of concentrated patch loads. A concrete plastic damage constitutive model (CDP) was developed and employed to examine the strength of two-way RC slabs. Additionally, to enhance the strength of existing RC slabs, carbon fiber reinforced polymer (CFRP) strips are affixed to the tension surface of the sections. The research begins with the calibration of a numerical model, based on data from laboratory tests. The objective of this study is to constrain the plastic behavior of two-way RC slabs reinforced with CFRP, with a focus on establishing an optimal elasto-plastic analysis, aimed at controlling concrete damage plasticity using CFRP, and employing a plastic limit load multiplier. Subsequently, a series of numerical simulations, incorporating different variables, are conducted to investigate shear behavior. The numerical results indicate that an increase in the strengthening ratio has a significant impact on shear strength. Finite element simulations are carried out using Abaqus CAE®/2018.
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(This article belongs to the Section Computational Engineering)
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Numerical Estimation of Nonlinear Thermal Conductivity of SAE 1020 Steel
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Ariel Flores Monteiro de Oliveira, Elisan dos Santos Magalhães, Kahl Dick Zilnyk, Philippe Le Masson and Ernandes José Gonçalves do Nascimento
Computation 2024, 12(5), 92; https://doi.org/10.3390/computation12050092 - 4 May 2024
Abstract
Thermally characterizing high-thermal conductivity materials is challenging, especially considering high temperatures. However, the modeling of heat transfer processes requires specific material information. The present study addresses an inverse approach to estimate the thermal conductivity of SAE 1020 relative to temperature during an autogenous
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Thermally characterizing high-thermal conductivity materials is challenging, especially considering high temperatures. However, the modeling of heat transfer processes requires specific material information. The present study addresses an inverse approach to estimate the thermal conductivity of SAE 1020 relative to temperature during an autogenous LASER Beam Welding (LBW) experiment. The temperature profile during LBW is computed with the aid of an in-house CUDA-C algorithm. Here, the governing three-dimensional heat diffusion equation is discretized through the Finite Volume Method (FVM) and solved using the Successive Over-Relaxation (SOR) parallelized iterative solver. With temperature information, one may employ a minimization procedure to assess thermal properties or process parameters. In this work, the Quadrilateral Optimization Method (QOM) is applied to perform estimations because it allows for the simultaneous optimization of variables with no quantity restriction and renders the assessment of parameters in unsteady states valid, thereby preventing the requirement for steady-state experiments. We extended QOM’s prior applicability to account for more parameters concurrently. In Case I, the optimization of the three parameters that compose the second-degree polynomial function model of thermal conductivity is performed. In Case II, the heat distribution model’s gross heat rate (Ω) is also estimated in addition to the previous parameters. Ω [W] quantifies the power the sample receives and is related to the process’s efficiency. The method’s suitability for estimating the parameters was confirmed by investigating the reduced sensitivity coefficients, while the method’s stability was corroborated by performing the estimates with noisy data. There is a good agreement between the reference and estimated values. Hence, this study introduces a proper methodology for estimating a temperature-dependent thermal property and an LBW parameter. As the performance of the present algorithm is increased using parallel computation, a pondered solution between estimation reliability and computational cost is achieved.
