Relevant bibliographies by topics / Failure physics

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Failure physics'

Author: Grafiati
Published: 1 February 2025

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Journal articles on the topic "Failure physics"

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Pecht, Michael, and Abhijit Dasgupta. "Physics-of-Failure: An Approach to Reliable Product Development." Journal of the IEST 38, no. 5 (September 1, 1995): 30–34. http://dx.doi.org/10.17764/jiet.2.38.5.y3561m03801h0082.

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Reliability assessments based on physics-of-failure methods incorporate reliability into the design process to prevent parts from failing in service. An understanding of the physics-of-failure is necessary in applications that afford little opportunity for testing, or for reliability growth. This paper presents an overview of physics-of-failure and a case study of the application of physics-of-failure to a specific failure mechanism called conductive filament formation.
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THADURI, ADITHYA, A. K. VERMA, V. GOPIKA, RAJESH GOPINATH, and UDAY KUMAR. "FAILURE MODELING OF CONSTANT FRACTION DISCRIMINATOR USING PHYSICS OF FAILURE APPROACH." International Journal of Reliability, Quality and Safety Engineering 20, no. 03 (June 2013): 1340002. http://dx.doi.org/10.1142/s0218539313400020.

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Due to several advancements in the technology trends in electronics, the reliability prediction by the constant failure methods and standards no longer provide accurate time to failure. The physics of failure methodology provides a detailed insight on the operation, failure point location and causes of failure for old, existing and newly developed components with consideration of failure mechanisms. Since safety is a major criteria for the nuclear industries, the failure modeling of advanced custom made critical components that exists on signal conditioning module are need to be studied with higher confidence. One of the components, constant fraction discriminator, is the critical part at which the failure phenomenon and modeling by regression is studied in this paper using physics of failure methodology.
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Williams, Hollis. "Physics of Brittle Failure during Impact." Physics Teacher 62, no. 7 (October 1, 2024): 575–78. http://dx.doi.org/10.1119/5.0136324.

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SATO, Atsuro, Mikio SAKAI, and Seiichi KOSHIZUKA. "450 Slope Failure in Physics Based CG." Proceedings of The Computational Mechanics Conference 2008.21 (2008): 774–75. http://dx.doi.org/10.1299/jsmecmd.2008.21.774.

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Torigoe, Eugene T., and Gary E. Gladding. "Connecting symbolic difficulties with failure in physics." American Journal of Physics 79, no. 1 (January 2011): 133–40. http://dx.doi.org/10.1119/1.3487941.

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Jiao, Jian, Xinlin De, Zhiwei Chen, and Tingdi Zhao. "Integrated circuit failure analysis and reliability prediction based on physics of failure." Engineering Failure Analysis 104 (October 2019): 714–26. http://dx.doi.org/10.1016/j.engfailanal.2019.05.021.

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Rovelli, C., and I. A. Rybakova. "PHYSICS NEEDS PHILOSOPHY. PHILOSOPHY NEEDS PHYSICS." Metaphysics, no. 3 (December 15, 2021): 36–46. http://dx.doi.org/10.22363/2224-7580-2021-3-36-46.

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Contrary to claims about the irrelevance of philosophy for science, I argue that philosophy has had, and still has, far more influence on physics than is commonly assumed. I maintain that the current anti-philosophical ideology has had damaging effects on the fertility of science. I also suggest that recent important empirical results, such as the detection of the Higgs particle and gravitational waves, and the failure to detect supersymmetry where many expected to find it, question the validity of certain philosophical assumptions common among theoretical physicists, inviting us to engage in a clearer philosophical reflection on scientific method.
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Zhang, Ren Peng, Yi Yong Hu, and Jun Yao. "Reliability Enhancement Test on Undercarriage Signal Light Box." Applied Mechanics and Materials 291-294 (February 2013): 2403–7. http://dx.doi.org/10.4028/www.scientific.net/amm.291-294.2403.

