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Academic literature on the topic 'Life Prediction Model'

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Published: 4 June 2021
Last updated: 5 February 2022

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Journal articles on the topic "Life Prediction Model"

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Ahmad, J., U. Santhosh, and S. Hoff. "A Metal Matrix Composite Damage and Life Prediction Model." Journal of Engineering for Gas Turbines and Power 120, no. 4 (October 1, 1998): 825–32. http://dx.doi.org/10.1115/1.2818475.

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A simple analytical model is derived for the prediction of time-dependent deformation and damage response of metal matrix composites under fiber direction loading. The model can be used in conjunction with a number of viscoplastic constitutive models to describe the matrix material behavior. Damage in the form of progressive fiber fractures is incorporated using a mechanistic approach. The criterion for fiber fractures can be based on statistical information on fiber strength. When used in conjunction with a prescribed failure condition for a composite, the model provides a means for predicting composite life under general thermomechanical load conditions. Based on comparison of results with detailed finite element analyses and with laboratory test data, it appears that the simple model provides reasonably accurate predictions.
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Cruse, T. A., S. E. Stewart, and M. Ortiz. "Thermal Barrier Coating Life Prediction Model Development." Journal of Engineering for Gas Turbines and Power 110, no. 4 (October 1, 1988): 610–16. http://dx.doi.org/10.1115/1.3240179.

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Ceramic thermal barrier coating tests show that the coating fails by ceramic spallation. Analysis of life data indicates that cyclic thermal loading and thermal exposure play synergistic roles in controlling the spallation life of the coating. A life prediction algorithm has been developed, based on a damage accumulation algorithm that includes both cyclic and time-dependent damage. The cyclic damage is related to the calculated cyclic inelastic strain range in the ceramic coating; the time-dependent damage is related to the oxidation kinetics at the bond-ceramic interface. Cyclic inelastic strain range is calculated using a modified form of the Walker viscoplastic material model. Calculation of the oxidation kinetics is based on traditional oxidation algorithms using experimentally determined parameters. A relation between oxide growth and cycle parameters was derived from test data. The life prediction model was evaluated by predicting the lives of a set of thermal cyclic tests whose heating and cooling rates were significantly greater than those used to correlate the life parameters. Correlation between the actual and predicted spallation lives is within a factor of 3. This is judged to be satisfactory, relative to fatigue life prediction scatter in metals.
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Pilsner, B., R. Hillery, R. McKnight, T. Cook, and M. Hartle. "Thermal barrier coating life prediction model." Surface and Coatings Technology 32, no. 1-4 (November 1987): 305–6. http://dx.doi.org/10.1016/0257-8972(87)90115-0.

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Fu, Zhuo, Xiang Li, Sha Zhang, Hanqing Xiong, Chi Liu, and Kun Li. "Establishment and Verification of Multiaxis Fatigue Life Prediction Model." Scanning 2021 (February 2, 2021): 1–6. http://dx.doi.org/10.1155/2021/8875958.

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A fatigue life prediction model with multiaxis load is proposed. The model introduces a new effective cyclic parameter, equivalent stress on the critical surface, to modify the Suntech model. The new damage parameters are not related to empirical constants, hence more applicable for practical application in engineering. The multiaxis fatigue test was carried out with high-strength aluminum alloy 7075-T651, and the multiaxis fatigue life prediction of the test piece was conducted with the finite element software. The experiment result shows that the model proposed is effective for predicting the fatigue life under multiaxis load.
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Salganik, Matthew J., Ian Lundberg, Alexander T. Kindel, Caitlin E. Ahearn, Khaled Al-Ghoneim, Abdullah Almaatouq, Drew M. Altschul, et al. "Measuring the predictability of life outcomes with a scientific mass collaboration." Proceedings of the National Academy of Sciences 117, no. 15 (March 30, 2020): 8398–403. http://dx.doi.org/10.1073/pnas.1915006117.

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How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences.
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Shangguan, Wen-Bin, Guo-feng Zheng, Tai-Kai Liu, Xiao-Cheng Duan, and Subhash Rakheja. "Prediction of fatigue life of rubber mounts using stress-based damage indexes." Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design and Applications 231, no. 8 (October 6, 2015): 657–73. http://dx.doi.org/10.1177/1464420715608407.

