Computation最新文献

{"title":"Analytical and Numerical Investigation of Two-Dimensional Heat Transfer with Periodic Boundary Conditions","authors":"İ. Bağlan, Erman Aslan","doi":"10.3390/computation12010011","DOIUrl":"https://doi.org/10.3390/computation12010011","url":null,"abstract":"A two-dimensional heat diffusion problem with a heat source that is a quasilinear parabolic problem is examined analytically and numerically. Periodic boundary conditions are employed. As the problem is nonlinear, Picard’s successive approximation theorem is utilized. We demonstrate the existence, uniqueness, and constant dependence of the solution on the data using the generalized Fourier method under specific conditions of natural regularity and consistency imposed on the input data. For the numerical solution, an implicit finite difference scheme is used. The results obtained from the analytical and numerical solutions closely match each other.","PeriodicalId":52148,"journal":{"name":"Computation","volume":"90 9","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139440370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancement of Machine-Learning-Based Flash Calculations near Criticality Using a Resampling Approach","authors":"Eirini Maria Kanakaki, Anna Samnioti, V. Gaganis","doi":"10.3390/computation12010010","DOIUrl":"https://doi.org/10.3390/computation12010010","url":null,"abstract":"Flash calculations are essential in reservoir engineering applications, most notably in compositional flow simulation and separation processes, to provide phase distribution factors, known as k-values, at a given pressure and temperature. The calculation output is subsequently used to estimate composition-dependent properties of interest, such as the equilibrium phases’ molar fraction, composition, density, and compressibility. However, when the flash conditions approach criticality, minor inaccuracies in the computed k-values may lead to significant deviation in the dependent properties, which is eventually inherited to the simulator, leading to large errors in the simulation. Although several machine-learning-based regression approaches have emerged to drastically accelerate flash calculations, the criticality issue persists. To address this problem, a novel resampling technique of the ML models’ training data population is proposed, which aims to fine-tune the training dataset distribution and optimally exploit the models’ learning capacity across various flash conditions. The results demonstrate significantly improved accuracy in predicting phase behavior results near criticality, offering valuable contributions not only to the subsurface reservoir engineering industry but also to the broader field of thermodynamics. By understanding and optimizing the model’s training, this research enables more precise predictions and better-informed decision-making processes in domains involving phase separation phenomena. The proposed technique is applicable to every ML-dominated regression problem, where properties dependent on the machine output are of interest rather than the model output itself.","PeriodicalId":52148,"journal":{"name":"Computation","volume":"22 6","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139444292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corporate Bankruptcy Prediction Models: A Comparative Study for the Construction Sector in Greece","authors":"K. Toudas, S. Archontakis, P. Boufounou","doi":"10.3390/computation12010009","DOIUrl":"https://doi.org/10.3390/computation12010009","url":null,"abstract":"This study focuses on testing the efficiency of alternative bankruptcy prediction models (Altman, Ohlson, Zmijewski) and on assessing the possible reasons that led to the confirmation or not of the prevailing model. Data from financial statements of listed (Greek) construction companies before the economic crisis were utilized. The results showed that Altman’s main predictive model as well as the revised models have low overall predictability for all three years before bankruptcy.","PeriodicalId":52148,"journal":{"name":"Computation","volume":"119 4","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139444603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of Effectiveness of Combined Surface Treatment Methods for Structural Parts with Holes to Enhance Their Fatigue Life","authors":"Olexander Grebenikov, Andrii Humennyi, Serhii Svitlychnyi, Vasyl Lohinov, Valerii Matviienko","doi":"10.3390/computation12010008","DOIUrl":"https://doi.org/10.3390/computation12010008","url":null,"abstract":"The typical and most widespread stress concentrators in the lower wing panels of aircraft are the drain holes located on the stringer vertical ribs. These are prime sources for the initiation and development of fatigue cracks, which lead to early failure of the wing structure. Therefore, improving fatigue life in these critical areas is one of the significant issues for research. Two combined methods of surface plastic treatment in the location around drain holes are discussed in this paper. Using the finite element method and ANSYS software, we created a finite element model and obtained nonlinear solution results in the case of tension in a plate with three holes. In addition, the development of residual stress due to the surface plastic treatment of the hole-adjacent areas was taken into account. In this paper, it is shown that after surface treatment of the corresponding areas of the holes, residual stress, which exceeds the yield stress for the plate material, is induced. When combined with alternative tensile stress, these reduce the amplitude of the local stresses, thus increasing the number of stress cycles before failure. The benefits of this technology were confirmed by fatigue test results, which include the fatigue failure types of the plates. Graphs showing the impact of applicable surface treatment combined methods on the number of cycles to failure were also plotted.","PeriodicalId":52148,"journal":{"name":"Computation","volume":"28 