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Based on the theory of failure physics, reliability enhancement test is a test technology of stimulation in order to improve reliability by discovering, researching and curing failure. In this paper, the main factors inducing failure modes of undercarriage light box were analyzed, and the environmental sensitive stresses affecting reliability were determined. The testing program was designed and test profiles were established based on the theory of reliability enhancement test. Additionally, the test results were analyzed based on failures of products in order to carry out improvement measures.
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Qiu, Wenhao, Guangyao Lian, Mingxi Xue, and Kaoli Huang. "Physics of failure-based failure mode, effects, and criticality analysis for Integrated Circuits." Systems Engineering 21, no. 6 (June 25, 2018): 511–19. http://dx.doi.org/10.1002/sys.21451.

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Osterman, M. D. "A Physics of Failure Approach to Component Placement." Journal of Electronic Packaging 114, no. 3 (September 1, 1992): 305–9. http://dx.doi.org/10.1115/1.2905455.

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Traditionally, placement techniques have focused on improving rotability based on minimizing the total wire length between interconnected components. However, electronic card assembly (ECA) reliability, which is measured in terms of time to failure, cycles to failure, or the hazard rates of the individual components, the interconnections, and the PWB, is also affected by component placement. This paper discusses component placement for reliability based on a failure model which incorporates component temperature, a base operating temperature, a threshold temperature, and change in temperature. Placement procedures are developed so as to minimize the time to failure or the total hazard rate of the components on a PWB utilizing a forced convection cooling.
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Dissertations / Theses on the topic "Failure physics"

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Kodger, Thomas Edward. "Mechanical Failure in Colloidal Gels." Thesis, Harvard University, 2015. http://nrs.harvard.edu/urn-3:HUL.InstRepos:14226100.

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When colloidal particles in a dispersion are made attractive, they aggregate into fractal clusters which grow to form a space-spanning network, or gel, even at low volume fractions. These gels are crucial to the rheological behavior of many personal care, food products and dispersion-based paints. The mechanical stability of these products relies on the stability of the colloidal gel network which acts as a scaffold to provide these products with desired mechanical properties and to prevent gravitational sedimentation of the dispersed components. Understanding the mechanical stability of such colloidal gels is thus of crucial importance to predict and control the properties of many soft solids. Once a colloidal gel forms, the heterogeneous structure bonded through weak physical interactions, is immediately subject to body forces, such as gravity, surface forces, such as adhesion to a container walls and shear forces; the interplay of these forces acting on the gel determines its stability. Even in the absence of external stresses, colloidal gels undergo internal rearrangements within the network that may cause the network structure to evolve gradually, in processes known as aging or coarsening or fail catastrophically, in a mechanical instability known as syneresis. Studying gel stability in the laboratory requires model colloidal system which may be tuned to eliminate these body or endogenous forces systematically. Using existing chemistry, I developed several systems to study delayed yielding by eliminating gravitational stresses through density matching and cyclic heating to induce attraction; and to study syneresis by eliminating adhesion to the container walls, altering the contact forces between colloids, and again, inducing gelation through heating. These results elucidate the varied yet concomitant mechanisms by which colloidal gels may locally or globally yield, but then reform due to the nature of the physical, or non-covalent, interactions which form them.
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Thaduri, Adithya. "Physics-of-failure based performance modeling of critical electronic components." Doctoral thesis, Luleå tekniska universitet, Drift, underhåll och akustik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-16877.