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Prediction of fatigue lives of a rubber mount necessitate formulation of models for estimating fatigue life of the rubber materials used in the mount. Moreover, the prediction accuracy of the model is strongly dependent upon the choice of damage index that are based on different strain, energy or stress measures in the vicinity of critical locations of the rubber mount. In this study, relative performance of models employing different damage indices are evaluated for prediction of fatigue lives of rubber material and a drive-train rubber mount. A combined stress and an effective stress function are proposed as a damage index for predicting fatigue lives of rubber materials and the mounts. Different damage indices, identified from the finite element models of the rubber dumbbell cylindrical specimen are applied for formulations of fatigue life prediction models. The model parameters are identified from the measured data acquired for the rubber dumbbell cylindrical specimen under 31 different uniaxial displacement loads, using least squared error minimization technique. The identified models employing different damage indices are subsequently applied for predicting fatigue lives of rubber mounts under different magnitudes of loads applied along two different directions. The correlations of the predicted lives of the rubber mount from the models employing different damage indices with measured fatigue life data were subsequently investigated for the rubber mount subject to different load conditions. It is shown that the models identified for the rubber material could be effectively used for predicting fatigue lives of the mounts, which are made of same material. The fatigue lives predicted by the models considering either effective stress or combined stress as the damage index correlated with the measured data within a factor of two for the two, suggesting that stress-based damage indices could yield more accurate predictions of fatigue lives of typical mounts.
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Nicholas, T. "Fatigue Life Prediction in Titanium Matrix Composites." Journal of Engineering Materials and Technology 117, no. 4 (October 1, 1995): 440–47. http://dx.doi.org/10.1115/1.2804737.

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Methods used for life prediction of titanium matrix composites under isothermal and thermomechanical (TMF) fatigue are reviewed. Models containing a single parameter are shown to have applicability only under limited conditions. Two models, a dominant damage and a life fraction model, demonstrate predictive capabilities over a broad range of loads, frequencies, temperatures, and TMF parameters. Relationships between the underlying fatigue mechanisms and the individual terms in the models are illustrated.
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Blake, J. W., and H. S. Cheng. "A Surface Pitting Life Model for Spur Gears: Part I—Life Prediction." Journal of Tribology 113, no. 4 (October 1, 1991): 712–18. http://dx.doi.org/10.1115/1.2920683.

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Surface pitting is a major failure mode for gears. Estimation of failure probability and service life are important in gear design. Current techniques give only a pass/fail rating based on semi-empirical methods. A predictive model for estimating service lives and failure probabilities has been developed. This paper discusses the life prediction analysis, which is based on propagation of a surface breaking crack under rolling/sliding contact conditions. The effects of both surface roughness and non-metallic inclusions can be included. While predicted lives are lower than expected, trends observed through parametric variation are consistent with service behavior.
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Hanson, R., D. Allsopp, T. Deng, D. Smith, M. S. A. Bradley, I. M. Hutchings, and M. K. Patel. "A model to predict the life of pneumatic conveyor bends." Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering 216, no. 3 (August 1, 2002): 143–49. http://dx.doi.org/10.1243/095440802320225284.

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A new approach to the prediction of bend lifetime in pneumatic conveyors, subject to erosive wear is described. Mathematical modelling is exploited. Commercial Computational Fluid Dynamics (CFD) software is used for the prediction of air flow and particle tracks, and custom code for the modelling of bend erosion and lifetime prediction. The custom code uses a toroidal geometry, and employs a range of empirical data rather than trying to fit classical erosion models to a particular circumstance. The data used was obtained relatively quickly and easily from a gas-blast erosion tester. A full-scale pneumatic conveying rig was used to validate a sample of the bend lifetime predictions, and the results suggest accuracy of within ±65%, using calibration methods. Finally, the work is distilled into user-friendly interactive software that will make erosion lifetime predictions for a wide range of bends under varying conveying conditions. This could be a valuable tool for the pneumatic conveyor design or maintenance engineer.
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Lee, Jun Youn, and Soon Bok Lee. "GSW0309 Development of a creep-fatigue life prediction model for type 316L stainless steels." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2003.2 (2003): _GSW0309–1—_GSW0309–5. http://dx.doi.org/10.1299/jsmeatem.2003.2._gsw0309-1.

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Dissertations / Theses on the topic "Life Prediction Model"

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Mishra, Madhav. "Model-based Prognostics for Prediction of Remaining Useful Life." Licentiate thesis, Luleå tekniska universitet, Drift, underhåll och akustik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-17263.

