@article{FaizollahzadehArdabiliNajafiAlizamiretal.,
  author    = {Faizollahzadeh Ardabili, Sina and Najafi, Bahman and Alizamir, Meysam and Mosavi, Amir and Shamshirband, Shahaboddin and Rabczuk, Timon},
  title     = {Using SVM-RSM and ELM-RSM Approaches for Optimizing the Production Process of Methyl and Ethyl Esters},
  series = {Energies},
  journal   = {Energies},
  number    = {11, 2889},
  publisher = {MDPI},
  address   = {Basel},
  doi       = {10.3390/en11112889},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20181025-38170},
  pages     = {1 -- 20},
  abstract  = {The production of a desired product needs an effective use of the experimental model. The present study proposes an extreme learning machine (ELM) and a support vector machine (SVM) integrated with the response surface methodology (RSM) to solve the complexity in optimization and prediction of the ethyl ester and methyl ester production process. The novel hybrid models of ELM-RSM and ELM-SVM are further used as a case study to estimate the yield of methyl and ethyl esters through a trans-esterification process from waste cooking oil (WCO) based on American Society for Testing and Materials (ASTM) standards. The results of the prediction phase were also compared with artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS), which were recently developed by the second author of this study. Based on the results, an ELM with a correlation coefficient of 0.9815 and 0.9863 for methyl and ethyl esters, respectively, had a high estimation capability compared with that for SVM, ANNs, and ANFIS. Accordingly, the maximum production yield was obtained in the case of using ELM-RSM of 96.86\% for ethyl ester at a temperature of 68.48 °C, a catalyst value of 1.15 wt. \%, mixing intensity of 650.07 rpm, and an alcohol to oil molar ratio (A/O) of 5.77; for methyl ester, the production yield was 98.46\% at a temperature of 67.62 °C, a catalyst value of 1.1 wt. \%, mixing intensity of 709.42 rpm, and an A/O of 6.09. Therefore, ELM-RSM increased the production yield by 3.6\% for ethyl ester and 3.1\% for methyl ester, compared with those for the experimental data.},
  subject      = {Biodiesel},
  language  = {en}
}
@article{ZhangHaoWangetal.,
  author    = {Zhang, Chao and Hao, Xiao-Li and Wang, Cuixia and Wei, Ning and Rabczuk, Timon},
  title     = {Thermal conductivity of graphene nanoribbons under shear deformation: A molecular dynamics simulation},
  series = {Scientific Reports},
  journal   = {Scientific Reports},
  doi       = {10.1038/srep41398},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170428-31718},
  abstract  = {Tensile strain and compress strain can greatly affect the thermal conductivity of graphene nanoribbons (GNRs). However, the effect of GNRs under shear strain, which is also one of the main strain effect, has not been studied systematically yet. In this work, we employ reverse nonequilibrium molecular dynamics (RNEMD) to the systematical study of the thermal conductivity of GNRs (with model size of 4 nm × 15 nm) under the shear strain. Our studies show that the thermal conductivity of GNRs is not sensitive to the shear strain, and the thermal conductivity decreases only 12-16\% before the pristine structure is broken. Furthermore, the phonon frequency and the change of the micro-structure of GNRs, such as band angel and bond length, are analyzed to explore the tendency of thermal conductivity. The results show that the main influence of shear strain is on the in-plane phonon density of states (PDOS), whose G band (higher frequency peaks) moved to the low frequency, thus the thermal conductivity is decreased. The unique thermal properties of GNRs under shear strains suggest their great potentials for graphene nanodevices and great potentials in the thermal managements and thermoelectric applications.},
  subject      = {W{\"a}rmeleitf{\"a}higkeit},
  language  = {en}
}
@article{RabczukGuoZhuangetal.,
  author    = {Rabczuk, Timon and Guo, Hongwei and Zhuang, Xiaoying and Chen, Pengwan and Alajlan, Naif},
  title     = {Stochastic deep collocation method based on neural architecture search and transfer learning for heterogeneous porous media},
  series = {Engineering with Computers},
  volume    = {2022},
  journal   = {Engineering with Computers},
  publisher = {Springer},
  address   = {London},