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(This article belongs to the Special Issue 10th Anniversary of Computation—Computational Heat and Mass Transfer (ICCHMT 2023))
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Minimizing the Number of Distrustful Nodes on the Path of IP Packet Transmission
by
Kvitoslava Obelovska, Oleksandr Tkachuk and Yaromyr Snaichuk
Computation 2024, 12(5), 91; https://doi.org/10.3390/computation12050091 - 3 May 2024
Abstract
One of the important directions for improving modern Wide Area Networks is efficient and secure packet routing. Efficient routing is often based on using the shortest paths, while ensuring security involves preventing the possibility of packet interception. The work is devoted to improving
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One of the important directions for improving modern Wide Area Networks is efficient and secure packet routing. Efficient routing is often based on using the shortest paths, while ensuring security involves preventing the possibility of packet interception. The work is devoted to improving the security of data transmission in IP networks. A new approach is proposed to minimize the number of distrustful nodes on the path of IP packet transmission. By a distrustful node, we mean a node that works correctly in terms of hardware and software and fully implements its data transport functions, but from the point of view of its organizational subordination, we are not sure that the node will not violate security rules to prevent unauthorized access and interception of data. A distrustful node can be either a transit or an end node. To implement this approach, we modified Dijkstra’s shortest path tree construction algorithm. The modified algorithm ensures that we obtain a path that will pass only through trustful nodes, if such a path exists. If there is no such path, the path will have the minimum possible number of distrustful intermediate nodes. The number of intermediate nodes in the path was used as a metric to obtain the shortest path trees. Routing tables of routers, built on the basis of trees obtained using a modified algorithm, provide increased security of data transmission, minimizing the use of distrustful nodes.
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(This article belongs to the Special Issue 10th Anniversary of Computation—Computational Engineering)
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Selection of Appropriate Criteria for Optimization of Ventilation Element for Protective Clothing Using a Numerical Approach
by
Sanjay Rajni Vejanand, Alexander Janushevskis and Ivo Vaicis
Computation 2024, 12(5), 90; https://doi.org/10.3390/computation12050090 - 2 May 2024
Abstract
While there are multiple methods to ventilate protective clothing, there is still room for improvement. In our research, we are using ventilation elements that are positioned at the ventilation holes in the air space between the body and clothing. These ventilation elements allow
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While there are multiple methods to ventilate protective clothing, there is still room for improvement. In our research, we are using ventilation elements that are positioned at the ventilation holes in the air space between the body and clothing. These ventilation elements allow air to flow freely while preventing sun radiation, rain drops, and insects from directly accessing the body. Therefore, the shape of the ventilation element is crucial. This led us to study the shape optimization of ventilation elements through the utilization of metamodels and numerical approaches. In order to accomplish the objective, it is crucial to thoroughly evaluate and choose suitable criteria for the optimization process. We know from prior research that the toroidal cut-out shape element provides better results. In a previous study, we optimized the shape of this element based on the minimum pressure difference as a criterion. In this study, we are using different criteria for the shape optimization of ventilation elements to determine which are most effective. This study involves a metamodeling strategy that utilizes local and global approximations with different order polynomials, as well as Kriging approximations, for the purpose of optimizing the geometry of ventilation elements. The goal was achieved by a sequential process. (1) Planning the position of control points of Non-Uniform Rational B-Splines (NURBS) in order to generate elements with a smooth shape. (2) Constructing geometric CAD models based on the design of experiments. (3) Compute detailed model solutions using SolidWorks Flow Simulation. (4) Developing metamodels for responses using computer experiments. (5) Optimization of element shape using metamodels. The procedure is repeated for six criteria, and subsequently, the results are compared to determine the most efficient criteria for optimizing the design of the ventilation element.
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(This article belongs to the Section Computational Engineering)
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Analysis of a Novel Method for Generating 3D Mesh at Contact Points in Packed Beds
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Daniel F. Szambien, Maximilian R. Ziegler, Christoph Ulrich and Roland Scharf
Computation 2024, 12(5), 89; https://doi.org/10.3390/computation12050089 - 30 Apr 2024
Abstract
This study comprehensively analyzes the impact of the novel HybridBridge method, developed by the authors, for generating a 3D mesh at contact points within packed beds within the effective thermal conductivity. It compares HybridBridge with alternative methodologies, highlights its superiority and outlines potential
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This study comprehensively analyzes the impact of the novel HybridBridge method, developed by the authors, for generating a 3D mesh at contact points within packed beds within the effective thermal conductivity. It compares HybridBridge with alternative methodologies, highlights its superiority and outlines potential applications. The HybridBridge employs two independent geometry parameters to facilitate optimal flow mapping while maintaining physically accurate effective thermal conductivity and ensuring high mesh quality. A method is proposed to estimate the HybridBridge radius for a defined packed bed and cap height, enabling a presimulative determination of a suitable radius. Numerical analysis of a body-centered-cubic unit cell with varied HybridBridges is conducted alongside previous simulations involving a simple-cubic unit cell. Additionally, a physically based resistance model is introduced, delineating effective thermal conductivity as a function of the HybridBridge geometry and porosity. An equation for the HybridBridge radius, tailored to simulation parameters, is derived. Comparison with the unit cells and a randomly packed bed reveals an acceptable average deviation between the calculated and utilized radii, thereby streamlining and refining the implementation of the HybridBridge methodology.