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Prognostics and healthmanagement (PHM) is an engineering discipline that aims to maintain the systembehaviour and function, and assure the mission success, safety andeffectiveness. Health management using a proper condition-based maintenance (CBM)deployment is a worldwide accepted technique and has grown very popular in manyindustries over the past decades. These techniques are relevant in environmentswhere the prediction of a failure and the prevention and mitigation of itsconsequences increase the profit and safety of the facilities concerned.Prognosis is the most critical part of this process and is nowadays recognizedas a key feature in maintenance strategies, since estimation of the remaininguseful life (RUL) is essential.PHM can provide a stateassessment of the future health of systems or components, e.g. when a degradedstate has been found. Using this technology, one can estimate how long it willtake before the equipment will reach a failure threshold, in future operatingconditions and future environmental conditions. This thesis focuses especiallyon physics-based prognostic approaches, which depend on a fundamentalunderstanding of the physical system in order to develop condition monitoringtechniques and to predict the RUL.The overall research objective of thework performed for this thesis has been to improve the accuracy and precisionof RUL predictions. The research hypothesis is that fusing the output of morethan one method will improve the accuracy and precision of the RUL estimation,by developing a new approach to prognostics that combines different remaininglife estimators and physics-based and data-driven methods. There are two waysof acquiring data for data-driven models, namely measurements of real systemsand syntactic data generation from simulations. The thesis deals with two casestudies, the first of which concerns the generation of synthetic data andindirect measurement of dynamic bearing loads and was performed atBillerudKorsäs paper mill at Karlsborg in Sweden. In this study the behaviourof a roller in a paper machine was analysed using the finite element method(FEM). The FEM model is a step towards the possibility of generating syntheticdata on different failure modes, and the possibility of estimating crucialparameters like dynamic bearing forces by combining real vibration measurementswith the FEM model. The second case study deals with the development ofprognostic methods for battery discharge estimation for Mars-based rovers. Herephysical models and measurement data were used in the prognostic development insuch a way that the degradation behaviour of the battery could be modelled andsimulated in order to predict the life-length. A particle filter turned out tobe the method of choice in performing the state assessment and predicting thefuture degradation. The method was then applied to a case study of batteriesthat provide power to the rover.
Godkänd; 2015; 20151116 (madmis); Nedanstående person kommer att hålla licentiatseminarium för avläggande av teknologie licentiatexamen. Namn: Madhav Mishra Ämne: Drift och underhållsteknik/Operation and Maintenance Engineering Uppsats: Model-based Prognostics for Prediction of Remaining Useful Life Examinator: Professor Uday Kumar Institutionen för samhällsbyggnad och naturresurser Avdelning Drift, underhåll och akustik Luleå tekniska universitet Diskutant: Accos. Professor Jyoti Kumar Sinha University of Manchester, Aerospace and Civil Engineering, Manchester Tid: Torsdag 17 december 2015 kl 10.00 Plats: F1031, Luleå tekniska universitet
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Huynh, Daniel Duc Cong. "Next generation probabilistic prediction model for submarine propulsion shaft life." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/118664.

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Thesis: Nav. E., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018.
Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 81-85).
With the development of the U.S. Navy's new COLUMBIA class ballistic missile submarine, the Navy plans to implement a new, longer operational inspection interval for the propulsion shaft system, attempting to double the current 6-year inspection interval for the OHIO class of submarine it is replacing. However, an initial study conducted suggests unsatisfactory levels of failure at this interval due to corrosion fatigue, although with a high level of uncertainty. This thesis addresses that uncertainty by developing a more robust probabilistic model for submarine propulsion shaft reliability in order to more accurately predict probabilities of failure. To improve upon previous efforts, all the components and failure modes of the propulsion shaft were first identified. While the most likely scenario involves water ingress and a wetted propulsion shaft leading to corrosion, pitting, and cracking, other factors that could contribute to shaft failure include damage during installation or failure of cathodic protection systems. Using literature and data gathered during visits to Portsmouth Naval Shipyard (PNSY), these failure modes were approximated with appropriate relationships and statistical distributions and ultimately combined to form a complete probabilistic model of the propulsion shaft system, including all the expected components and the best physics available. Additionally, while this model was designed with extension to the COLUMBIA class of submarine in mind, it can be tailored and easily modified to apply to a broad range of shafting systems, including other classes of submarines, conventional surface ships, and even offshore platforms. The GoldSim program was used as the vehicle for the model, with failure probabilities for the submarine shaft predicted using Monte Carlo simulations. To calibrate the model, outputs from the probabilistic model were compared against hypothetical shaft inspection data, adjusting distributions and variables as appropriate to match target values. While the model used the OHIO class submarine as its baseline, it is expected that the new COLUMBIA class shafting system will use similar materials and have a similar configuration. These inspections have typically taken place at around the 6-year operational interval, but the calibrated model can be used to predict propulsion shaft failures at a range of inspection intervals.
by Daniel Duc Cong Huynh.
Nav. E.
S.M.
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Yu, Jianxiong. "Pavement Service Life Estimation And Condition Prediction." See Full Text at OhioLINK ETD Center (Requires Adobe Acrobat Reader for viewing), 2005. http://www.ohiolink.edu/etd/view.cgi?toledo1132896646.

