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The system is driven by four excitations: two external excitations (aerodynamics torque and force) and two internal excitations (two mesh stiffness fluctuations). In this work, we develop a dynamic model with lumped components and 28 Dofs. We use the Runge Kutta step-by-step time integration numerical algorithm to solve the equations of motion obtained by Lagrange formalism. The numerical results have allowed us to identify the sources of vibration in the wind turbine. Also, they are useful to help the designer to make the right design and correctly choose the times for maintenance.",{"EN":187},"Nonlinear dynamic behavior of mechanical torque-limiter coupled with two stage helical gear",{"VOID":189},"[]",{"VOID":191},"Patel MR (2006) Wind and solar power systems design, analysis and operation. Press Taylor & Francis Group, Second Edition, U.S. Merchant Marine Academy Kings Point, New York\nTempel JVD, Molenaar DP (2002) Wind turbine structural dynamics. A review of the principles for modern power generation. Onshore Offshore Wind Eng 26:211–220\nGabriele M, Hansen AD, Hartkopf T (2008) Variable speed wind turbines: modeling, control and impact on power systems. In: European wind energy conference and exhibition, Brussels\nGuerine A, El Hami A, Walha L, Fakhfakh T, Haddar M (2017) Dynamic response of wind turbine gear system with uncertain-but-bounded parameters using interval analysis method. Renew Energy 113:679–687\nDodson L, Busawon K, Jovanovic M (2005) Estimation of the power coefficient in a wind conversion system. In: 44th IEEE conference on decision and control, and the European control conference, Spain\nGuerine A, El Hami A, Walha L, Fakhfakh T, Haddar M (2016) A polynomial chaos method for the analysis of the dynamic behavior of uncertain gear friction system. Eur J Mechan: A\u002FSolids 59:76–84\nLanzafame R, Messina (2009) Design and performance of a double-pitch wind turbine with non-twisted blades. Renew Energy 34:1413–1420\nAbboudi K, Walha L, Driss Y, Maatar M, Haddar M (2011) Dynamic behavior of the two stage spur gear system with fixed speed turbine excitation. Mech Mach Theory 46:1888–1900\nRamakrishnan V, Srivatsa SK (2007) Mathematical modeling of wind energy systems. Asian J Inform Technol 6:1160–1166\nMolina MG, Mercado PE (2011) Modelling and control design of pitch-controlled variable speed wind turbines. Wind turbines, pp 373–402\nHuang K, Yi Y, Xiong Y, Cheng Z, Chen H (2020) Nonlinear dynamics analysis of high contact ratio gears system with multiple clearances. J Braz Soc Mech Sci Eng 42:98\nWalha L, Driss Y, Khabou MT, Fakhfakh T, Haddar M (2011) Effects of eccentricity defect on the nonlinear dynamic behavior of the mechanism clutch-helical two stage gear. Mech Mach Theory 46(7):986–997\nWalha L, Driss Y, Fakhfakh T, Haddar M (2009) Effect of manufacturing defects on the dynamic behaviour for an helical two-stage gear system. Méc Ind 10(5):365–376\nXinhao T (2004) Dynamic simulation for system response of gearbox including localized gear faults. Thesis of university of Alberta, Canada\nWalha L (2008) Contribution à la dynamique non linéaire des réducteurs à engrenages. Thesis of university of Sfax, Tunisia\nLiu J, Tang C, Wu H, Xu Z, Wang L (2019) An analytical calculation method of the load distribution and stiffness of an angular contact ball bearing. Mech Mach Theory 142:103597\nLiu J, Xu Y, Pan G (2021) A combined acoustic and dynamic model of a defective ball bearing. J Sound Vib 501:116029\nManyonge AW, Ochieng RM, Onyango FN, Shichikha JM (2012) Mathematical modelling of wind turbine in a wind energy conversion system: power coefficient analysis. Appl Math Sci 6:4527–4536\nAsress MB, Aleksanda S, Dragan K, Slobodan S (2013) Numerical and analytical investigation of vertical axis wind turbine. 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The nonlinear ODE of system is obtained by using Galerkin method. To solve the nonlinear ODE, harmonic balance method (HBM) is used. Moreover, validation of results and analysis-verification are considered based on the numerical fourth-order Runge–Kutta method. Forced vibration in this research is distributed excitation. Therefore, new analysis is achieved in the field of jump and bifurcation phenomena for geometrical nonlinear cantilever beams. Using HBM led us to accomplish valuable and accurate research regarding bifurcation. Finally, the achieved results are demonstrated suitable and valuable not only regarding agreement of the precise results, but also studying many significant phenomena such as jump, bifurcation and beat in this field.",{"EN":316},"Analysis on jump and bifurcation phenomena in the forced vibration of nonlinear cantilever beam using HBM",{"VOID":318},"[\"16391274718052335200\"]",{"VOID":320},"Arafat HN (1999) Nonlinear response of cantilever beams. Ph.D. thesis, Virginia Polytechnic Institute and State University. Blacksburg. Virginia\nde Oliveira FM, Greco M (2014) Nonlinear dynamic analysis of beams with layered cross sections under moving masses. J Braz Soc Mech Sci Eng :1–12\nMalatkar P (2003) Nonlinear vibrations of cantilever beams and plates. Ph.D. thesis, Virginia Polytechnic Institute and State University. Blacksburg. Virginia\nCrespo da Silva M, Glynn C (1978) Nonlinear flexural-flexural-torsional dynamics of inextensional beams. II. Forced motions. J Struct Mech 6(4):449–461\nMalatkar P, Nayfeh AH (2003) On the transfer of energy between widely spaced modes in structures. Nonlinear Dyn 31(2):225–242\nDelgado-Velázquez I (2007) Nonlinear vibration of a cantilever beam\nStoykov S, Ribeiro P (2010) Nonlinear forced vibrations and static deformations of 3D beams with rectangular cross section: the influence of warping, shear deformation and longitudinal displacements. Int J Mech Sci 52(11):1505–1521\nLaxalde D, Thouverez F, Sinou J-J, Lombard J-P (2007) Qualitative analysis of forced response of blisks with friction ring dampers. Eur J Mech-A\u002FSolids 26(4):676–687\nMickens RE (2010) Truly nonlinear oscillations: harmonic balance, parameter expansions, iteration, and averaging methods. World Scientific\nNayfeh AH, Mook DT (1995) Nonlinear oscillations. Wiley, New York\nRibeiro P, Petyt M (1999) Geometrical non-linear, steady state, forced, periodic vibration of plates, part I: model and convergence studies. J Sound Vib 226(5):955–983\nSalles Lc, Blanc L, Thouverez F, Gouskov AM, Jean P Dynamic analysis of a bladed disk with friction and fretting-wear in blade attachments. In: ASME Turbo Expo 2009: Power for Land, Sea, and Air, 2009. American Society of Mechanical Engineers, pp 465–476\nKrylov N, Bogoliubov N (1947) Introduction to nonlinear mechanics. Acad. Sci. Ukr. SSR (1937). English translation. Princeton University Press, Princeton\nHu H, Tang J (2006) Solution of a Duffing-harmonic oscillator by the method of harmonic balance. J Sound Vib 294(3):637–639\nBrennan M, Kovacic I, Carrella A, Waters T (2008) On the jump-up and jump-down frequencies of the Duffing oscillator. J Sound Vib 318(4):1250–1261\nJacques N, Daya E, Potier-Ferry M (2010) Nonlinear vibration of viscoelastic sandwich beams by the harmonic balance and finite element methods. J Sound Vib 329(20):4251–4265\nGrolet A, Thouverez F (2013) Vibration of mechanical systems with geometric nonlinearities: solving Harmonic Balance Equations with Groebner basis and continuations methods. In: Proceedings of the Colloquium Calcul des structures et Modélisation CSMA. Giens\nZ-y Zhang, Y-s Chen (2014) Harmonic balance method with alternating frequency\u002Ftime domain technique for nonlinear dynamical system with fractional exponential. Appl Math Mech 35:423–436\nSouayeh S, Kacem N (2014) Computational models for large amplitude nonlinear vibrations of electrostatically actuated carbon nanotube-based mass sensors. Sens Actuators A 208:10–20\nClaeys M, Sinou J-J, Lambelin J-P, Alcoverro B (2014) Multi-harmonic measurements and numerical simulations of nonlinear vibrations of a beam with non-ideal boundary conditions. Commun Nonlinear Sci Numer Simul 19(12):4196–4212\nSzekrényes A (2015) A