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Reliability prediction of the electronic components used in industrial safety systems requires high accuracy and compatibility with the working environment. The traditional reliability prediction methods that draw on standard handbooks such as MIL-HDBK 217F, Telcordia, PRISM etc., are not appropriate to determine the reliability indices of these components. For one thing, technology is constantly advancing; for another, the empirical data do not always match the actual working environment.The newest reliability prediction methodology, the physics-of-failure (PoF), emphasizes the root cause of failure, failure analysis, and failure mechanisms based on the analysis of parameter characteristics. It involves a focused examination of failure point locations, considering the fabrication technology, process, materials and circuit layout obtained from the manufacturer. This methodology is capable of providing recommendations for the increased reliability of components using intuitive analysis.However, there is a limitation: it is sometimes difficult to obtain manufacturer’s details for failure analysis and quality information. Several statistical and probability modeling methods can be performed on the experimental data of these components to measure the time to failure. These experiments can be conducted using the accelerated-testing of dominant stress parameters such as Voltage, Current, Temperature, Radiation etc.In this thesis, the combination of qualitative data from PoF approach and quantitative data from the statistical analysis is used to create a modified physics-of-failure approach. This methodology overcomes the limitations of the standard PoF approach as it involves detailed analysis of stress factors, data modeling and prediction. A decision support system is created to select the best option from failure data models, failure mechanisms, failure criteria and other factors to ensure a growth in reliability.In this study, the critical electronic components used in certain safety systems from different technologies are chosen for reliability prediction: Optocoupler, Constant Fraction Discriminator, BJT Transistor, Voltage Comparator, Voltage Follower and Instrumentation amplifier. The study finds that the modified physics-of-failure methodology provides more accurate reliability indices than the traditional approaches using field data. Stress based degradation models are developed for each of the components. The modified PoF models developed using Response Surface Regression and Support Vector Machine (SVM) show better performance.
Godkänd; 2013; 20130813 (aditha); Tillkännagivande disputation 2013-08-23 Nedanstående person kommer att disputera för avläggande av teknologie doktorsexamen. Namn: Adithya Thaduri Ämne: Drift och underhållsteknik/Operation and Maintenance Avhandling: Physics-of-Failure Based Performance Modeling of Critical Electronic Components Opponent: Professor Hoang Pham, Dept of Industrial and Systems Engineering, Rutgers, The State University of New Jersey, USA Ordförande: Professor Uday Kumar, Institutionen för samhällsbyggnad och naturresurser, Luleå tekniska universitet Tid: Torsdag den 12 september 2013, kl 10.00 Plats: F1031, Luleå tekniska universitet
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Smith, Christopher John. "Holistic physics-of-failure approach to wind turbine power converter reliability." Thesis, Durham University, 2018. http://etheses.dur.ac.uk/12567/.

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As the cost of wind energy becomes of increasing importance to the global surge of clean and green energy sources, the reliability-critical power converter is a target for vast improvements in availability through dedicated research. To this end, this thesis concentrates on providing a new holistic approach to converter reliability research to facilitate reliability increasing, cost reducing innovations unique to the wind industry. This holistic approach combines both computational and physical experimentation to provide a test bench for detailed reliability analysis of the converter power modules under the unique operating conditions of the wind turbine. The computational models include a detailed permanent magnet synchronous generator wind turbine with a power loss and thermal model representing the machine side converter power module response to varying wind turbine conditions. The supporting experimental test rig consists of an inexpensive, precise and extremely fast temperature measurement approach using a PbSe photoconductive infra-red sensor unique in the wind turbine reliability literature. This is used to measure spot temperatures on a modified power module to determine the junction temperature swings experienced during current cycling. A number of key conclusions have been made from this holistic approach. -Physics-of-failure analysis (and indeed any wind turbine power converter based reliability analysis) requires realistic wind speed data as the temporal changes in wind speed have a significant impact on the thermal loading on the devices. -The use of drive train modelling showed that the current throughput of the power converter is decoupled from the incoming wind speed due to drive train dynamics and control. Therefore, the power converter loading cannot be directly derived from the wind speed input without this modelling. -The minimum wind speed data frequency required for sufficiently accurate temperature profiles was determined, and the use of SCADA data for physics-of failure reliability studies was subsequently shown to be entirely inadequate. -The experimental emulation of the power converter validated a number of the aspects of the simulation work including the increase in temperature with wind speed and the detectability of temperature variations due to the current's fundamental frequency. Most importantly, this holistic approach provides an ideal test bench for optimising power converter designs for wind turbine, or for other industries with stochastic loading, conditions whilst maintaining or exceeding present reliability levels to reduce wind turbine's cost of energy, and therefore, society.
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Gu, Jie. "Prognostics of solder joint reliability under vibration loading using physics of failure approach." College Park, Md.: University of Maryland, 2009. http://hdl.handle.net/1903/9266.

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Thesis (Ph. D.) -- University of Maryland, College Park, 2009.
Thesis research directed by: Dept. of Mechanical Engineering. 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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Qin, Jin. "A new physics-of-failure based VLSI circuits reliability simulation and prediction methodology." College Park, Md. : University of Maryland, 2007. http://hdl.handle.net/1903/7410.