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Dissertation (Ph.D.)--University of Toledo, 2005.
Typescript. "A dissertation [submitted] as partial fulfillment of the requirements of the Doctor of Philosophy degree in Engineering." Bibliography: leaves 69-74.
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Nowicki, Timothy. "Statistical model prediction of fatigue life for diffusion bonded Inconel 600 /." Online version of thesis, 2008. http://hdl.handle.net/1850/7984.

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Grobaski, Thomas. "Preliminary Research for the Development of a Hot Forging Die Life Prediction Model." Ohio University / OhioLINK, 2004. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1102695461.

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Grobaski, Thomas C. "Preliminary research for the development of a hot forging die life prediction model." Ohio : Ohio University, 2004. http://www.ohiolink.edu/etd/view.cgi?ohiou1102695461.

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Karl, Justin. "Thermomechanical Fatigue Life Prediction of Notched 304 Stainless Steel." Doctoral diss., University of Central Florida, 2013. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5796.

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The behavior of materials as they are subjected to combined thermal and mechanical fatigue loads is an area of research that carries great significance in a number of engineering applications. Power generation, petrochemical, and aerospace industries operate machinery with expensive components that undergo repeated applications of force while simultaneously being exposed to variable temperature working fluids. A case of considerable importance is found in steam turbines, which subject blades to cyclic loads from rotation as well as the passing of heated gases. The complex strain and temperature histories from this type of operation, combined with the geometric profile of the blades, make accurate prediction of service life for such components challenging. Development of a deterministic life prediction model backed by physical data would allow design and operation of turbines with higher efficiency and greater regard for reliability. The majority of thermomechanical fatigue (TMF) life prediction modeling research attempts to correlate basic material property data with simplistic strain and thermal histories. With the exception of very limited cases, these types of efforts have been insufficient and imprecise in their capabilities. Early researchers did not account for the multiple damage mechanisms that operate and interact within a material during TMF loads, and did not adequately address the extent of the relationship between smooth and notched parts. More recent research that adequately recognizes the multivariate nature of TMF develops models that handle life reduction through summation of constitutive damage terms. It is feasible that a modification to the damage-based approach can sufficiently include cases that involve complex geometry. The focus of this research is to construct an experimentally-backed extension of the damage-based approach that improves handling of geometric discontinuities. Smooth and notched specimens of Type 304 stainless steel were subjected to several types of idealized fatigue conditions to assemble a clear picture of the types of damage occurring in a steam turbine and similarly-loaded mechanical systems. These results were compared with a number of idealized TMF experiments, and supplemented by numerical simulation and microscopic observation. A non-uniform damage-summation constitutive model was developed primarily based on physical observations. An additional simplistic model was developed based on phenomenological effect. Findings from this study will be applicable to life prediction efforts in other similar material and load cases.
Ph.D.
Doctorate
Mechanical and Aerospace Engineering
Engineering and Computer Science
Mechanical Engineering
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Singley, Daniel Browne. "Longitudinal prediction of domain satisfaction and global life satisfaction test of a social cognitive model /." College Park, Md. : University of Maryland, 2005. http://hdl.handle.net/1903/2364.

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Thesis (Ph. D.) -- University of Maryland, College Park, 2005.
Thesis research directed by: Dept. of Counseling and Personnel Services. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
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Sarwade, Rohit Foster Winfred A. "Life prediction analysis of a subscale rocket engine combustor using a fluid-thermal-structural model." Auburn, Ala., 2006. http://repo.lib.auburn.edu/2006%20Spring/master's/SARWADE_ROHIT_49.pdf.

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Aikio, Englund Rebecca. "A study of calculation models for fatigue life prediction : A thesis accomplished together with GKN Aerospace." Thesis, Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-67741.