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(This article belongs to the Special Issue 10th Anniversary of Computation—Computational Heat and Mass Transfer (ICCHMT 2023))
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Open AccessArticle
Torque Calculation and Dynamical Response in Halbach Array Coaxial Magnetic Gears through a Novel Analytical 2D Model
by
Panteleimon Tzouganakis, Vasilios Gakos, Christos Kalligeros, Christos Papalexis, Antonios Tsolakis and Vasilios Spitas
Computation 2024, 12(5), 88; https://doi.org/10.3390/computation12050088 - 27 Apr 2024
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Coaxial magnetic gears have piqued the interest of researchers due to their numerous benefits over mechanical gears. These include reduced noise and vibration, enhanced efficiency, lower maintenance costs, and improved backdrivability. However, their adoption in industry has been limited by drawbacks like lower
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Coaxial magnetic gears have piqued the interest of researchers due to their numerous benefits over mechanical gears. These include reduced noise and vibration, enhanced efficiency, lower maintenance costs, and improved backdrivability. However, their adoption in industry has been limited by drawbacks like lower torque density and slippage at high torque levels. This work presents an analytical 2D model to compute the magnetic potential in Halbach array coaxial magnetic gears for every rotational angle, geometry configuration, and magnet specifications. This model calculates the induced torques and torque ripple in both rotors using the Maxwell Stress Tensor. The results were confirmed through Finite Element Analysis (FEA). Unlike FEA, this analytical model directly produces harmonics values, leading to faster computational times as it avoids torque calculations at each time step. In a case study, a standard coaxial magnetic gear was compared to one with a Halbach array, revealing a 14.3% improvement in torque density and a minor reduction in harmonics that cause torque ripple. Additionally, a case study was conducted to examine slippage in both standard and Halbach array gears during transient operations. The Halbach array coaxial magnetic gear demonstrated a 13.5% lower transmission error than its standard counterpart.
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Open AccessArticle
BEM Modeling for Stress Sensitivity of Nonlocal Thermo-Elasto-Plastic Damage Problems
by
Mohamed Abdelsabour Fahmy
Computation 2024, 12(5), 87; https://doi.org/10.3390/computation12050087 - 23 Apr 2024
Abstract
The main objective of this paper is to propose a new boundary element method (BEM) modeling for stress sensitivity of nonlocal thermo-elasto-plastic damage problems. The numerical solution of the heat conduction equation subjected to a non-local condition is described using a boundary element
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The main objective of this paper is to propose a new boundary element method (BEM) modeling for stress sensitivity of nonlocal thermo-elasto-plastic damage problems. The numerical solution of the heat conduction equation subjected to a non-local condition is described using a boundary element model. The total amount of heat energy contained inside the solid under consideration is specified by the non-local condition. The procedure of solving the heat equation will reveal an unknown control function that governs the temperature on a specific region of the solid’s boundary. The initial stress BEM for structures with strain-softening damage is employed in a boundary element program with iterations in each load increment to develop a plasticity model with yield limit deterioration. To avoid the difficulties associated with the numerical calculation of singular integrals, the regularization technique is applicable to integral operators. To validate the physical correctness and efficiency of the suggested formulation, a numerical case is solved.
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(This article belongs to the Topic Advances in Computational Materials Sciences)
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