975 research outputs found
Stochastic neuro-swarming intelligence paradigm for the analysis of magneto-hydrodynamic Prandtl–Eyring fluid flow with diffusive magnetic layers effect over an elongated surface
No full textIn recent years, the integration of stochastic techniques, especially those based on artificial neural networks, has emerged as a pivotal advancement in the field of computational fluid dynamics. These techniques offer a powerful framework for the analysis of complex fluid flow phenomena and address the uncertainties inherent in fluid dynamics systems. Following this trend, the current investigation portrays the design and construction of an important technique named swarming optimized neuro-heuristic intelligence with the competency of artificial neural networks to analyze nonlinear viscoelastic magneto-hydrodynamic Prandtl–Eyring fluid flow model, with diffusive magnetic layers effect along an extended sheet. The currently designed computational technique is established using inverse multiquadric radial basis activation function through the hybridization of a well-known global searching technique of particle swarm optimization and sequential quadratic programming, a technique capable of rapid convergence locally. The most appropriate scaling group involved transformations that are implemented on governing equations of the suggested fluidic model to convert it from a system of nonlinear partial differential equations into a dimensionless form of a third-order nonlinear ordinary differential equation. The transformed/reduced fluid flow model is solved for sundry variations of physical quantities using the designed scheme and outcomes are matched consistently with Adam's numerical technique with negligible magnitude of absolute errors and mean square errors. Moreover, it is revealed that the velocity of the fluid depreciates in the presence of a strong magnetic field effect. The efficacy of the designed solver is depicted evidently through rigorous statistical observations via exhaustive numerical experimentation of the fluidic problem
The integration of environmental and social sustainability impacts of the biojet fuel product system within the life cycle assessment framework
No full textThe Master's programme Industrial Ecology is jointly organised by Leiden University and Delft University of Technology - Biojet fuel is developed as a potentially more sustainable alternative to existing petroleum based jet fuels. To establish the environmental and social sustainability of the biojet fuel product system, the full life cycle of the production should be analyzed. The environmental LCA (ELCA)and social LCA (SLCA) have been developed as two independent tools, but they cannot be used to analyze the same product system as their system boundaries differ. This research studies the possibility of harmonizing the two tools into a single social and environmental LCA (SELCA) methodology in light of its use in the biojet fuel product system. SELCA was developed through an extensive literature review, followed by catering it to the biojet fuel product system based on a survey and a dummy case study. The ELCA is based on unit processes while the SLCA uses organizations as its base. To reconcile these two system elements, the organizations were treated as multifunctional processes that can be allocated to the product system. The DPSIR model was used to ensure that data on interventions and economic flows were equivalent to each other and capable of being causally connected to the product system. The resulting methodology has consistent system boundaries and data for both social and environmental impacts. The majority of existing SLCA characterization methods and indicators are not compatible with SELCA. Indicators must be based on DPSIR pressure level data and be capable of being aggregated for the product system in order to be comparable to ELCA indicators. Many SLCA methodologies are based on statistical data which conceptually cannot be attributed to a particular organization or unit process. The only operational methodology is that of Hunkeler (2006) which uses quantitative labor hour data. As a methodology for assessing the biojet fuel, SELCA has several limits. The existing indicators do not address all issues considered important by academia and the industry. Also, despite that SELCA can in principle include the full biojet product system, in practice it will be limited by the lack of background databases. This results in more cut-off points and smaller system boundaries as shown in the dummy case study. However, with further research and development of characterization methods and databases, SELCA has the potential to fully integrate the environmental and social impact assessments of the biojet fuel product system.Technology, Policy and ManagementEngineering, Systems and ServicesIndustrial Ecolog