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GKN Aerospace in Trollhättan don’t use the latest ANSYS version and need to upgrade their life analysis models. The aim with this thesis is to do a study of the new models and investigate the times required for the calculations. A flight mission were chosen and this mission together with different life analysis models were run in the GKN in house program Life Analysis System. The results were analyzed and depending on the results additional runs were made or the problem were sent to the life management group at GKN Aerospace. Strain levels versus time were also plotted for the runs with the new models to get a perception where any problems occurs. The results from the model 4.10.149 had no variations between equal runs for the high pressure turbine and the low pressure turbine but there was a variation between the results when equal runs was made with the high pressure compressor. The results from model 4.10.157 and 4.10.124 and 4.10.160 and 4.10.173 had variations in the fatigue life for equal runs. The variations can depend on that the calculations converges to different solutions, the reason for this can depend on the non-linear contact elements. The variation in the results between equal runs occurs when the model uses two or more cores. The time required for the calculation becomes faster with the use of more cores. The longest duration had model 4.10.173 because of the many requirements for the calculations in this model. The problem with the variation in the results is sent to ANSYS.
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Books on the topic "Life Prediction Model"

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Strangman, T. E. Thermal barrier coating life-prediction model development: Second annual report. Phoenix, Ariz: Garrett Turbine Engine Co., 1986.

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Strangman, T. E. Thermal barrier coating life prediction model development: First annual report. Phoenix, AZ: Garrett Turbine Engine Co., 1985.

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Kitamura, Takayuki. Creep life prediction based on stochastic model of microstructurally short crack growth. [Washington, DC]: National Aeronautics and Space Administration, 1988.

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Kitamura, Takayuki. Creep life prediction based on stochastic model of microstructurally short crack growth. [Washington, DC]: National Aeronautics and Space Administration, 1988.

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Radhakrishnan, V. Application of an energy-based life prediction model to bithermal and thermomechanical fatigue. [Washington, DC]: National Aeronautics and Space Administration, 1994.

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Radhakrishnan, V. Application of an energy-based life prediction model to bithermal and thermomechanical fatigue. [Washington, DC]: National Aeronautics and Space Administration, 1994.

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Brenner, Martin J. On-line robust modal stability prediction using wavelet processing. Edwards, Calif: National Aeronautics and Space Administration, Dryden Flight Research Center, 1998.

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Waskan, Jonathan A. Models and cognition: Prediction and explanation in everyday life and in science. Cambridge, Mass: MIT Press, 2006.

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Lifetime prediction and constitutive modelling for creep fatigue interaction. Berlin: Borntraeger, 1996.

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Jones, Steven P. Neural network models of simple mechanical systems illustrating the feasibility of accelerated life testing. [Washington, DC]: National Aeronautics and Space Administration, 1996.

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Book chapters on the topic "Life Prediction Model"

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Nizeyimana, F., and H. Issard. "A Kinetic Model for Predicting Polymeric Neutron Shieldings Lifetime." In Service Life Prediction of Exterior Plastics, 59–70. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06034-7_4.

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Wood, Kurt A., and Ségolène de Robien. "A Quantitative Model for Weathering-induced Mass Loss in Thermoplastic Paints." In Service Life Prediction of Polymeric Materials, 457–74. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-84876-1_30.

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Possan, E., J. J. O. Andrade, D. C. C. Dal Molin, and José Luis Duarte Ribeiro. "Model to Estimate Concrete Carbonation Depth and Service Life Prediction." In Hygrothermal Behaviour and Building Pathologies, 67–97. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-50998-9_4.

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Hu, Changhua, Hongdong Fan, and Zhaoqiang Wang. "Degradation Modeling and Residual Life Prediction Based on Grey Predcition Model." In Residual Life Prediction and Optimal Maintenance Decision for a Piece of Equipment, 213–27. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2267-0_10.

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Vona, Marco, and Benedetto Manganelli. "Economic Life Prediction Model of RC Buildings Based on Fragility Curves." In Computational Science and Its Applications -- ICCSA 2015, 771–81. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-21470-2_56.

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Allen, D. H., A. L. Highsmith, and D. C. Lo. "A Continuum Damage Mechanics Model for Life Prediction of Laminated Composites." In Durability of Polymer Based Composite Systems for Structural Applications, 119–28. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3856-7_7.

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Niu, Wei, Jianping Zhao, Guozhen Wang, and Jiqiang Wang. "Remaining Useful Life Prediction of Aircraft Engine Based on Grey Model." In Lecture Notes in Electrical Engineering, 1125–33. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-5912-6_83.

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Lee, Y. B., H. E. Kim, Y. C. Yoo, and J. H. Park. "Accelerated Life Test Model for Life Prediction of Piston Assemblies in Hydraulic Pump and Motor." In Experimental Mechanics in Nano and Biotechnology, 649–52. Stafa: Trans Tech Publications Ltd., 2006. http://dx.doi.org/10.4028/0-87849-415-4.649.