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Thesis (Ph. D.) -- University of Maryland, College Park, 2007.
Thesis research directed by: Reliability Engineering. 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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Xin, Xudong. "An analytical and numerical analysis of dynamic failure based on the multi-physics involved /." free to MU campus, to others for purchase, 2001. http://wwwlib.umi.com/cr/mo/fullcit?p3025668.

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Siddique, Shahnewaz. "Failure mechanisms of complex systems." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/51831.

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Understanding the behavior of complex, large-scale, interconnected systems in a rigorous and structured manner is one of the most pressing scientific and technological challenges of current times. These systems include, among many others, transportation and communications systems, smart grids and power grids, financial markets etc. Failures of these systems have potentially enormous social, environmental and financial costs. In this work, we investigate the failure mechanisms of load-sharing complex systems. The systems are composed of multiple nodes or components whose failures are determined based on the interaction of their respective strengths and loads (or capacity and demand respectively) as well as the ability of a component to share its load with its neighbors when needed. Each component possesses a specific strength (capacity) and can be in one of three states: failed, damaged or functioning normally. The states are determined based on the load (demand) on the component. We focus on two distinct mechanisms to model the interaction between components strengths and loads. The first, a Loss of Strength (LOS) model and the second, a Customer Service (CS) model. We implement both models on lattice and scale-free graph network topologies. The failure mechanisms of these two models demonstrate temporal scaling phenomena, phase transitions and multiple distinct failure modes excited by extremal dynamics. We find that the resiliency of these models is sensitive to the underlying network topology. For critical ranges of parameters the models demonstrate power law and exponential failure patterns. We find that the failure mechanisms of these models have parallels to failure mechanisms of critical infrastructure systems such as congestion in transportation networks, cascading failure in electrical power grids, creep-rupture in composite structures, and draw-downs in financial markets. Based on the different variants of failure, strategies for mitigating and postponing failure in these critical infrastructure systems can be formulated.
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Hulman, Andrea. "Breaking Glass: Exploring the Relationship Between Kinetic Energy and Radial Fracturing in Plate Glass." Scholarship @ Claremont, 2012. http://scholarship.claremont.edu/scripps_theses/95.

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When glass breaks from the impact of an object, it exhibits a distinctive shattering pattern comprised of two different regions. This pattern was investigated using experimental impacts and predicted using Young’s Modulus. Results were not as expected, and it is likely that there exists error in some measurements. Further investigation of this topic is recommended.
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Starkey, Carl Alan. "Analysis of the Failure Modes of Twisted Fiber Structures." Marietta College Honors Theses / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=marhonors1210352501.

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Petel, Oren E. "A study of the failure mechanism of detonations in homogeneous and heterogeneous explosives /." Thesis, McGill University, 2006. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=99530.

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The present study measured the critical diameter and critical thickness of a variety of explosives. The explosives tested included two "unstable" homogeneous explosives (nitromethane and a nitromethane/nitroethane blend); a model heterogeneous explosive consisting of a packed bed of glass beads (Φ ~ 80 μm) saturated with the homogeneous nitromethane/nitroethane blend; and a commercial heterogeneous explosive, Apex Elite(TM). The comparison of the critical diameter and thickness of an explosive is used to identify the dominant propagation and failure mechanisms of the various explosives. The ratio of critical diameter to critical thickness for nitromethane, the nitromethane/nitroethane blend, the beaded heterogeneous explosive, and Apex Elite(TM) were found to be 3.2 +/- 0.6, 3.6 +/- 0.4, 2.3 +/- 0.1, and 3.5 +/- 1.2 respectively. According to accepted detonation failure theories, the energy losses associated with detonation front curvature are responsible for detonation failure. The curvature model, which is elaborated upon in the present work, leads to a predicted critical diameter to critical thickness ratio of exactly 2. The present study has shown that the only explosive which follows the behaviour predicted by curvature failure models is the beaded heterogeneous explosive, which exhibits fine scale heterogeneities. This seems to indicate that unstable liquid explosives and heterogeneous explosives with large scale heterogeneities do not fail simply due to the wave front curvature, but rather by a local mechanism of failure and reinitiation which dominates the detonation propagation.
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Books on the topic "Failure physics"

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Modarres, Mohammad, Mehdi Amiri, and Christopher Jackson. Probabilistic Physics of Failure Approach to Reliability. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2017. http://dx.doi.org/10.1002/9781119388692.