special case of parametrically excited systems: Free vibration of delaminated composite beams. Eur J Mechics-A\u002FSolids 49:82–105\nSun Y, Yu Y, Liu B (2015) Closed form solutions for predicting static and dynamic buckling behaviors of a drillstring in a horizontal well. Eur JMechanics-A\u002FSolids 49:362–372\nCrespo da Silva M, Glynn C (1978) Nonlinear flexural-flexural-torsional dynamics of inextensional beams I Equations of motion. J Struct Mechn 6(4):437–448\nRao SS, Yap FF (1995) Mechanical vibrations, vol 4. Addison-Wesley, New York\nBarari A, Kaliji H, Ghadimi M, Domairry G (2011) Non-linear vibration of Euler-Bernoulli beams. Lat Amour Solids Struct 8(2):139–148\nBelhaq M, Bichri A, Der Hogapian J, Mahfoud J (2011) Effect of electromagnetic actuations on the dynamics of a harmonically excited cantilever beam. Int J Non-Linear Mech 46(6):828–833\nShiki SB, Lopes V Jr, da Silva S (2014) Identification of nonlinear structures using discrete-time Volterra series. J Braz Soc Mech Eng 36(3):523–532\nYaman M (2009) Direct and parametric excitation of a nonlinear cantilever beam of varying orientation with time-delay state feedback. J Sound Vib 324(3):892–902\nZhang W (2005) Chaotic motion and its control for nonlinear nonplanar oscillations of a parametrically excited cantilever beam. 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As a result, this dimensionless number is key to parametrize emulsion flooding for EOR purposes. In this work, we incorporate capillary number effects that influence two well-known oil recovery mechanisms observed in continuous emulsion flooding, namely a microscopic increased pore-level efficiency, and a macroscopic mobility control or flood conformance. These mechanisms can be advantageously exploited in a newly proposed process denominated water-alternated-emulsion (WAE) injection, which is the focus of this article. To this end, a capillary number dependence was added to our initial model [17]. The resulted parametrization of relative permeability curves as functions of the capillary number was implemented in a Matlab open-source code. A parametric analysis of a 1\u002F4 five-spot geometry used on the first layer of the Tabert Formation shows that capillary number can significantly impact emulsion mobility control potential that has been shown to contribute to the observed oil recovery enhancement. Emulsions with adequate drop-to-pore size ratio and interfacial properties optimize emulsion mobility reduction and sweep efficiency. Results show that timing of the emulsion injection can promote conformance improvement and accelerate oil production. Mitigation of high injection pressure observed in continuous emulsion flooding is possible during cyclic WAE injection without significant oil recovery impairment.",{"EN":458},"Water-alternating-macroemulsion reservoir simulation through capillary number-dependent modeling",{"VOID":460},"[\"6733929525490359134\"]",{"VOID":462},"10.1007\u002Fs40430-017-0885-7","2024-05-01T14:55:58.390+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs40430-017-0885-7",[466,483,500],{"id":467,"sortIndex":21,"researcher":20,"roles":468,"affiliations":469,"properties":478},"1f2888e7-df9c-4f9e-9ea4-cd1390fe97fd",[203],[470],{"id":471,"sortIndex":21,"affiliation":472,"properties":20},"84bb5642-b832-47c3-b8fd-38c8fdb78747",{"id":471,"createTime":20,"updateTime":20,"relativeEntities":473,"slug":20,"properties":474,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":477,"statistic":20},[],{"title":475},{"VI":476},"Department of Mechanical Engineering, PUC-Rio, Rio de Janeiro, Brazil",[],{"title":479,"gsAuthor":481},{"VI":480},"Ranena V. 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Geometric modelling, numerical simulation, and optimization: applied mathematics at SINTEF. Springer, Berlin, pp 265–306",{},{"id":593,"text":594,"url":595,"identifiers":596},"4c68646b-0035-4279-8000-0006b275d4fa","Alvarado DA, Marsden SS (1979) Flow of oil-in-water emulsion through tubes and porous media. SPE J 19:369–377","https:\u002F\u002Flink.springer.com\u002F10.1007\u002Fs10440-022-00541-7",{"doi":597},"10.1007\u002Fs10440-022-00541-7",{"id":599,"text":600,"url":601,"identifiers":602},"69664214-117f-4785-bc35-a46c20c840c6","Baldygin A, Nobes DS, Mitra SK (2014) Water-alternate-emulsion (wae): a new technique for enhanced oil recovery. J Pet Sci Technol 121:167–173","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0920410514001776",{"doi":603},"10.1016\u002Fj.petrol.2014.06.021",{"id":593,"text":605,"url":595,"identifiers":606},"Cobos S, Carvalho MS, Alvarado V (2009) Flow of oil–water emulsions through a constricted capillary. Int J Multiph Flow 35:507–515",{"doi":597},{"id":593,"text":608,"url":595,"identifiers":609},"Corey AT (1954) The interrelation between gas and oil relative permeabilities. Prod Mon 19:38–41",{"doi":597},{"id":593,"text":611,"url":595,"identifiers":612},"Guillen V, Carvalho MS, Alvarado V (2012a) Pore scale and macroscopic displacement mechanism in emulsion flooding. Transp Porous Med 94:197–206",{"doi":597},{"id":614,"text":615,"url":616,"identifiers":617},"c6b7695b-03fc-4548-b447-f647dba9ff9e","Guillen V, Romero MI, Carvalho MS, Alvarado V (2012b) Capillary-driven mobility control in macro emulsion flow in porous media. Int J Multiph Flow 43:62–65","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0301932212000432",{"doi":618},"10.1016\u002Fj.ijmultiphaseflow.2012.03.001",{"id":593,"text":620,"url":595,"identifiers":621},"Hofman JAMH, Stein HN (1991) Permeability reduction of porous-media on transport of emulsions through them. Colloids Surf 61:317–329",{"doi":597},{"id":593,"text":623,"url":595,"identifiers":624},"Jain V, Demond AH (2002) Conductivity reduction due to emulsification during surfactant enhanced-aquifer remediation. 1. Emulsion transport. Environ Sci Technol 36:5426–5433",{"doi":597},{"id":593,"text":626,"url":595,"identifiers":627},"McAuliffe CD (1973a) Crude-oil-in-water emulsions to improve fluid-flow in an oil reservoir. J Pet Technol 25:721–726",{"doi":597},{"id":593,"text":629,"url":595,"identifiers":630},"McAuliffe CD (1973b) Oil-in-water emulsions and their flow properties in porous media. J Pet Technol 25:727–733",{"doi":597},{"id":632,"text":633,"url":634,"identifiers":635},"f9468e76-e9be-42b6-8205-477a33bd9f3c","Moradi M, Kazempour M, French JT, Alvarado V (2014) Dynamic flow response of crude oil-in-water emulsion during flow through porous media. Fuel 135:38–45","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0016236114005912",{"doi":636},"10.1016\u002Fj.fuel.2014.06.025",{"id":593,"text":638,"url":595,"identifiers":639},"Nogueira GL, Carvalho MS, Alvarado V (2013) Dynamic network model of mobility control in emulsion flow through porous media. Transport Porous Med 984:427–441",{"doi":597},{"id":593,"text":641,"url":595,"identifiers":642},"Olbricht WL, Leal LG (1983) The creeping motion of immiscible drops through a converging diverging tube. J Fluid Mech 134:329–355",{"doi":597},{"id":593,"text":644,"url":595,"identifiers":645},"Ouyang Y, Mansell RS, Rhue RD (1995) Emulsion-mediated transport of nonaqueous-phase liquid in porous media: a review. Crit Rev Environ Sci Technol 25:269–290",{"doi":597},{"id":647,"text":648,"url":649,"identifiers":650},"e0049697-09d1-4fab-a664-69326c10b149","Peng CC, Bengani LC, Jung HJ, Leclerc J, Gupta C, Chauhan A (2011) Emulsions and microemulsions for ocular drug delivery. J Drug Deliv Sci Technol 21:111–121","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS1773224711500103",{"doi":651},"10.1016\u002Fs1773-2247(11)50010-3",{"id":593,"text":653,"url":595,"identifiers":654},"Ponce FRV, Carvalho MS, Alvarado V (2014) Oil recovery modeling of macro-emulsion flooding at low capillary number. J Pet Sci Technol 119:112–122",{"doi":597},{"id":593,"text":656,"url":595,"identifiers":657},"Romero MI, Carvalho MS, Alvarado V (2011) Experiments and network model of flow of oil–water emulsion in porous media. Phys Rev E 84(046):305",{"doi":597},{"id":659,"text":660,"url":661,"identifiers":662},"47aa2c4f-89d9-49e6-ab3d-f1fa4dd42ada","Singh H, Ye A, Horne D (2009) Structuring food emulsions in the gastrointestinal tract to modify lipid digestion. Prog Lipid Res 48:92–100","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0163782708000635",{"doi":663},"10.1016\u002Fj.plipres.2008.12.001",{"id":20,"text":665,"url":666,"identifiers":667},"Society of Petroleum Engineering (2009) SPE comparative solution project—description of model 2. Online http:\u002F\u002Fwww.spe.org\u002Fweb\u002Fcsp\u002Fdatasets\u002Fset02.htm. Accessed 6 Dec 2016","http:\u002F\u002Fwww.spe.org\u002Fweb\u002Fcsp\u002Fdatasets\u002Fset02.htm",{},{"id":593,"text":669,"url":595,"identifiers":670},"Soo H, Radke C (1984a) The flow mechanism of dilute, stable emulsions in porous media. Ind Eng Chem Fundam 23:342–347",{"doi":597},{"id":593,"text":672,"url":595,"identifiers":673},"Soo H, Radke C (1984b) Velocity effects in emulsion flow through porous media. J Colloid Interface Sci 102:462–476",{"doi":597},{"id":593,"text":675,"url":595,"identifiers":676},"Tsai TM, Miksis MJ (1994) Dynamics of a drop in a constricted capillary-tube. J Fluid Mech 274:197–217",{"doi":597},{"id":678,"createTime":679,"updateTime":680,"relativeEntities":681,"slug":682,"properties":683,"entityType":194,"verifyStatus":195,"verifyTime":692,"verifyNote":197,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":693,"fullTextUrl":20,"authors":694,"publicationType":232,"publisherRelationship":727,"citationCount":795,"citationInfo":796,"publishDate":799,"publishYear":797,"citationAnalyzeStatus":446,"lastCitationAnalyze":680,"indexDatabases":800,"openAccess":20,"references":801,"isForceReanalyzing":305},"ac4fbd1b-817a-41fc-8026-6ce3ca1b009c","2024-02-05T12:16:55.564+00:00","2026-08-16T15:20:19.720+00:00",[],"Flexural-strength-prediction-of-randomly-oriented-chopped-glass-fiber-composite-laminate-using-artificial-neural-network",{"abstract":684,"title":686,"gsPaper":688,"doi":690},{"EN":685},"Randomly oriented chopped glass fiber reinforced polymer (ROCGFRP) composite laminate exhibits better flexural behavior, intended to use in various industrial applications such as aerospace, automobile, defence and marine engineering industries. This work employs the artificial neural network (ANN) model to predict the flexural strength of the randomly oriented chopped glass fiber composite beam using MATLAB\n                \n                  \n                \n                $$^{\\circledR }$$\n                \n              2021a. For this purpose, experimental flexural strength test based on ASTM D790 and finite element analysis (FEA) simulation with cohesive zone model using ANSYS Workbench 19.2 were conducted to compute the input and output parameters for the ANN model. Strain and stress datasets were chosen as the model’s input and output parameters, respectively. The entire datasets i.e., seven thousand six hundred and sixteen points, were divided into training, validation and test sets in the proportion of 70:15:15, respectively. The appropriate structure of the ANN model such as input layer, hidden layer, output layer, activation functions and training algorithm are selected and evaluated using statistical tools. The number of neurons in the hidden layer is optimized using Levenberg-Marquardt training algorithm. The training, validation and test components are fitted along the regression line, which shows strong relationship between analysis and desired outcomes. Thus, it is observed that, there is a high level of consistency is observed among the numerical, experimental and predicted results. Finally, the obtained ANN model is good predictor for flexural strength of ROCGFRP composite laminate.",{"EN":687},"Flexural strength prediction of randomly oriented chopped glass fiber composite laminate using artificial neural network",{"VOID":689},"[\"12450152884295842153\"]",{"VOID":691},"10.1007\u002Fs40430-023-04061-9","2024-04-29T08:31:36.719+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs40430-023-04061-9",[695,712],{"id":696,"sortIndex":21,"researcher":20,"roles":697,"affiliations":698,"properties":707},"4f8d7b9f-8e95-4455-90ec-d61e33f83e1f",[203],[699],{"id":700,"sortIndex":21,"affiliation":701,"properties":20},"792c1405-8cf4-4f95-90ac-83a9af5ecd59",{"id":700,"createTime":20,"updateTime":20,"relativeEntities":702,"slug":20,"properties":703,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":706,"statistic":20},[],{"title":704},{"EN":705},"Department of Mechanical Engineering, National Institute of Technology, Tiruchirappalli, India",[],{"title":708,"gsAuthor":710},{"VI":709},"Pankaj Chaupal",{"VOID":711},"[\"7rpZBVYAAAAJ\"]",{"id":713,"sortIndex":218,"researcher":20,"roles":714,"affiliations":715,"properties":722},"4a48df9a-1ee2-453e-b721-7c13d3e4f319",[203],[716],{"id":700,"sortIndex":21,"affiliation":717,"properties":20},{"id":700,"createTime":20,"updateTime":20,"relativeEntities":718,"slug":20,"properties":719,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":721,"statistic":20},[],{"title":720},{"EN":705},[],{"title":723,"gsAuthor":725},{"VI":724},"Prakash 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User’s Guide, MathWorks 2:77–81",{},{"id":593,"text":986,"url":595,"identifiers":987},"Mousavi MV, Khoramishad H (2019) The effect of hybridization on high-velocity impact response of carbon fiber-reinforced polymer composites using finite element modeling, Taguchi method and artificial neural network. Aerospace Sci Technol 94:105393",{"doi":597},{"id":593,"text":989,"url":595,"identifiers":990},"Waseem M, Kumar K (2014) Finite element modelling for delamination analysis of double cantilever beam specimen. Int J Mech Eng 1(5):27–34",{"doi":597},{"id":593,"text":992,"url":595,"identifiers":993},"I ASTM (2007) Standard test methods for flexural properties of unreinforced and reinforced plastics and electrical insulating materials. ASTM D790–07",{"doi":597},{"id":995,"text":996,"url":997,"identifiers":998},"89e007ad-800b-4298-a8a0-3c95123c683f","Harper L, Ahmed I, Felfel R, Qian C (2012) Finite element modelling of the flexural performance of resorbable phosphate glass fibre reinforced pla composite bone plates. J Mech Behav Biomed Mater 15:13–23","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS1751616112001956",{"doi":999},"10.1016\u002Fj.jmbbm.2012.07.002",{"id":1001,"createTime":1002,"updateTime":1003,"relativeEntities":1004,"slug":1005,"properties":1006,"entityType":194,"verifyStatus":195,"verifyTime":1016,"verifyNote":197,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":1017,"fullTextUrl":20,"authors":1018,"publicationType":232,"publisherRelationship":1083,"citationCount":20,"citationInfo":20,"publishDate":1150,"publishYear":797,"citationAnalyzeStatus":303,"lastCitationAnalyze":1151,"indexDatabases":1152,"openAccess":20,"references":20,"isForceReanalyzing":305},"fe05f306-bac0-4b92-8172-38bf37841029","2024-02-14T13:49:42.694+00:00","2026-08-13T17:40:45.887+00:00",[],"Numerical-analysis-and-experimental-verification-on-crack-growth-and-fatigue-life-in-double-edge-cracked-metal-plates",{"abstract":1007,"title":1009,"gsPaper":1011,"references":1012,"doi":1014},{"EN":1008},"The aims of the work were first to obtain the fatigue crack growth and life numerically and empirically and then compare the numerical results and experimental data. Grade 1 titanium plates with both symmetrically and anti-symmetrically waisted cracks were due to tension tests first to receive the load versus displacement diagrams and mechanical properties of strength and stiffness. Next from cyclic tests the load versus cycles curves were constructed and fatigue life obtained. The numerical analysis using finite element method and ANSYS workbench was to yield the numerical results of crack growth and life. From fracture mechanics, the critical crack length was considered as final failure, and then, the modified numerical results were received. The estimated crack growth rates showed that at high load ratios the rates were faster and the lives shorter; however, at low load rations both were reverse. The results in load versus cycles curves from two numerical method were found within acceptable errors with the experimental data.",{"EN":1010},"Numerical analysis and experimental verification on crack growth and fatigue life in double-edge cracked metal plates",{"VOID":189},{"VOID":1013},"Wang DA, Pan J (2005) A computational study of local stress intensity factor solutions for kinked cracks near spot welds in lap-shear specimens. Int J Solids Struct 42:6277–6298. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ijsolstr.2005.05.036\nYan Y (2006) Stress intensity and propagation of mixed-mode cracks. Eng Fail Anal 13:1022–1027. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.engfailanal.2005.04.007\nSinha S, Ghosh S (2006) Modeling cyclic ratcheting based fatigue life of HSLA steels using crystal plasticity FEM simulations and experiments. Int J Fatigue 28:1690–1774. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ijfatigue.2006.01.008\nRichard HA, Sander M, Fulland M, Kullmer G (2008) Development of fatigue crack growth in real structures. Eng Fract Mech 75:331–340. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.engfracmech.2007.01.017\nSingh IV, Mishra BK, Bhattacharya S, Patil RU (2012) The numerical simulation of fatigue crack growth using extended finite element method. Int J Fatigue 38:109–119. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ijfatigue.2011.08.010\nJha SK, John R, Larsen JM (2013) Incorporating small fatigue crack growth in probabilistic life prediction: effect of stress ratio in Ti–6Al–2Sn–4Zr–6Mo. Int J Fatigue 51:83–95. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ijfatigue.2013.01.008\nKumar S, Singh IV, Mishra BK (2015) A homogenized XFEM approach to simulate fatigue crack growth problems. Comput Struct 150:1–22. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.compstruc.2014.12.008\nGrbovic A, Rasuo B (2012) FEM based fatigue crack growth predictions for spar of light aircraft under variable amplitude loading. Eng Fail Anal 26:50–64. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.engfailanal.2012.07.003\nPetrasinovic D et al (2012) Extended finite element method (XFEM) applied to aircraft duralumin spar fatigue life estimation. Tech Gaz 19(3):557–562\nGrbovic AM (2011) Simulation of crack propagation in titanium mini dental implants (MDI). FME Trans 39(4):165–170\nShlyannikov VN, Ishtyryakov IS (2019) Crack growth rate and lifetime prediction for aviation gas turbine engine compressor disk based on nonlinear fracture mechanics parameters. Theor Appl Fract Mech 103:102313. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.tafmec.2019.102313\nLi Z, Wang X, Wang J, Lu Y, Shoji T (2020) High cycle fatigue behavior and numerical evaluation of Alloy 690TT steam generator tube. Int J Fatigue 137:105662. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ijfatigue.2020.105662\nGrbovic A, Rasuo B (2015) Use of modern numerical methods for fatigue life predictions. Recent trends in fatigue design. Nova Science Publishers Inc, New York\nSaber A, Shariati M, Nejad RM (2020) Experimental and numerical investigation of effect of size, position and geometry of some cutouts on fatigue life and crack growth path on AISI1045 steel plate. Theor Appl Fract Mech 10:102506. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.tafmec.2020.102506\nGori Y, Verma RP, Kumar A, Patil PP (2021) FEA based fatigue crack growth analysis. Mater Today Proc 46:10575–10581. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.matpr.2021.01.319\nBang DJ, Ince A, Oterkus E, Oterkus S (2021) Crack growth modeling and simulation of a peridynamic fatigue model based on numerical and analytical solution approaches. 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Eng Fract Mech 145:115–127. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.engfracmech.2015.03.027\nRozumek D, Marciniak Z, Lesiuk G, Correia JA, de Jesus AM (2018) Experimental and numerical investigation of mixed mode I + II and I + III fatigue crack growth in S355J0 steel. Int J Fatigue 113:160–170. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ijfatigue.2018.04.005\nPan X, Su H, Sun C, Hong Y (2018) The behavior of crack initiation and early growth in high-cycle and very-high-cycle fatigue regimes for a titanium alloy. Int J Fatigue 115:67–78. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ijfatigue.2018.03.021\nSajith S, Murthy KSRK, Robi PS (2020) Experimental and numerical investigation of mixed mode fatigue crack growth models in aluminum 6061–T6. Int J Fatigue 130:105285. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ijfatigue.2019.105285\nShlyannikov V, Fedotova D (2021) Distinctive features of crack growth rate for assumed pure mode II conditions. 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Adv Mater Sci Eng 2022:2705240. https:\u002F\u002Fdoi.org\u002F10.1155\u002F2022\u002F2705240\nGross D, Seelig T (2006) Fracture mechanisms: with an introduction to micromechanics, 1st edn. Springer, Germany\nJen MHR, Yang JM, Tseng YH, Wu YH (2022) Fatigue failure of hybrid nanocomposite laminates with kinked single- and double-edged cracks. Theor Appl Fract Mech 121:103473. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.tafmec.2022.103473",{"VOID":1015},"10.1007\u002Fs40430-022-03982-1","2024-09-04T23:24:03.430+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs40430-022-03982-1",[1019,1037,1052,1067],{"id":1020,"sortIndex":21,"researcher":20,"roles":1021,"affiliations":1022,"properties":1034},"24ce8e8c-f7f2-47a9-93fd-cea7fd619bd8",[203],[1023],{"id":1024,"sortIndex":21,"affiliation":1025,"properties":1031},"0311c819-9dcb-4220-bcdc-352cc3f1f80b",{"id":1024,"createTime":20,"updateTime":20,"relativeEntities":1026,"slug":20,"properties":1027,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1030,"statistic":20},[],{"title":1028},{"VI":1029},"Department of Mechanical and Electro Mechanical Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan, ROC",[],{"title":1032},{"VI":1033},"Department of Mechanical and Electro-Mechanical Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan, ROC",{"title":1035},{"VI":1036},"Ming-Hwa R. Jen",{"id":1038,"sortIndex":218,"researcher":20,"roles":1039,"affiliations":1040,"properties":1049},"dbcf3704-74a9-43f1-9343-f5b8a8f77c97",[203],[1041],{"id":1024,"sortIndex":21,"affiliation":1042,"properties":1047},{"id":1024,"createTime":20,"updateTime":20,"relativeEntities":1043,"slug":20,"properties":1044,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1046,"statistic":20},[],{"title":1045},{"VI":1029},[],{"title":1048},{"VI":1033},{"title":1050},{"VI":1051},"Yu-Jen 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the renewable energy culture grows, so does the demand for renewable energy production. The peak in demand is mainly due to the rise in fossil fuel prices and the harmful impact of fossil fuels on the environment. Among all renewable energy sources, solar energy is one of the cleanest, most abundant, and highest potential renewable energy sources. However, solar energy has some limitations, such as its intermittent nature and availability only on sunny days. Thus, the need for energy storage is realized and results in sensible and latent heat energy storage being used. Latent heat energy storage (LHES) offers high storage density and an isothermal condition for a low- to medium-temperature range compared to sensible heat storage. The work presented here provides a comprehensive review of the design, development, and application of latent heat energy storage. It is found that choosing a phase change material and its properties is the first stage of development. In the next phase, numerical and experimental investigations of performance estimation are reviewed. Further, performance enhancement techniques are found to be an effective practice to get better results. Finally, findings are categorized based on the application of LHES. The objective is to explore and present the potential of LHES to store solar heat. Thus, this review serves as the guidelines for the design and development of LHES.",{"EN":1163},"A comprehensive review of latent heat energy storage for various applications: an alternate to store solar thermal energy",{"VOID":1165},"[\"16878719559202724585\"]",{"VOID":1167},"IEA (2019) World energy balances: an overview. J Chem Inf Model 53:1689–1699. https:\u002F\u002Fdoi.org\u002F10.1017\u002FCBO9781107415324.004\nMuzzamal MB (2017) Energy efficient solar milk chiller. Int J Sci Technol Res 6:65–69\nTiwari AK, Sontake VC, Kalamkar VR (2020) Enhancing the performance of solar photovoltaic water pumping system by water cooling over and below the photovoltaic array. 