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Kamde, D. R., B. Kondraivendhan, and S. N. Desai. "Service Life Prediction Model for Reinforced Concrete Structures Due to Chloride Ingress." In Advances in Structural Engineering, 1883–94. New Delhi: Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2187-6_145.

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Song, Bong-Min, Bongtae Han, Avram Bar-Cohen, Rajdeep Sharma, and Mehmet Arik. "Hierarchical Reliability Model for Life Prediction of Actively Cooled LED-Based Luminaire." In MEMS and Nanotechnology, Volume 4, 189–90. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4614-0210-7_27.

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Conference papers on the topic "Life Prediction Model"

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Ahmad, Jalees, Unnikrishnan Santhosh, and Sandra Hoff. "A Metal Matrix Composite Damage and Life Prediction Model." In ASME 1997 International Gas Turbine and Aeroengine Congress and Exhibition. American Society of Mechanical Engineers, 1997. http://dx.doi.org/10.1115/97-gt-445.

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A simple analytical model is derived for the prediction of time dependent deformation and damage response of metal matrix composites under fiber direction loading. The model can be used in conjunction with a number of viscoplastic constitutive models to describe the matrix material behavior. Damage in the form of progressive fiber fractures is incorporated using a mechanistic approach. The criterion for fiber fractures can be based on statistical information on fiber strength. When used in conjunction with a prescribed failure condition for a composite, the model provides a means for predicting composite life under general thermomechanical load conditions. Based on comparison of results with detailed finite element analyses and with laboratory test data, it appears that the simple model provides reasonably accurate predictions.
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van Beek, A. "Validation model for service life prediction of concrete structures." In 2nd International RILEM Workshop on Life Prediction and Aging Management of Concrete Structures. RILEM Publications SARL, 2003. http://dx.doi.org/10.1617/2912143780.025.

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Meier, Susan Manning, David M. Nissley, Keith D. Sheffler, and Thomas A. Cruse. "Thermal Barrier Coating Life Prediction Model Development." In ASME 1991 International Gas Turbine and Aeroengine Congress and Exposition. American Society of Mechanical Engineers, 1991. http://dx.doi.org/10.1115/91-gt-040.

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A thermal barrier coated (TBC) turbine component design system, including an accurate TBC life prediction model, is needed to realize the full potential of available TBC engine performance and/or durability benefits. The objective of this work, which was sponsored in part by NASA under the Hot Section Technology (HOST) Program (Contract NAS3-23944), was to generate a life prediction model for electron beam - physical vapor deposited (EB-PVD) zirconia TBC. Specific results include EB-PVD zirconia mechanical and physical properties, coating adherence strength measurements, interfacial oxide growth characteristics, quantitative cyclic thermal spallation life data, and a spallation life model.
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Xiong, Yanting, Xin Sui, and Ning-fei Wang. "Research on NEPE Propellant Life Prediction Model." In 51st AIAA/SAE/ASEE Joint Propulsion Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2015. http://dx.doi.org/10.2514/6.2015-3872.

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Wang, Hongyan, Xinglin Qi, and Yingwei Wu. "Application of storage life prediction model based on performance degradation distribution in fuze storage life prediction." In 2ND INTERNATIONAL CONFERENCE ON MATERIALS SCIENCE, RESOURCE AND ENVIRONMENTAL ENGINEERING (MSREE 2017). Author(s), 2017. http://dx.doi.org/10.1063/1.5005189.

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Xianxin, Cai, Guo Xiaojun, Wu Chunlai, and Mi Dong. "An EHM System and Its Life Prediction Model." In 2013 5th International Conference on Computational Intelligence and Communication Networks (CICN). IEEE, 2013. http://dx.doi.org/10.1109/cicn.2013.118.

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Tunga, Krishna, Joseph Ross, Kamal Sikka, and Bakul Parikh. "Fatigue Life Prediction Model Development for Decoupling Capacitors." In 2019 IEEE 69th Electronic Components and Technology Conference (ECTC). IEEE, 2019. http://dx.doi.org/10.1109/ectc.2019.00174.

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Wang, Jing, Jiwei Liu, and Bing Liu. "Slope anchor cable life evolution model and prediction." In 2016 2nd Workshop on Advanced Research and Technology in Industry Applications (WARTIA-16). Paris, France: Atlantis Press, 2016. http://dx.doi.org/10.2991/wartia-16.2016.101.

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Mohanty, Subhasish, Aditi Chattopadhyay, and Pedro Peralta. "On-Line Life Prediction of a Structural Hotspot." In ASME 2008 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. ASMEDC, 2008. http://dx.doi.org/10.1115/smasis2008-646.