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McPherson, J. W. Reliability physics and engineering: Time-to-failure modeling. New York: Springer, 2010.

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McPherson, J. W. Reliability Physics and Engineering: Time-To-Failure Modeling. 2nd ed. Heidelberg: Springer International Publishing, 2013.

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Rossmanith, H. P. Dynamic Failure of Materials: Theory, Experiments and Numerics. Dordrecht: Springer Netherlands, 1991.

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Munz, Dietrich. Ceramics: Mechanical Properties, Failure Behaviour, Materials Selection. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999.

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Brzesowsky, Rolf. Micromechanics of sand grain failure and sand compaction. [Utrecht: Faculteit Aardwetenschappen, Universiteit Utrecht, 1996.

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J, Bean Alan, Darzi Kent, University of Alabama in Huntsville. Dept. of Mechanical Engineering., George C. Marshall Space Flight Center., and United States. National Aeronautics and Space Administration. Scientific and Technical Information Division., eds. Hypervelocity impact physics. [Washington, D.C.]: National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Division, 1991.

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Sih, G. C. Plasticity and failure behavior of solids: Memorial volume dedicated to the late Professor Yuriy Nickolaevich Rabotnov. Dordrecht: Springer Netherlands, 1990.

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Sih, G. C. Mechanics of Fracture Initiation and Propagation: Surface and volume energy density applied as failure criterion. Dordrecht: Springer Netherlands, 1991.

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B, Thompson R., and United States. Dept. of Energy. Division of Materials Science., eds. Mechanics and physics of crack growth: Application to life prediction. London: Elsevier Applied Science, 1988.

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Book chapters on the topic "Failure physics"

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Czichos, Horst. "Physics of Failure." In Handbook of Technical Diagnostics, 23–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-25850-3_3.

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Jata, Kumar V., and Triplicane A. Parthasarathy. "Physics of Failure." In System Health Management, 199–217. Chichester, UK: John Wiley & Sons, Ltd, 2011. http://dx.doi.org/10.1002/9781119994053.ch12.

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McPherson, J. W. "Failure Rate Modeling." In Reliability Physics and Engineering, 109–24. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93683-3_8.

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McPherson, J. W. "Failure Rate Modeling." In Reliability Physics and Engineering, 75–89. Heidelberg: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00122-7_7.

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McPherson, J. W. "Failure Rate Modeling." In Reliability Physics and Engineering, 79–93. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-6348-2_7.

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McPherson, J. W. "Ramp-to-Failure Testing." In Reliability Physics and Engineering, 149–64. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93683-3_11.

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McPherson, J. W. "Time-to-Failure Modeling." In Reliability Physics and Engineering, 67–80. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93683-3_5.

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McPherson, J. W. "Time-to-Failure Statistics." In Reliability Physics and Engineering, 93–107. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93683-3_7.

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McPherson, J. W. "Ramp-to-Failure Testing." In Reliability Physics and Engineering, 117–32. Heidelberg: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00122-7_10.

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McPherson, J. W. "Time-to-Failure Modeling." In Reliability Physics and Engineering, 37–49. Heidelberg: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00122-7_4.

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Conference papers on the topic "Failure physics"

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Perez, Rigo. "Thermal Physics of Failure." In Reliability, Maintainability, Supportability & Logistics (Rmsl) Conference & Workshop. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1996. http://dx.doi.org/10.4271/961266.

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Perez, Rigo. "Dynamic Physics of Failure." In Reliability, Maintainability, Supportability & Logistics (Rmsl) Conference & Workshop. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1996. http://dx.doi.org/10.4271/961267.

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Bunis, C. B. "Physics of failure - the basic materials science behind failures." In GaAs Reliability Workshop. Proceedings. IEEE, 2001. http://dx.doi.org/10.1109/gaasrw.2001.995733.