  doi       = {10.1007/s00366-021-01586-2},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20220209-45835},
  pages     = {1 -- 26},
  abstract  = {We present a stochastic deep collocation method (DCM) based on neural architecture search (NAS) and transfer learning for heterogeneous porous media. We first carry out a sensitivity analysis to determine the key hyper-parameters of the network to reduce the search space and subsequently employ hyper-parameter optimization to finally obtain the parameter values. The presented NAS based DCM also saves the weights and biases of the most favorable architectures, which is then used in the fine-tuning process. We also employ transfer learning techniques to drastically reduce the computational cost. The presented DCM is then applied to the stochastic analysis of heterogeneous porous material. Therefore, a three dimensional stochastic flow model is built providing a benchmark to the simulation of groundwater flow in highly heterogeneous aquifers. The performance of the presented NAS based DCM is verified in different dimensions using the method of manufactured solutions. We show that it significantly outperforms finite difference methods in both accuracy and computational cost.},
  subject      = {Maschinelles Lernen},
  language  = {en}
}
@article{BanihaniRabczukAlmomani,
  author    = {Banihani, Suleiman and Rabczuk, Timon and Almomani, Thakir},
  title     = {POD for real-time simulation of hyperelastic soft biological tissue using the point collocation method of finite spheres},
  series = {Mathematical Problems in Engineering},
  journal   = {Mathematical Problems in Engineering},
  doi       = {10.1155/2013/386501},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170413-31203},
  abstract  = {The point collocation method of finite spheres (PCMFS) is used to model the hyperelastic response of soft biological tissue in real time within the framework of virtual surgery simulation. The proper orthogonal decomposition (POD) model order reduction (MOR) technique was used to achieve reduced-order model of the problem, minimizing computational cost. The PCMFS is a physics-based meshfree numerical technique for real-time simulation of surgical procedures where the approximation functions are applied directly on the strong form of the boundary value problem without the need for integration, increasing computational efficiency. Since computational speed has a significant role in simulation of surgical procedures, the proposed technique was able to model realistic nonlinear behavior of organs in real time. Numerical results are shown to demonstrate the effectiveness of the new methodology through a comparison between full and reduced analyses for several nonlinear problems. It is shown that the proposed technique was able to achieve good agreement with the full model; moreover, the computational and data storage costs were significantly reduced.},
  subject      = {Chirurgie},
  language  = {en}
}
@article{ShiraziMohebbiAzadiKakavandetal.,
  author    = {Shirazi, A. H. N. and Mohebbi, Farzad and Azadi Kakavand, M. R. and He, B. and Rabczuk, Timon},
  title     = {Paraffin Nanocomposites for Heat Management of Lithium-Ion Batteries: A Computational Investigation},
  series = {JOURNAL OF NANOMATERIALS},
  journal   = {JOURNAL OF NANOMATERIALS},
  doi       = {10.1155/2016/2131946},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170411-31141},
  abstract  = {Lithium-ion (Li-ion) batteries are currently considered as vital components for advances in mobile technologies such as those in communications and transport. Nonetheless, Li-ion batteries suffer from temperature rises which sometimes lead to operational damages or may even cause fire. An appropriate solution to control the temperature changes during the operation of Li-ion batteries is to embed batteries inside a paraffin matrix to absorb and dissipate heat. In the present work, we aimed to investigate the possibility of making paraffin nanocomposites for better heat management of a Li-ion battery pack. To fulfill this aim, heat generation during a battery charging/discharging cycles was simulated using Newman's well established electrochemical pseudo-2D model. We couple this model to a 3D heat transfer model to predict the temperature evolution during the battery operation. In the later model, we considered different paraffin nanocomposites structures made by the addition of graphene, carbon nanotubes, and fullerene by assuming the same thermal conductivity for all fillers. This way, our results mainly correlate with the geometry of the fillers. Our results assess the degree of enhancement in heat dissipation of Li-ion batteries through the use of paraffin nanocomposites. Our results may be used as a guide for experimental set-ups to improve the heat management of Li-ion batteries.},