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Energy Proced 110:83–88. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.egypro.2017.03.110",{"VOID":1169},"10.1007\u002Fs40430-022-03740-3","2024-05-16T11:33:28.502+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs40430-022-03740-3",[1173,1190,1207],{"id":1174,"sortIndex":21,"researcher":20,"roles":1175,"affiliations":1176,"properties":1185},"102e221b-05c9-4307-9d27-d383727320ea",[203],[1177],{"id":1178,"sortIndex":21,"affiliation":1179,"properties":20},"b248b53f-0543-40bb-916d-927b95b4278b",{"id":1178,"createTime":20,"updateTime":20,"relativeEntities":1180,"slug":20,"properties":1181,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1184,"statistic":20},[],{"title":1182},{"VI":1183},"Department of Mechanical Engineering, Visvesvaraya National Institute of Technology – Nagpur, India",[],{"title":1186,"gsAuthor":1188},{"VI":1187},"Devendra Raut",{"VOID":1189},"[\"dvsxDf0AAAAJ\"]",{"id":1191,"sortIndex":218,"researcher":20,"roles":1192,"affiliations":1193,"properties":1202},"9980fe27-aea0-4d75-ae65-5932d27d462c",[203],[1194],{"id":1195,"sortIndex":21,"affiliation":1196,"properties":20},"cddde8ea-ce61-4809-a313-01f9027741d8",{"id":1195,"createTime":20,"updateTime":20,"relativeEntities":1197,"slug":20,"properties":1198,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1201,"statistic":20},[],{"title":1199},{"VI":1200},"Solar Energy Division, Sardar Patel Renewable Energy Research Institute (SPRERI), Anand, India",[],{"title":1203,"gsAuthor":1205},{"VI":1204},"Arunendra K. 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Kalamkar",{"VOID":1221},"[\"yu3CdsMAAAAJ\"]",{"url":1171,"publisher":1223,"properties":1285},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":1224,"slug":10,"properties":1225,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":1229,"manageAffiliations":1254,"indexDatabases":1265,"url":115,"thumbnailPath":20,"statistic":1280,"gsStatistic":20,"type":172,"analyzePriority":20},[],{"issn":1226,"title":1227,"eissn":1228},{"VOID":13},{"EN":15},{"VOID":17},[1230,1234,1238,1242,1246,1250],{"id":36,"createTime":20,"updateTime":20,"relativeEntities":1231,"label":1232,"description":1233,"parentId":20,"standard":20,"scholarHubFieldId":20},[],{"EN":39},{},{"id":24,"createTime":20,"updateTime":20,"relativeEntities":1235,"label":1236,"description":1237,"parentId":20,"standard":20,"scholarHubFieldId":20},[],{"EN":27},{},{"id":42,"createTime":20,"updateTime":20,"relativeEntities":1239,"label":1240,"description":1241,"parentId":20,"standard":20,"scholarHubFieldId":20},[],{"EN":45},{},{"id":48,"createTime":20,"updateTime":20,"relativeEntities":1243,"label":1244,"description":1245,"parentId":20,"standard":20,"scholarHubFieldId":20},[],{"EN":51},{},{"id":30,"createTime":20,"updateTime":20,"relativeEntities":1247,"label":1248,"description":1249,"parentId":20,"standard":20,"scholarHubFieldId":20},[],{"EN":33},{},{"id":54,"createTime":20,"updateTime":20,"relativeEntities":1251,"label":1252,"description":1253,"parentId":20,"standard":20,"scholarHubFieldId":20},[],{"EN":57},{},[1255,1260],{"id":61,"createTime":20,"updateTime":20,"relativeEntities":1256,"slug":20,"properties":1257,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1259,"statistic":20},[],{"title":1258},{"EN":65},[67],{"id":69,"createTime":20,"updateTime":20,"relativeEntities":1261,"slug":20,"properties":1262,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1264,"statistic":20},[],{"title":1263},{"EN":73},[67],[1266,1273],{"id":77,"indexDatabase":1267,"url":90,"indexYears":20,"academicFieldIds":1272,"indexDatabaseRanking":20},{"id":79,"createTime":20,"updateTime":20,"relativeEntities":1268,"label":1269,"description":1270,"key":86,"publicationTags":1271,"standard":20},[],{"EN":82,"VI":82},{"EN":84,"VI":85},[88,89],[92],{"id":94,"indexDatabase":1274,"url":105,"indexYears":106,"academicFieldIds":1279,"indexDatabaseRanking":114},{"id":96,"createTime":20,"updateTime":20,"relativeEntities":1275,"label":1276,"description":1277,"key":102,"publicationTags":1278,"standard":20},[],{"EN":99,"VI":99},{"EN":99,"VI":101},[104],[108,109,110,111,112,113],{"impactFactor":21,"impactFactorByYear":1281,"i10Index":128,"i10IndexLast5Year":129,"totalPublication":130,"totalPublicationByYear":1282,"totalCitation":144,"totalCitationByYear":1283,"totalCitationPerPublication":158,"totalCitationPerPublicationByYear":1284,"hindexLast5Year":171,"hindex":171},{"2014":118,"2015":119,"2016":120,"2017":121,"2018":122,"2019":123,"2020":124,"2021":125,"2022":126,"2023":127},{"2013":132,"2014":133,"2015":134,"2016":135,"2017":136,"2018":137,"2019":138,"2020":139,"2021":140,"2022":141,"2023":142,"2024":143},{"2013":146,"2014":147,"2015":148,"2016":149,"2017":150,"2018":151,"2019":152,"2020":153,"2021":154,"2022":155,"2023":156,"2024":157},{"2013":160,"2014":161,"2015":162,"2016":163,"2017":164,"2018":165,"2019":166,"2020":167,"2021":168,"2022":169,"2023":170,"2024":118},{"pages":1286,"volume":1288},{"VOID":1287},"1-38",{"VOID":300},34,{"total":1289,"publishYear":302,"statisticByYear":1291},{"2022":218,"2023":1069,"2024":1292,"2025":1293,"2026":1293},12,9,"2022-09-05","2026-07-29T20:20:33.037+00:00",[114,88],{"id":1298,"createTime":1299,"updateTime":1300,"relativeEntities":1301,"slug":1302,"properties":1303,"entityType":194,"verifyStatus":195,"verifyTime":1316,"verifyNote":197,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":1317,"fullTextUrl":20,"authors":1318,"publicationType":232,"publisherRelationship":1368,"citationCount":1431,"citationInfo":1432,"publishDate":1436,"publishYear":1433,"citationAnalyzeStatus":1437,"lastCitationAnalyze":1438,"indexDatabases":1439,"openAccess":20,"references":20,"isForceReanalyzing":305},"f17a9c52-8164-459b-811c-06f177d58fc9","2024-04-06T16:31:47.489+00:00","2026-07-29T08:46:07.739+00:00",[],"Assessment-of-various-isogeometric-contact-surface-refinement-strategies",{"abstract":1304,"title":1306,"gsPaper":1308,"keywords":1310,"references":1312,"doi":1314},{"EN":1305},"Since its inception, isogeometric analysis (IGA) has shown significant advantages over Lagrange polynomials-based finite element analysis (FEA), especially for contact problems. IGA often uses C\n                \n                  \n                \n                $$^\\text {1}$$\n                \n              -continuous non-uniform rational B-splines (NURBS) as basis functions, providing a smooth description of kinematic variables across the contact interface. This leads to increased accuracy and stability in the numerical solutions. However, from the existing literature on isogeometric contact analysis, it is not yet clear what interpolation order and continuity of NURBS one should employ to accurately capture the distribution of contact forces across the contact interface. The present work aims to fill this gap and provides a comparative assessment of different NURBS-based standard (conventional) refinement strategies for contact problems within the IGA framework. A recently proposed refinement strategy, known as the varying-order (VO) based NURBS discretization, has demonstrated its capability to refine geometry through the implementation of order elevation in a controlled manner. However, a detailed investigation that directly compares the VO based NURBS discretization with the standard NURBS discretization has not yet been carried out. Therefore, a thorough study of the VO based discretization strategy is also conducted, evaluating its effectiveness in comparison with the standard discretization strategy for contact problems. For this, a few examples on contact problems are solved using an in-house MATLAB® code. The solution to these examples shows that quadratic order standard NURBS discretization is sufficient to achieve the desired level of solution accuracy just by increasing the mesh size. It is further demonstrated that VO based discretization can achieve much higher accuracy than standard discretization, even with a coarse mesh, by generating additional degrees of freedom in the contact boundary layer. In addition, VO based discretization makes considerable savings in analysis time to achieve the same accuracy level as standard discretization.",{"EN":1307},"Assessment of various isogeometric contact surface refinement strategies",{"VOID":1309},"[\"9895919649337485750\"]",{"EN":1311},"",{"VOID":1313},"Agrawal V, Gautam SS (2019) Higher order Hermite enriched contact finite elements for adhesive contact problems. Int J Mater Struct Integr 13(1–3):16–31. https:\u002F\u002Fdoi.org\u002F10.1504\u002FIJMSI.2019.100380\nAgrawal V, Gautam SS (2019) IGA: a simplified introduction and implementation details for finite element users. J Inst Eng Ser C 100(3):561–585. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs40032-018-0462-6\nAgrawal V, Gautam SS (2019) Investigation of contact pressure oscillations with different segment-to-segment based isogeometric contact formulations. In: Wahab MA (ed) Lect. Notes Mech Eng Springer, Singapore, pp 90–103. https:\u002F\u002Fdoi.org\u002F10.1007\u002F978-981-13-2273-0_8\nAgrawal V, Gautam SS (2020) Investigating the influence of higher-order NURBS discretization on contact force oscillation for large deformation contact using isogeometric analysis. In: Voruganti H, Kumar K, Krishna P, Jin X (eds) Lect. Notes Mech Eng Springer, Singapore, pp 343–350. https:\u002F\u002Fdoi.org\u002F10.1007\u002F978-981-15-1201-8_39\nAgrawal V, Gautam SS (2020) Varying-order NURBS discretization: an accurate and efficient method for isogeometric analysis of large deformation contact problems. 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Comput Mech 60:1011–1031. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00466-017-1455-7",{"VOID":1315},"10.1007\u002Fs40430-024-04712-5","2024-06-23T10:59:33.938+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs40430-024-04712-5",[1319,1336,1353],{"id":1320,"sortIndex":21,"researcher":20,"roles":1321,"affiliations":1322,"properties":1331},"6fd19a29-715a-4986-9f41-97d34faabdde",[203],[1323],{"id":1324,"sortIndex":21,"affiliation":1325,"properties":20},"9ae5c4c7-d54b-4cf2-a194-4cb94f15d7e1",{"id":1324,"createTime":20,"updateTime":20,"relativeEntities":1326,"slug":20,"properties":1327,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1330,"statistic":20},[],{"title":1328},{"VI":1329},"Department of Mechanical Engineering, Indian Institute of Technology Guwahati, Guwahati, India",[],{"title":1332,"gsAuthor":1334},{"VI":1333},"Sumit Kumar 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this work, we study the ensemble size influence on an adaptive ensemble-based methodology for history matching of petroleum reservoirs. The assimilation scheme used is an adaptive ensemble smoother with multiple data assimilation (ES-MDA) in which both the total number of assimilations and the inflation factor of each iteration are defined automatically by the algorithm. This fact leads to the assumption that the predefined algorithm parameters may have influence in the total number of assimilations and the inflation factors. One main parameter that can be investigated is the number of ensemble members used in the assimilation, also called ensemble size. The ensemble size influence was analyzed by applying the adaptive ES-MDA in a synthetic large-scale reservoir model. As a result of the investigation, the ensemble size showed influence on the reduction in the uncertainty of the posterior models, but it did not show any influence on the total number of assimilations and on the inflation factor selection.",{"EN":1450},"Ensemble size investigation in adaptive ES-MDA reservoir history matching",{"VOID":1452},"[\"15234246660959720353\"]",{"VOID":1454},"Aanonsen SI, Nævdal G, Oliver DS, Reynolds AC, Vallès B (2009) The ensemble Kalman filter in reservoir engineering—a review. SPE J 14(3):393–412. https:\u002F\u002Fdoi.org\u002F10.2118\u002F117274-PA\nOliver DS, Chen Y (2011) Recent progress on reservoir history matching: a review. Comput Geosci 15(1):185–221. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10596-010-9194-2\nRwechungura R, Dadashpour M, Kleppe J (2011) Advanced history matching techniques reviewed. In: SPE middle east oil and gas show and conference (MEOS), SPE. https:\u002F\u002Fdoi.org\u002F10.2118\u002F142497-MS\nEvensen G (1994) Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics. J Geophys Res 99(C5):10143–10162. https:\u002F\u002Fdoi.org\u002F10.1029\u002F94JC00572\nEvensen G (2003) The ensemble Kalman filter: theoretical formulation and practical implementation. Ocean Dyn 53:343–367. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10236-003-0036-9\nHaugen V, Nævdal G, Natvik LJ, Evensen G, Berg AM, Flornes KM (2008) History matching using the ensemble Kalman filter on a North Sea field case. SPE J 13(4):382–391. https:\u002F\u002Fdoi.org\u002F10.2118\u002F102430-PA\nZhang Y, Oliver DS (2011) History matching using the ensemble Kalman filter with multiscale parameterization: a field case study. SPE J 16(2):307–317. https:\u002F\u002Fdoi.org\u002F10.2118\u002F118879-PA\nHeidari L, Gervais V, Ravalec ML, Wackernagel H (2013) History matching of petroleum reservoir models by the ensemble Kalman filter and parameterization methods. Comput Geosci 55:84–95. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.cageo.2012.06.006\nShuai Y, White C, Sun T, Feng Y (2016) A gathered EnKF for continuous reservoir model updating. J Petrol Sci Eng 139:205–218. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.petrol.2016.01.005\nThulin K, Li G, Aanonsen SI, Reynolds AC (2007) Estimation of initial fluid contacts by assimilation of production data with EnKF. In: SPE annual technical conference and exhibition (ATCE), SPE. https:\u002F\u002Fdoi.org\u002F10.2118\u002F109975-MS\nWang Y, Li G, Reynolds AC (2010) Estimation of depths of fluid contacts and relative permeability curves by history matching using iterative ensemble-Kalman smoothers. SPE J 15(2):509–525. https:\u002F\u002Fdoi.org\u002F10.2118\u002F119056-PA\nThulin K, Nævdal G, Skaug HJ, Aanonsen SI (2011) Quantifying Monte Carlo uncertainty in the ensemble Kalman filter. SPE J 16(1):172–182. https:\u002F\u002Fdoi.org\u002F10.2118\u002F123611-PA\nvan Leeuwen PJ, Evensen G (1996) Data assimilation and inverse methods in terms of a probabilistic formulation. Mon Weather Rev 124:2898–2913. https:\u002F\u002Fdoi.org\u002F10.1175\u002F1520-0493(1996)124%3c2898:DAAIMI%3e2.0.CO;2\nMa X, Hetz G, Wang X, Bi L, Hoda N (2017) A robust iterative ensemble smoother method for efficient history matching and uncertainty quantification. In: SPE reservoir simulation conference (RSC), SPE. https:\u002F\u002Fdoi.org\u002F10.2118\u002F182693-MS\nEmerick AA, Reynolds AC (2013) Ensemble smoother with multiple data assimilation. Comput Geosci 55:3–15. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.cageo.2012.03.011\nMaucec M, Ravanelli FM, Lyngra S, Zhang SJ, Alramadhan AA, Abdelhamid OA, Al-Garni SA (2016) Ensemble-based assisted history matching with rigorous uncertainty quantification applied to a naturally fractured carbonate reservoir. In: SPE annual technical conference & exhibition (ATCE), SPE. https:\u002F\u002Fdoi.org\u002F10.2118\u002F181325-MS\nBreslavich ID, Sarkisov GG, Marakova ES (2017) Experience of MDA ensemble smoother practice for Volga-Ural Oilfield. In: SPE Russian petroleum technology conference (RPTC), SPE. https:\u002F\u002Fdoi.org\u002F10.2118\u002F187800-MS\nEmerick AA (2016) Analysis of the performance of ensemble-based assimilation of production and seismic data. J Petrol Sci Eng 139:219–239. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.petrol.2016.01.029\nMorosov AL, Schiozer DJ (2017) Field-development process revealing uncertainty-assessment pitfalls. SPE Reserv Eval Eng 20(3):1–14. https:\u002F\u002Fdoi.org\u002F10.2118\u002F180094-PA\nLe DH, Emerick AA, Reynolds AC (2016) An adaptive ensemble smoother with multiple data assimilation for assisted history matching. SPE J 21(6):2195–2207. https:\u002F\u002Fdoi.org\u002F10.2118\u002F173214-PA\nRafiee J, Reynolds AC (2017) Theoretical and efficient practical procedures for the generation of inflation factors for ES-MDA. Inverse Probl 33(11):1–28. https:\u002F\u002Fdoi.org\u002F10.1088\u002F1361-6420\u002Faa8cb2\nEvensen G (2018) Analysis of iterative ensemble smoother for solving inverse problems. Comput Geosci 22(3):885–908. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10596-018-9731-y\nIglesias MA (2015) Iterative regularization for ensemble data assimilation in reservoir models. Comput Geosci 19(1):177–212. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10596-014-9456-5\nSilva VLS, Emerick AA, Couto P, Alves JLD (2017) History matching and production optimization under uncertainties—application of closed-loop reservoir management. J Petrol Sci Eng 157:860–874. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.petrol.2017.07.037\nSoares RV, Maschio C, Schiozer DJ (2018) Applying a localization technique to Kalman Gain and assessing the influence on the variability of models in history matching. J Petrol Sci Eng 169:110–125. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.petrol.2018.05.059\nEmerick AA (2018) Deterministic ensemble smoother with multiple data assimilation as an alternative for history-matching seismic data. Comput Geosci 22(5):1–12. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10596-018-9745-5\nRanazzi PH, Sampaio MA (2018) Análise da Influência do Tamanho do Conjunto na Aplicação do Conjunto Suavizado no Processo de Ajuste de Histórico. In: Rio oil & gas expo and conference (ROG), IBP\nRanazzi PH, Sampaio MA (2019) Influence of the Kalman gain localization in adaptive ensemble smoother history matching. J Petrol Sci Eng 179:244–256. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.petrol.2019.04.079\nChen Y, Oliver DS (2010) Ensemble-based closed-loop optimization applied to Brugge field. SPE Reservoir Eval Eng 13(1):56–71. https:\u002F\u002Fdoi.org\u002F10.2118\u002F118926-PA\nBurgers G, van Leeuwen PJ, Evensen G (1998) Analysis scheme in the ensemble Kalman filter. Mon Weather Rev 126(6):1719–1724. https:\u002F\u002Fdoi.org\u002F10.1175\u002F1520-0493(1998)126%3c1719:ASITEK%3e2.0.CO;2\nChen Y, Oliver DS (2016) Localization and regularization for iterative ensemble smoothers. Comput Geosci 21(1):13–30. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10596-016-9599-7\nMaschio C, Avansi G, Schiozer DJ, Santos A (2015) Study case for history matching and uncertainties reduction based on UNISIM-I field. www.unisim.cepetro.unicamp.br\u002Fbenchmarks\u002Fbr\u002Funisim-i\u002Funisim-i-h. Accessed 13 Mar 2019\nAvansi GD, Schiozer DJ (2015) UNISIM-I: synthetic model for reservoir development and management applications. Int J Model Simul Petrol Ind 9(1):21–30\nGaspari G, Cohn SE (1999) Construction of correlation functions in two and three dimensions. Q J R Meteorol Soc 125(554):723–757. https:\u002F\u002Fdoi.org\u002F10.1002\u002Fqj.49712555417\nOliver DS, Reynolds AC, Liu N (2008) Inverse theory for petroleum reservoir characterization and history matching. Cambridge University Press, Cambridge\nEvensen G (2009) The ensemble Kalman filter, 2nd edn. 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gradient and nonlocal influences have important roles in the mechanical characteristics of structures as they are scaled down to nanoscopic dimensions. In this research, an attempt is made to capture both effects on the static bending response of nanoscopic Bernoulli–Euler beams by means of a comprehensive model. For this purpose, the strain gradient theory of Mindlin is combined with the integral (original) form of Eringen’s nonlocal theory. Also, the integral nonlocal formulation is written on the basis of both strain-driven and stress-driven versions of nonlocal theory. This mixed nonlocal strain gradient formulation is capable of reducing to the size-independent and combination of integral nonlocal strain gradient family theories by employing simple substitutions. Through constructing finite difference-based differential and integral matrix operators, numerical solution approaches are developed to obtain the deflection of nanobeams under various end conditions. In addition, for the solution of governing equation of strain-driven nonlocal strain gradient theory, an efficient technique is presented that is applied to the variational statement of the problem in a direct approach. Selected numerical results are provided to explore the simultaneous influences of strain gradient terms and nonlocality based on different theories on the static bending response of beams. It is revealed that the developed size-dependent model has the ability of considering strain gradient and nonlocal influences in the most general way.",{"EN":1576},"Bending analysis of nanoscopic beams based upon the strain-driven and stress-driven integral nonlocal strain gradient theories",{"VOID":1578},"[\"9510850682165376327\"]",{"VOID":1580},"Rao FB, Almumen H, Fan Z, Li W, Dong LX (2012) Inter-sheet-effect-inspired graphene sensors: design, fabrication and characterization. Nanotechnology 23:105501\nZhang Y, Chang G, Liu S, Lu W, Tian J, Sun X (2011) A new preparation of Au nanoplates and their application for glucose sensing. Biosens Bioelectron 28:344–348\nRafiee MA, Rafiee J, Wang Z, Song H, Yu ZZ, Koratkar N (2009) Enhanced mechanical properties of nanocomposites at low graphene content. ACS Nano 3:3884–3890\nStankovich S, Dikin DA, Dommett GHB, Kohlhaas KM, Zimney EJ, Stach EA, Piner RD, Nguyen ST, Ruoff RS (2006) Graphene-based composite materials. Nature 442:282–286\nEringen AC (1972) Nonlocal polar elastic continua. Int J Eng Sci 10:1–16\nEringen AC, Edelen DGB (1972) On nonlocal elasticity. Int J Eng Sci 10:233–248\nEringen AC (1983) On differential equations of nonlocal elasticity and solutions of screw dislocation and surface waves. J Appl Phys 54:4703–4710\nArash B, Wang Q (2012) A review on the application of nonlocal elastic models in modeling of carbon nanotubes and graphenes. Comput Mater Sci 51:303–313\nWang KF, Wang BL, Kitamura T (2016) A review on the application of modified continuum models in modeling and simulation of nanostructures. Acta Mech Sin 32:83–100\nRafii-Tabar H, Ghavanloo E, Fazelzadeh SA (2016) Nonlocal continuum-based modeling of mechanical characteristics of nanoscopic structures. Phys Rep 638:1–97\nEltaher MA, Khater ME, Emam SA (2016) A review on nonlocal elastic models for bending, buckling, vibrations, and wave propagation of nanoscale beams. Appl Math Model 40:4109–4128\nThai H-T, Vo TP, Nguyen T-K, Kim S-E (2017) A review of continuum mechanics models for size-dependent analysis of beams and plates. Compos Struct 177:196–219\nGürses M, Akgöz B, Civalek Ö (2012) Mathematical modeling of vibration problem of nano-sized annular sector plates using the nonlocal continuum theory via eight-node discrete singular convolution transformation. Appl Math Comput 219:3226–3240\nCivalek Ö, Uzun B, Özgür Yaylı M, Akgöz B (2020) Size-dependent transverse and longitudinal vibrations of embedded carbon and silica carbide nanotubes by nonlocal finite element method. Eur Phys J Plus 135(2020):381\nKhodabakhshi P, Reddy JN (2015) A unified integro-differential nonlocal model. Int J Eng Sci 95:60–75\nFernández-Sáez J, Zaera R, Loya JA, Reddy JN (2016) Bending of Euler–Bernoulli beams using Eringen’s integral formulation: a paradox resolved. Int J Eng Sci 99:107–116\nTuna M, Kirca M (2016) Exact solution of Eringen’s nonlocal integral model for bending of Euler–Bernoulli and Timoshenko beams. Int J Eng Sci 105:80–92\nEptaimeros KG, Koutsoumaris CC, Tsamasphyros GJ (2016) Nonlocal integral approach to the dynamical response of nanobeams. Int J Mech Sci 115–116:68–80\nNorouzzadeh A, Ansari R (2017) Finite element analysis of nano-scale Timoshenko beams using the integral model of nonlocal elasticity. Physica E 88:194–200\nNorouzzadeh A, Ansari R, Rouhi