MHD slip flow through nanofluids for thermal energy storage in solar collectors using radiation and conductivity effects: A novel design sequential quadratic programming-based neuro-evolutionary approach
No full textIn this research, a novel design stochastic numerical technique is presented to investigate the unsteady form magnetohydrodynamic (MHD) slip flow along the boundary layer to analyze the transportation and heat transfer in a solar collector through nano liquids which is a revolution in the field of neurocomputing. Thermal conductivity in variable form is dependent on temperature and wall slips are assumed over the boundary. For mathematical modeling, the solar collector is assumed in the form of a nonlinear stretching sheet and a quite new artificial neural networks (ANNs) based approach is used to solve the current problem in which inverse multiquadric radial basis (IMRB) kernel is sandwiched between a global search solver named genetic algorithms (GAs) and a highly effective local solver named sequential quadratic programming (SQP) i.e. IMRB-GASQP solver. The governing boundary value problem is altered in the form of a system of nonlinear ordinary differential equations (ODEs) through the utilization of similarity transformation and then the obtained system of ODEs is solved using IMRB-GASQP solver by altering the values of distinguished parameters involved in it to observe the fluctuation in the velocity and temperature profiles of nanofluid. The obtained results are effectively compared with the reference solutions using the Adams numerical technique in graphical and tabulated form. An exhaustive error analysis using performance operators is presented while the efficacy of the designed solver using various statistical operators is also part of this research
Neuro-Heuristic Computational Intelligence Approach for Optimization of Electro-Magneto-Hydrodynamic Influence on a Nano Viscous Fluid Flow
No full textIn this investigative study, the electro-magneto hydrodynamic (EMHD) influence on a nano viscous fluid model is scrutinized by designing an artificial neural network (ANN) paradigm using a neuro-heuristic approach (NHA) through the combination of GAs (genetic algorithms) and one of the most efficient locally searching solver SQP (sequential quadratic programming), i.e., NHA-GA-SQP. The fluid flow for the proposed problem is initially interpreted in the form of PDEs and then utilization of suitable similarity transformation on these PDEs yields in terms of a stiff nonlinear system of ODEs. The numerical results of the suggested fluidic model based on the variation of its physically existing parameters are calculated through the NHA-GA-SQP solver to detect the variation in velocity, thermal gradient, and concentration during the fluid flow. A detailed analysis of obtained outcomes through the NHA-GA-SQP algorithm and their comparison with the reference results estimated via the Adams method are presented. The calculation of the proposed solver's accuracy, stability, and consistency through various statistical operators is also involved in the current inspection
Inverse multiquadric kernel-based neuro heuristic approach to analyze the unsteady MHD nanofluid flow via permeable elongating surface
No full textIn this study, a novel neuro heuristic approach is designed to investigate the flow properties of magnetohydrodynamic (MHD) nanofluid along an exponentially extending sheet with a permeable medium with the impact of radiation as well as fluctuating heat source/sink. The designed scheme to handle the suggested problem is established through the well-known biologically inspired neural networks (BINNs) by exploiting the inverse multiquadric kernel (IMQK), that is, BINNs-IMQK which is quite a new approach. The partial differential equations (PDEs) which govern the fluidic flow are reformed into a nonlinear system of ordinary differential equations (ODEs) using the most fitted similarity transformations rules and numerically solved by varying the parametric values including unsteady parameter, Brownian motion parameter, suction/injection parameter, radiation parameter, Schmidt number together with Prandtl number to visualize the velocity, thermal gradient, and mass transfer in the suggested fluid problem. It is noticed that nanofluid temperature hikes by uplifting the value of the Brownian motion parameter but this effect is reversed in case of unsteady parameter. The obtained numerical results are verified through reference solution using the well-known Adams method and the efficacy of the suggested solver is endorsed using a variety of statistical operators
Radial basis kernel harmony in neural networks for the analysis of MHD Williamson nanofluid flow with thermal radiation and chemical reaction: An evolutionary approach