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139447598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Thermal Analysis and Cooling Strategies of High-Efficiency Three-Phase Squirrel-Cage Induction Motors—A Review","authors":"Yashwanth Reddy Konda, Vamsi Krishna Ponnaganti, Peram Venkata Sivarami Reddy, R. R. Singh, Paolo Mercorelli, Edison Gundabattini, D. Solomon","doi":"10.3390/computation12010006","DOIUrl":"https://doi.org/10.3390/computation12010006","url":null,"abstract":"In recent times, there has been an increased demand for electric vehicles. In this context, the energy management of the electric motor, which are an important constituent of electric vehicles, plays a pivotal role. A lot of research has been conducted on the optimization of heat flow through electric motors, thus reducing the wastage of energy via heat. Futuristic power sources may increasingly rely on cutting-edge innovations like energy harvesting and self-powered induction motors. In this context, effective thermal management techniques are discussed in this paper. Importance was given to the potential energy losses, hotspots, the influence of overheating on the motor efficiency, different cooling strategies, certain experimental approaches, and power control techniques. Two types of thermal analysis computation methods, namely the lumped-parameter circuit method (LPCM) and the finite element method (FEM), are discussed. Also, this paper reviews different cooling strategies. The experimental research showed that the efficiency was greater by 11% with the copper rotor compared to the aluminum rotor. Each rotor type was reviewed based on the temperature rise and efficiency at higher temperatures. The water-cooling method reduced the working temperatures by 39.49% at the end windings, 41.67% at the side windings, and by a huge margin of 56.95% at the yoke of the induction motor compared to the air-cooling method; hence, the water-cooling method is better. Lastly, modern cooling strategies are proposed to provide an effective thermal management solution for squirrel-cage induction motors.","PeriodicalId":52148,"journal":{"name":"Computation","volume":"49 5","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139385864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A New Mixed Fractional Derivative with Applications in Computational Biology","authors":"K. Hattaf","doi":"10.3390/computation12010007","DOIUrl":"https://doi.org/10.3390/computation12010007","url":null,"abstract":"This study develops a new definition of a fractional derivative that mixes the definitions of fractional derivatives with singular and non-singular kernels. This developed definition encompasses many types of fractional derivatives, such as the Riemann–Liouville and Caputo fractional derivatives for singular kernel types, as well as the Caputo–Fabrizio, the Atangana–Baleanu, and the generalized Hattaf fractional derivatives for non-singular kernel types. The associate fractional integral of the new mixed fractional derivative is rigorously introduced. Furthermore, a novel numerical scheme is developed to approximate the solutions of a class of fractional differential equations (FDEs) involving the mixed fractional derivative. Finally, an application in computational biology is presented.","PeriodicalId":52148,"journal":{"name":"Computation","volume":"64 2","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139385540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implicit and Explicit Solvent Effects on the Global Reactivity and the Density Topological Parameters of the Preferred Conformers of Caespitate","authors":"Andrea Moreno-Ceballos, Maria Eugenia Castro, Norma A Caballero, Liliana Mammino, Francisco J. Melendez","doi":"10.3390/computation12010005","DOIUrl":"https://doi.org/10.3390/computation12010005","url":null,"abstract":"In the search to cover the urgent need to combat infectious diseases, natural products have gained attention in recent years. The caespitate molecule, isolated from the plant Helichrysum caespititium of the Asteraceae family, is used in traditional African medicine. Caespitate is an acylphloroglucinol with biological activity. Acylphloroglucinols have attracted attention for treating tuberculosis due to their structural characteristics, highlighting the stabilizing effect of their intramolecular hydrogen bonds (IHBs). In this work, a conformational search for the caespitate was performed using the MM method. Posteriorly, DFT calculations with the APFD functional were used for full optimization and vibrational frequencies, obtaining stable structures. A population analysis was performed to predict the distribution of the most probable conformers. The calculations were performed in the gas phase and solution using the implicit SMD model for water, chloroform, acetonitrile, and DMSO solvents. Additionally, the multiscale ONIOM QM1/QM2 model was used to simulate the explicit solvent. The implicit and explicit solvent effects were evaluated on the global reactivity indexes using the conceptual-DFT approach. In addition, the QTAIM approach was applied to analyze the properties of the IHBs of the most energetically and populated conformers. The obtained results indicated that the most stable and populated conformer is in the gas phase, and chloroform has an extended conformation. However, water, acetonitrile, and DMSO have a hairpin shape. The optimized structures are well preserved in explicit solvent and the interaction energies for the IHBs were lower in explicit than implicit solvents due to non-covalent interactions formed between the solvent molecules. Finally, both methodologies, with implicit and explicit solvents, were validated with 1H and 13C NMR experimental data. In both cases, the results agreed with the experimental data reported in the CDCl3 solvent.","PeriodicalId":52148,"journal":{"name":"Computation","volume":"19 2","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139388531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"LSTM Reconstruction of Turbulent Pressure Fluctuation Signals","authors":"Konstantinos Poulinakis, Dimitris