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Current aerospace practice follows an engineering model based on damage-tolerant reliability whereby structural components are regularly inspected and replaced. Under this practice, engineering designs are generally based on a physics-based fracture mechanics approach, in which the life of structural component is estimated using an assumed initial damaged condition. However, in a real time environment, keeping track of the damage condition of a complex structural component manually is quite difficult and requires automatic damage state estimation. The real-time damage state information can be regularly fed to a prognosis model to update the residual useful life estimation in event of a new prevailing situation. The present paper discusses the use of an adaptive hybrid prognosis model, which estimates the residual useful life of a structural hotspot using information on the damage condition obtained in real time. The hybrid prognosis model has two modules: an off-line prognosis module that forecasts the future damage state, and an on-line state estimation module, which regularly predicts the current damage state and feeds into the off-line module in real time. Both the off-line and on-line modules are probabilistic models and use the concept of Bayesian inference based on input-output mapping through a Gaussian process.
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Chan, K. S., and N. S. Cheruvu. "Field Validation of a TBC Life-Prediction Model for Land-Based Gas Turbines." In ASME Turbo Expo 2010: Power for Land, Sea, and Air. ASMEDC, 2010. http://dx.doi.org/10.1115/gt2010-22226.

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The coating life-prediction model, COATLIFE, was previously developed for estimating the lifetimes of first-stage blades and vanes in land-based power-generation gas turbines on the basis of degradation mechanisms observed in laboratory and field data. For first-stage blades with thermal barrier coatings (TBCs), degradation mechanisms treated in COATLIFE include thermo-mechanical fatigue (TMF), Al depletion due to bond coat oxidation, sintering of voids and microcracks in TBC, and curvature effects. Material constants in COATLIFE were evaluated using laboratory data and subsequently utilized with the model to predict the remaining life of first-stage blades in the field. In the present study, the predictive capabilities of COATLIFE were evaluated against field data obtained from first-stage blades with TBC extracted from land-based power generation gas turbines. The ex-service blades were sectioned to characterize the conditions of the TBC and bond coat after various times of service. For coating characterization, the Al content and volume fraction of the β phase in the bond coat, as well as the extent of oxidation and microcracking in the TBCs and along the TBC/bond coat interface at various locations of the blade were determined. These results were compared against model predictions generated by COATLIFE. Good agreement between the field data and model predictions validates the predictive capabilities of COATLIFE for estimating the oxidation lives for first-stage blades with TBCs.
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Reports on the topic "Life Prediction Model"

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Ding, J. L., K. C. Liu, and C. R. Brinkman. Multiaxial deformation and life prediction model and experimental data for advanced silicon nitride ceramics. Office of Scientific and Technical Information (OSTI), June 1993. http://dx.doi.org/10.2172/10162954.

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Kim, Changmo, Ghazan Khan, Brent Nguyen, and Emily L. Hoang. Development of a Statistical Model to Predict Materials’ Unit Prices for Future Maintenance and Rehabilitation in Highway Life Cycle Cost Analysis. Mineta Transportation Institute, December 2020. http://dx.doi.org/10.31979/mti.2020.1806.

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The main objectives of this study are to investigate the trends in primary pavement materials’ unit price over time and to develop statistical models and guidelines for using predictive unit prices of pavement materials instead of uniform unit prices in life cycle cost analysis (LCCA) for future maintenance and rehabilitation (M&R) projects. Various socio-economic data were collected for the past 20 years (1997–2018) in California, including oil price, population, government expenditure in transportation, vehicle registration, and other key variables, in order to identify factors affecting pavement materials’ unit price. Additionally, the unit price records of the popular pavement materials were categorized by project size (small, medium, large, and extra-large). The critical variables were chosen after identifying their correlations, and the future values of each variable were predicted through time-series analysis. Multiple regression models using selected socio-economic variables were developed to predict the future values of pavement materials’ unit price. A case study was used to compare the results between the uniform unit prices in the current LCCA procedures and the unit prices predicted in this study. In LCCA, long-term prediction involves uncertainties due to unexpected economic trends and industrial demand and supply conditions. Economic recessions and a global pandemic are examples of unexpected events which can have a significant influence on variations in material unit prices and project costs. Nevertheless, the data-driven scientific approach as described in this research reduces risk caused by such uncertainties and enables reasonable predictions for the future. The statistical models developed to predict the future unit prices of the pavement materials through this research can be implemented to enhance the current LCCA procedure and predict more realistic unit prices and project costs for the future M&R activities, thus promoting the most cost-effective alternative in LCCA.
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Przystupa, M. A., and A. K. Vasudevan. Development of the Microstructure Based Stochastic Life Prediction Models. Fort Belvoir, VA: Defense Technical Information Center, January 1993. http://dx.doi.org/10.21236/ada270453.