  subject      = {Batterie},
  language  = {en}
}
@article{JiangZhuangRabczuk,
  author    = {Jiang, Jin-Wu and Zhuang, Xiaoying and Rabczuk, Timon},
  title     = {Orientation dependent thermal conductance in single-layer MoS 2},
  series = {Scientific Reports},
  journal   = {Scientific Reports},
  doi       = {10.1038/srep02209},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170418-31417},
  abstract  = {We investigate the thermal conductivity in the armchair and zigzag MoS2 nanoribbons, by combining the non-equilibrium Green's function approach and the first-principles method. A strong orientation dependence is observed in the thermal conductivity. Particularly, the thermal conductivity for the armchair MoS2 nanoribbon is about 673.6 Wm-1 K-1 in the armchair nanoribbon, and 841.1 Wm-1 K-1 in the zigzag nanoribbon at room temperature. By calculating the Caroli transmission, we disclose the underlying mechanism for this strong orientation dependence to be the fewer phonon transport channels in the armchair MoS2 nanoribbon in the frequency range of [150, 200] cm-1. Through the scaling of the phonon dispersion, we further illustrate that the thermal conductivity calculated for the MoS2 nanoribbon is esentially in consistent with the superior thermal conductivity found for graphene.},
  subject      = {Mechanische Eigenschaft},
  language  = {en}
}
@article{RenZhuangOterkusetal.,
  author    = {Ren, Huilong and Zhuang, Xiaoying and Oterkus, Erkan and Zhu, Hehua and Rabczuk, Timon},
  title     = {Nonlocal strong forms of thin plate, gradient elasticity, magneto-electro-elasticity and phase-field fracture by nonlocal operator method},
  series = {Engineering with Computers},
  volume    = {2021},
  journal   = {Engineering with Computers},
  doi       = {10.1007/s00366-021-01502-8},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20211207-45388},
  pages     = {1 -- 22},
  abstract  = {The derivation of nonlocal strong forms for many physical problems remains cumbersome in traditional methods. In this paper, we apply the variational principle/weighted residual method based on nonlocal operator method for the derivation of nonlocal forms for elasticity, thin plate, gradient elasticity, electro-magneto-elasticity and phase-field fracture method. The nonlocal governing equations are expressed as an integral form on support and dual-support. The first example shows that the nonlocal elasticity has the same form as dual-horizon non-ordinary state-based peridynamics. The derivation is simple and general and it can convert efficiently many local physical models into their corresponding nonlocal forms. In addition, a criterion based on the instability of the nonlocal gradient is proposed for the fracture modelling in linear elasticity. Several numerical examples are presented to validate nonlocal elasticity and the nonlocal thin plate.},
  subject      = {Bruchmechanik},
  language  = {en}
}
@article{NooriMortazaviKeshtkarietal.,
  author    = {Noori, Hamidreza and Mortazavi, Bohayra and Keshtkari, Leila and Zhuang, Xiaoying and Rabczuk, Timon},
  title     = {Nanopore creation in MoS2 and graphene monolayers by nanoparticles impact: a reactive molecular dynamics study},
  series = {Applied Physics A},
  volume    = {2021},
  journal   = {Applied Physics A},
  number    = {volume 127, article 541},
  publisher = {Springer},
  address   = {Heidelberg},
  doi       = {10.1007/s00339-021-04693-5},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20210804-44756},
  pages     = {1 -- 13},