Drikakis, I. Kokkinakis, S. Spottswood, T. Dbouk","doi":"10.3390/computation12010004","DOIUrl":"https://doi.org/10.3390/computation12010004","url":null,"abstract":"This paper concerns the application of a long short-term memory model (LSTM) for high-resolution reconstruction of turbulent pressure fluctuation signals from sparse (reduced) data. The model’s training was performed using data from high-resolution computational fluid dynamics (CFD) simulations of high-speed turbulent boundary layers over a flat panel. During the preprocessing stage, we employed cubic spline functions to increase the fidelity of the sparse signals and subsequently fed them to the LSTM model for a precise reconstruction. We evaluated our reconstruction method with the root mean squared error (RMSE) metric and via inspection of power spectrum plots. Our study reveals that the model achieved a precise high-resolution reconstruction of the training signal and could be transferred to new unseen signals of a similar nature with extremely high success. The numerical simulations show promising results for complex turbulent signals, which may be experimentally or computationally produced.","PeriodicalId":52148,"journal":{"name":"Computation","volume":"137 28","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139128292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design of Inhibitors That Target the Menin-Mixed-Lineage Leukemia Interaction.","authors":"Moses N Arthur, Kristeen Bebla, Emmanuel Broni, Carolyn Ashley, Miriam Velazquez, Xianin Hua, Ravi Radhakrishnan, Samuel K Kwofie, Whelton A Miller","doi":"10.3390/computation12010003","DOIUrl":"https://doi.org/10.3390/computation12010003","url":null,"abstract":"<p><p>The prognosis of mixed-lineage leukemia (MLL) has remained a significant health concern, especially for infants. The minimal treatments available for this aggressive type of leukemia has been an ongoing problem. Chromosomal translocations of the KMT2A gene are known as MLL, which expresses MLL fusion proteins. A protein called menin is an important oncogenic cofactor for these MLL fusion proteins, thus providing a new avenue for treatments against this subset of acute leukemias. In this study, we report results using the structure-based drug design (SBDD) approach to discover potential novel MLL-mediated leukemia inhibitors from natural products against menin. The three-dimensional (3D) protein model was derived from Protein Databank (Protein ID: 4GQ4), and EasyModeller 4.0 and I-TASSER were used to fix missing residues during rebuilding. Out of the ten protein models generated (five from EasyModeller and I-TASSER each), one model was selected. The selected model demonstrated the most reasonable quality and had 75.5% of residues in the most favored regions, 18.3% of residues in additionally allowed regions, 3.3% of residues in generously allowed regions, and 2.9% of residues in disallowed regions. A ligand library containing 25,131 ligands from a Chinese database was virtually screened using AutoDock Vina, in addition to three known menin inhibitors. The top 10 compounds including ZINC000103526876, ZINC000095913861, ZINC000095912705, ZINC000085530497, ZINC000095912718, ZINC000070451048, ZINC000085530488, ZINC000095912706, ZINC000103580868, and ZINC000103584057 had binding energies of -11.0, -10.7, -10.6, -10.2, -10.2, -9.9, -9.9, -9.9, -9.9, and -9.9 kcal/mol, respectively. To confirm the stability of the menin-ligand complexes and the binding mechanisms, molecular dynamics simulations including molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) computations were performed. The amino acid residues that were found to be potentially crucial in ligand binding included Phe243, Met283, Cys246, Tyr281, Ala247, Ser160, Asn287, Asp185, Ser183, Tyr328, Asn249, His186, Leu182, Ile248, and Pro250. MI-2-2 and PubChem CIDs 71777742 and 36294 were shown to possess anti-menin properties; thus, this justifies a need to experimentally determine the activity of the identified compounds. The compounds identified herein were found to have good pharmacological profiles and had negligible toxicity. Additionally, these compounds were predicted as antileukemic, antineoplastic, chemopreventive, and apoptotic agents. The 10 natural compounds can be further explored as potential novel agents for the effective treatment of MLL-mediated leukemia.</p>","PeriodicalId":52148,"journal":{"name":"Computation","volume":"12 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11209892/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141472441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MSVR & Operator-Based System Design of Intelligent MIMO Sensorless Control for Microreactor Devices","authors":"Tatsuma Kato, Kosuke Nishizawa, Mingcong Deng","doi":"10.3390/computation12010002","DOIUrl":"https://doi.org/10.3390/computation12010002","url":null,"abstract":"Recently, microreactors, which are tubular reactors capable of fast and highly efficient chemical reactions, have attracted attention. However, precise temperature control is required because temperature changes due to reaction heat can cause reactions to proceed differently from those designed. In a previous study, a single-input/output nonlinear control system was proposed using a model in which the microreactor is divided into three regions and the thermal equation is formulated considering the temperature gradient, but it could not control two different temperatures. In this paper, a multi-input, multi-output nonlinear control system was designed using operator theory. On the other hand, when the number of parallel microreactors is increased, a sensorless control method using M–SVR with a generalized Gaussian kernel was incorporated into the MIMO nonlinear control system from the viewpoint of cost reduction, and the effectiveness of the proposed method was confirmed via experimental results.","PeriodicalId":52148,"journal":{"name":"Computation","volume":"19 6","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139158657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}