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Przystupa, Marek A., Jimin Zhang, and Annetta J. Luevano. Development of the Microstructure Based Stochastic Life Prediction Models. Fort Belvoir, VA: Defense Technical Information Center, September 1993. http://dx.doi.org/10.21236/ada269880.

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Przystupa, Marek A., Jimin Zhang, and Annetta J. Luevano. Development of the Microstructure Based Stochastic Life Prediction Models. Fort Belvoir, VA: Defense Technical Information Center, February 1992. http://dx.doi.org/10.21236/ada246447.

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Przystupa, Marek A. Development of the Microstructure Based Stochastic Life Prediction Models. Fort Belvoir, VA: Defense Technical Information Center, June 1991. http://dx.doi.org/10.21236/ada237768.

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Wissink, Andrew, Jude Dylan, Buvana Jayaraman, Beatrice Roget, Vinod Lakshminarayan, Jayanarayanan Sitaraman, Andrew Bauer, James Forsythe, Robert Trigg, and Nicholas Peters. New capabilities in CREATE™-AV Helios Version 11. Engineer Research and Development Center (U.S.), June 2021. http://dx.doi.org/10.21079/11681/40883.

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CREATE™-AV Helios is a high-fidelity coupled CFD/CSD infrastructure developed by the U.S. Dept. of Defense for aeromechanics predictions of rotorcraft. This paper discusses new capabilities added to Helios version 11.0. A new fast-running reduced order aerodynamics option called ROAM has been added to enable faster-turnaround analysis. ROAM is Cartesian-based, employing an actuator line model for the rotor and an immersed boundary model for the fuselage. No near-body grid generation is required and simulations are significantly faster through a combination of larger timesteps and reduced cost per step. ROAM calculations of the JVX tiltrotor configuration give a comparably accurate download prediction to traditional body-fitted calculations with Helios, at 50X less computational cost. The unsteady wake in ROAM is not as well resolved, but wake interactions may be a less critical issue for many design considerations. The second capability discussed is the addition of six-degree-of-freedom capability to model store separation. Helios calculations of a generic wing/store/pylon case with the new 6-DOF capability are found to match identically to calculations with CREATE™-AV Kestrel, a code which has been extensively validated for store separation calculations over the past decade.
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Grendahl, Scott M., Franklyn Kellogg, Hoang Nguyen, and Matthew Motyka. Development of Life Prediction Models for High Strength Steel in a Hydrogen Emitting Environment. Fort Belvoir, VA: Defense Technical Information Center, May 2012. http://dx.doi.org/10.21236/ada562867.

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Seale, Maria, Natàlia Garcia-Reyero, R. Salter, and Alicia Ruvinsky. An epigenetic modeling approach for adaptive prognostics of engineered systems. Engineer Research and Development Center (U.S.), July 2021. http://dx.doi.org/10.21079/11681/41282.

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Prognostics and health management (PHM) frameworks are widely used in engineered systems, such as manufacturing equipment, aircraft, and vehicles, to improve reliability, maintainability, and safety. Prognostic information for impending failures and remaining useful life is essential to inform decision-making by enabling cost versus risk estimates of maintenance actions. These estimates are generally provided by physics-based or data-driven models developed on historical information. Although current models provide some predictive capabilities, the ability to represent individualized dynamic factors that affect system health is limited. To address these shortcomings, we examine the biological phenomenon of epigenetics. Epigenetics provides insight into how environmental factors affect genetic expression in an organism, providing system health information that can be useful for predictions of future state. The means by which environmental factors influence epigenetic modifications leading to observable traits can be correlated to circumstances affecting system health. In this paper, we investigate the general parallels between the biological effects of epigenetic changes on cellular DNA to the influences leading to either system degradation and compromise, or improved system health. We also review a variety of epigenetic computational models and concepts, and present a general modeling framework to support adaptive system prognostics.
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Gaver, Donald P., Patricia A. Jacobs, and I. G. O'Muircheartaigh. Regression Analysis of Hierarchical Poisson-Like Event Rate Data: Super- Population Model Effect on Predictions. Fort Belvoir, VA: Defense Technical Information Center, August 1990. http://dx.doi.org/10.21236/ada230297.

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