  abstract  = {In this work, extensive reactive molecular dynamics simulations are conducted to analyze the nanopore creation by nano-particles impact over single-layer molybdenum disulfide (MoS2) with 1T and 2H phases. We also compare the results with graphene monolayer. In our simulations, nanosheets are exposed to a spherical rigid carbon projectile with high initial velocities ranging from 2 to 23 km/s. Results for three different structures are compared to examine the most critical factors in the perforation and resistance force during the impact. To analyze the perforation and impact resistance, kinetic energy and displacement time history of the projectile as well as perforation resistance force of the projectile are investigated. Interestingly, although the elasticity module and tensile strength of the graphene are by almost five times higher than those of MoS2, the results demonstrate that 1T and 2H-MoS2 phases are more resistive to the impact loading and perforation than graphene. For the MoS2nanosheets, we realize that the 2H phase is more resistant to impact loading than the 1T counterpart. Our reactive molecular dynamics results highlight that in addition to the strength and toughness, atomic structure is another crucial factor that can contribute substantially to impact resistance of 2D materials. The obtained results can be useful to guide the experimental setups for the nanopore creation in MoS2or other 2D lattices.},
  subject      = {Nanomechanik},
  language  = {en}
}
@article{IlyaniAkmarKramerRabczuk,
  author    = {Ilyani Akmar, A.B. and Kramer, O. and Rabczuk, Timon},
  title     = {Multi-objective evolutionary optimization of sandwich structures: An evaluation by elitist non-dominated sorting evolution strategy},
  series = {American Journal of Engineering and Applied Sciences},
  journal   = {American Journal of Engineering and Applied Sciences},
  doi       = {10.3844/ajeassp.2015.185.201},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170418-31402},
  pages     = {185 -- 201},
  abstract  = {In this study, an application of evolutionary multi-objective optimization algorithms on the optimization of sandwich structures is presented. The solution strategy is known as Elitist Non-Dominated Sorting Evolution Strategy (ENSES) wherein Evolution Strategies (ES) as Evolutionary Algorithm (EA) in the elitist Non-dominated Sorting Genetic algorithm (NSGA-II) procedure. Evolutionary algorithm seems a compatible approach to resolve multi-objective optimization problems because it is inspired by natural evolution, which closely linked to Artificial Intelligence (AI) techniques and elitism has shown an important factor for improving evolutionary multi-objective search. In order to evaluate the notion of performance by ENSES, the well-known study case of sandwich structures are reconsidered. For Case 1, the goals of the multi-objective optimization are minimization of the deflection and the weight of the sandwich structures. The length, the core and skin thicknesses are the design variables of Case 1. For Case 2, the objective functions are the fabrication cost, the beam weight and the end deflection of the sandwich structures. There are four design variables i.e., the weld height, the weld length, the beam depth and the beam width in Case 2. Numerical results are presented in terms of Paretooptimal solutions for both evaluated cases.},
  subject      = {Optimierung},
  language  = {en}
}
@article{MortazaviPereiraJiangetal.,
  author    = {Mortazavi, Bohayra and Pereira, Luiz Felipe C. and Jiang, Jin-Wu and Rabczuk, Timon},
  title     = {Modelling heat conduction in polycrystalline hexagonal boron-nitride films},
  series = {Scientific Reports},
  journal   = {Scientific Reports},
  doi       = {10.1038/srep13228},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170425-31534},
  abstract  = {We conducted extensive molecular dynamics simulations to investigate the thermal conductivity of polycrystalline hexagonal boron-nitride (h-BN) films. To this aim, we constructed large atomistic models of polycrystalline h-BN sheets with random and uniform grain configuration. By performing equilibrium molecular dynamics (EMD) simulations, we investigated the influence of the average grain size on the thermal conductivity of polycrystalline h-BN films at various temperatures. Using the EMD results, we constructed finite element models of polycrystalline h-BN sheets to probe the thermal conductivity of samples with larger grain sizes. Our multiscale investigations not only provide a general viewpoint regarding the heat conduction in h-BN films but also propose that polycrystalline h-BN sheets present high thermal conductivity comparable to monocrystalline sheets.},
  subject      = {W{\"a}rmeleitf{\"a}higkeit},
  language  = {en}
}