No full textThe current investigative exploration exemplifies the conceptualization of a novel design intelligent computing paradigm based on artificial neural networks (ANNs) by utilizing radial basis function (RBF) to analyze magnetohydrodynamic (MHD) Williamson nanofluid two-dimensional flow along a stretchable sheet under the effect of chemical reaction as well as thermal radiation in a porous medium. This newly designed technique is an amalgam of a well-known reliable global solver named genetic algorithms (GAs) and a swift convergence generated local solver named sequential quadratic programming (SQP) used in ANNs by taking RBF as a kernel function i.e. ANNs-RBF-GASQP solver. The PDEs demonstrating the current nanofluid problem flow are transformed into the system of non-linear ODEs through a relevant similarity transformation and subsequently solved using ANNs-RBF-GASQP solver to investigate thermohydraulic properties by manipulating the values of various system parameters present in the ODEs. Moreover, the simulation results show that increasing the heat source parameter leads to a significant decrease in temperature. Additionally, an increase in the porosity parameter causes a decrease in the velocity of nanofluid, as a higher value of porosity increases fluid permeability and greater resistance to flow. The efficacy of the suggested solver is scrutinized through various statistical and convergence analyses
Intelligent computing paradigm for unsteady magneto nano-polymeric Casson nanofluid with Ohmic dissipation and thermal radiation
No full textIn this present investigative mode of study, a biological innovational approach is adopted in the form of an intelligent computing paradigm to investigate the properties of flow in the case of incompressible magneto nano-polymeric Casson nanofluid using a stochastic numerical technique named artificial neural networks based on the hybridization of genetic algorithms with highly efficient local search solvers which is sequential quadratic programming. The governing PDEs of the suggested fluid model are first converted into a system of ODEs using appropriate similarity transformations and then solved for sundry scenarios generated based on physical parameters existing in the ODEs to examine the velocity profile, thermal profile and nanofluid concentration. Furthermore, by uplifting the value of Casson parameter, the temperature of the nanofluid hikes however this effect is reversed in case of radiation parameter. The strong motivation behind this study is to obtain the numerical solution of a system of nonlinear differential equations involving fifth-order derivatives with strong accuracy. A comprehensive error analysis based on tables and graphs is presented to further enhance the scientific significance of this research in the results and discussion section
Culture of Tuva and its Investigators (S.I. Vainshtein)
No full textСтатья о творчестве профессора Севьяна Израйлевича Вайнштейна, который посвятил
полвека своей жизни изучению истории культуры Тувы. Дается обзор научной проблематики
исследований С.И. Вайнштейна, подчеркивается необходимость комплексного исследования
явлений народной культуры в тесной взаимосвязи всех составляющих его компонентов,
что требует особой квалификации ученых, обязанных обладать знаниями в смежных
областях науки.The article is devoted to the creative and scientific work of Sevyan Izrailevich Vainshtein who dedicated
more than fifty years of his life to the investigation of the history of Tuvan culture. Given in the article
is the survey of the problems studied by S.I. Vainshtein. The author emphasizes the necessity of an
integrated study of folk culture phenomena in a tight interrelation of all its components and parts,
which requires special qualifications of the scholars committed to have a large interdisciplinary
knowledge
Let's walk urban landscapes: New pathways in design research
No full textAccepted Author ManuscriptLandscape Architectur
Culture of Tuva and its Investigators (S.I. Vainshtein)
No full textСтатья о творчестве профессора Севьяна Израйлевича Вайнштейна, который посвятил
полвека своей жизни изучению истории культуры Тувы. Дается обзор научной проблематики
исследований С.И. Вайнштейна, подчеркивается необходимость комплексного исследования
явлений народной культуры в тесной взаимосвязи всех составляющих его компонентов,
что требует особой квалификации ученых, обязанных обладать знаниями в смежных
областях науки.The article is devoted to the creative and scientific work of Sevyan Izrailevich Vainshtein who dedicated
more than fifty years of his life to the investigation of the history of Tuvan culture. Given in the article
is the survey of the problems studied by S.I. Vainshtein. The author emphasizes the necessity of an
integrated study of folk culture phenomena in a tight interrelation of all its components and parts,
which requires special qualifications of the scholars committed to have a large interdisciplinary
knowledge
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