H (2017) Pre-buckling responses of Timoshenko nanobeams based on the integral and differential models of nonlocal elasticity: an isogeometric approach. Appl Phys A 123:330\nKoutsoumaris CC, Eptaimeros KG, Tsamasphyros GJ (2017) A different approach to Eringen’s nonlocal integral stress model with applications for beams. Int J Solids Struct 112:222–238\nRomano G, Barretta R, Diaco M, Marotti de Sciarra F (2017) Constitutive boundary conditions and paradoxes in nonlocal elastic nanobeams. Int J Mech Sci 121:151–156\nRomano G, Barretta R (2017) Nonlocal elasticity in nanobeams: the stress-driven integral model. Int J Eng Sci 115:14–27\nRomano G, Barretta R (2017) Stress-driven versus strain-driven nonlocal integral model for elastic nano-beams. Compos Part B 114:184–188\nFaraji Oskouie M, Ansari R, Rouhi H (2018) Bending of Euler–Bernoulli nanobeams based on the strain-driven and stress-driven nonlocal integral models: a numerical approach. Acta Mech Sin 2018(34):871–882\nMindlin RD (1964) Micro-structure in linear elasticity. Arch Rat Mech Anal 16:51–78\nMindlin RD, Eshel NN (1968) On first strain-gradient theories in linear elasticity. Int J Solids Struct 4:109–124\nMindlin RD (1965) Second gradient of strain and surface-tension in linear elasticity. Int J Solids Struct 1:417–438\nMindlin RD, Tiersten H (1962) Effects of couple-stresses in linear elasticity. Arch Rat Mech Anal 11:415–448\nToupin RA (1964) Theories of elasticity with couple-stress. Arch Rat Mech Anal 17:85–112\nLam DC, Yang F, Chong A, Wang J, Tong P (2003) Experiments and theory in strain gradient elasticity. J Mech Phys Solids 51:1477–1508\nYang F, Chong A, Lam DC, Tong P (2002) Couple stress based strain gradient theory for elasticity. Int J Solids Struct 39:2731–2743\nAkgöz B, Civalek Ö (2015) A microstructure-dependent sinusoidal plate model based on the strain gradient elasticity theory. Acta Mech 226:2277–2294\nFarahmand H (2020) Analytical solutions of bending and free vibration of moderately thick micro-plate via two-variable strain gradient theory. J Braz Soc Mech Sci Eng 42:251\nAkgöz B, Civalek Ö (2016) Bending analysis of embedded carbon nanotubes resting on an elastic foundation using strain gradient theory. Acta Astronaut 119:1–12\nNarendar S, Gopalakrishnan S (2010) Ultrasonic wave characteristics of nanorods via nonlocal strain gradient models. J Appl Phys 107:084312\nPolizzotto C (2015) A unifying variational framework for stress gradient and strain gradient elasticity theories. Eur J Mech A\u002FSolids 49:430–440\nLim CW, Zhang G, Reddy JN (2015) A higher-order nonlocal elasticity and strain gradient theory and its applications in wave propagation. J Mech Phys Solids 78:298–313\nMehralian F, Tadi Beni Y, Karimi Zeverdejani M (2017) Nonlocal strain gradient theory calibration using molecular dynamics simulation based on small scale vibration of nanotubes. Phys B 514:61–69\nFaghidian SA (2018) Reissner stationary variational principle for nonlocal strain gradient theory of elasticity. Eur J Mech A\u002FSolids 70:115–126\nNorouzzadeh A, Ansari R, Rouhi H (2019) Nonlinear bending analysis of nanobeams based on the nonlocal strain gradient model using an isogeometric finite element approach. Iranian J Sci Technol Trans Civil Eng 43:533–547\nBarretta R, Marotti de Sciarra F (2018) Constitutive boundary conditions for nonlocal strain gradient elastic nano-beams. Int J Eng Sci 130:187–198\nCivalek O, Uzun B, Yaylı MO, Akgöz B (2019) Size-dependent nonlinear forced oscillation of self-assembled nanotubules based on the nonlocal strain gradient beam model. J Braz Soc Mech Sci Eng 41:239\nEbrahimi F, Barati MR, Civalek Ö (2020) Application of Chebyshev–Ritz method for static stability and vibration analysis of nonlocal microstructure-dependent nanostructures. Eng Comput 36:953–964\nRajasekaran S, Bakhshi Khaniki H (2018) Bending, buckling and vibration analysis of functionally graded non-uniform nanobeams via finite element method. J Braz Soc Mech Sci Eng 40:549\nNorouzzadeh A, Ansari R, Rouhi H (2018) Isogeometric vibration analysis of small-scale Timoshenko beams based on the most comprehensive size-dependent theory. Scientia Iranica 25:1864–1878\nZhu X, Li L (2017) Closed form solution for a nonlocal strain gradient rod in tension. Int J Eng Sci 119:16–28\nZhu X, Li L (2017) On longitudinal dynamics of nanorods. Int J Eng Sci 120:129–145\nFakher M, Hosseini-Hashemi S (2017) Bending and free vibration analysis of nanobeams by differential and integral forms of nonlocal strain gradient with Rayleigh–Ritz method. Mater Res Exp 4:125025\nKumar D, Heinrich C, Waas AM (2008) Buckling analysis of carbon nanotubes modeled using nonlocal continuum theories. J Appl Phys 103:073521\nAkgoz B, Civalek O (2013) Buckling analysis of functionally graded microbeams based on the strain gradient theory. Acta Mech 224:2185–2201\nKahrobaiyan MH, Asghari M, Ahmadian MT (2013) Strain gradient beam element. 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The effect of pressure was found to affect on a different way short-term and long-term properties of the composite. Under atmospheric pressure, more oil was absorbed by the composite than at 17 bar. This behavior was attributed to the effect of the hydrostatic pressure upon the polymeric matrix-free volume. The set of mechanical properties evaluated by tree-point bending test (flexural strength, elastic modulus, toughness, and deformation at maximum load) was also more affected when aging was conducted under atmospheric pressure. However, the steady state creep rate of the composite aged under 17 bar was higher than that of the material aged at atmospheric pressure, reducing the expected service life of the repair joint when both temperature and pressure are applied together.",{"EN":1726},"Evaluation of the mechanical performance of the creep behavior of a fiberglass repair after aging in oil",{"VOID":1728},"[\"9618933821987315596\"]",{"VOID":1730},"Hsu TM, Skogsberg J, Karayaka M (2001) Composites utilization on a spar platform—potential economic impact and technical gaps. In: Wang SS, Willians JG, Lo KH (eds) Composite materials for offshore operations, vol 3. University of Houston, CEAC Publishing, Houston, pp 19–43\nHota G, Liang R (2011) Advanced fiber reinforced polymer composites for sustainable civil infrastructures. 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J Macromol Sci Part A 49:81–84\nAlizadeh F, Sutherland LS, Guedes Soares C (2016) Effect of vacuum bag pressure on the flexural properties of GFRP composite laminates. In: Guedes Soares C, Santos TA (eds) Maritime technology and engineering 3, vol 1. CRC Press, Boca Raton, pp 429–434\nStern S, Dierdorf D (2005) Thermogravimetric analysis (TGA) of various epoxy composite formulations. Air Force Research Laboratory, Report 2005-4585, Tyndall AFB, FL\nMay CA (1987) Epoxy resins. In: Reinhart TJ (ed) Engineered materials handbook, vol 1. Composites. ASM International, Materials Park, pp 66–77\nValliappan M, Roux JA, Vaughan JG, Arafat ES (1996) Die and post-die temperature and cure in graphite\u002Fepoxy composites. Comp Part B 27:1–9\nCarbas RJC, da Silva LFM, Marques EAS, Lopes AM (2013) Effect of post-cure on the glass transition temperature and mechanical properties of epoxy adhesives. J Adhes Sci Technol 27:2542–2557\nOdegard GM, Bandyopadhyay A (2011) Physical aging of epoxy polymers and their composites. J Polym Sci Part B Polym Phys 49:1695–1716\nKlopffer MH, Flaconnèche B (2001) Transport properties of gases in polymers: bibliographic review. Oil Gas Sci Technol 56(3):223–244\nShaito A, Fairbrother D, Sterling J, D’Souza NA (2010) Ethylene maleated amorphous propylene compatibilized polyethylene nanocomposites: stress and temperature effects on nonlinear creep. Polym Eng Sci 50:1633–1645\nEaton MJ, Pullin R, Holford KM (2012) Acoustic emission source location in composite materials using Delta T Mapping. Comp Part A 43:856–863\nChacón YG, Paciornik S, d’Almeida JRM (2010) Microstructural evaluation and flexural mechanical behavior of pultruded glass fiber composites. 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