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Koch, Tim, Wayne Richliug, John Whitlock, and Dave Hall. "A Bond Failure Mechanism." In 24th International Reliability Physics Symposium. IEEE, 1986. http://dx.doi.org/10.1109/irps.1986.362112.

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Drake, Gary S. "Engineering design analysis (Physics of Failure)." In 2010 Annual Reliability and Maintainability Symposium (RAMS). IEEE, 2010. http://dx.doi.org/10.1109/rams.2010.5448049.

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Raghavan, Nagarajan. "Tutorial: Physics of failure based prognostics." In 2017 Prognostics and System Health Management Conference (PHM-Harbin). IEEE, 2017. http://dx.doi.org/10.1109/phm.2017.8079097.

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Wang, Frank Fan, Clyde Jelinek, and Mary Davis. "Physics-of-Failure HALT Result Assessment." In ASME 2003 International Mechanical Engineering Congress and Exposition. ASMEDC, 2003. http://dx.doi.org/10.1115/imece2003-41089.

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Highly Accelerated Life Test (HALT) uses stimulation to identify weak points in a design thus to improve the quality. When used with proper assessment, HALT is a very useful product development tool. However, HALT without proper assessment is no better than not testing at all. Scientific assessment of the HALT result is critical to successful use of HALT. The following paper will discuss using a physics of failure approach to assessing HALT results. Discussions cover limitations of HALT, comparisons of HALT to traditional testing, and the roles of design specifications and product mechanical characteristics in HALT. Examples of HALT failures and HALT result assessments are also presented.
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Tse, P. K., J. C. Gammel, D. G. Schimmel, W. H. Becker, J. P. Ballantyne, and T. J. Riley. "Failure Analysis and Failure Mechanisms of High Voltage (530V) Gated Diode Crosspoint Arrays." In 24th International Reliability Physics Symposium. IEEE, 1986. http://dx.doi.org/10.1109/irps.1986.362121.

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Towner, Janet M. "Electromigration-Induced Short Circuit Failure." In 23rd International Reliability Physics Symposium. IEEE, 1985. http://dx.doi.org/10.1109/irps.1985.362080.

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Brooke, Laura. "Pulsed Current Electromigration Failure Model." In 25th International Reliability Physics Symposium. IEEE, 1987. http://dx.doi.org/10.1109/irps.1987.362169.

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Reports on the topic "Failure physics"

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Shockey, Donald A., Jeffrey W. Simons, Takao Kobayashi, and Dennis Grishin. Microstructural Failure Physics for Structural Failure Prognosis and Diagnosis. Fort Belvoir, VA: Defense Technical Information Center, December 2003. http://dx.doi.org/10.21236/ada427340.

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Kacprzynski, Gregory J., Michael J. Roemer, Girish Modgil, Andrea Palladino, and Kenneth Maynard. Enhancement of Physics-of-Failure Prognostic Models with System Level Features. Fort Belvoir, VA: Defense Technical Information Center, January 2002. http://dx.doi.org/10.21236/ada408967.

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Knodel, Mallory. A Comparison of the Availability and Failure Modes of the BaBar Superconducting Solenoid with Similar Magnets at Other High Energy Physics Laboratories. Office of Scientific and Technical Information (OSTI), September 2003. http://dx.doi.org/10.2172/815644.

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Ravichandran, Guruswami. Proceedings of a Symposium on the Dynamic Deformation and Failure of Materials (Journal of the Mechanics and Physics of Solids. Volume 46, Number 10). Fort Belvoir, VA: Defense Technical Information Center, May 2000. http://dx.doi.org/10.21236/ada378420.

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Morsy, Amr, and Islam Ebo. Development of Physics-Based Deterioration Models for Reinforced Soil Retaining Structures. Mineta Transportation Institute, 2025. https://doi.org/10.31979/mti.2024.2360.

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Reinforced soil walls are key earth retention features in the transportation infrastructure. They are used to support and retain soil in a wide variety of crucial structures, such as highways, bridges, and railways, to ensure stability. They also provide solutions for constructing embankments and slopes in constrained spaces, allowing for efficient land use and improved infrastructure planning. This study used advanced numerical modeling to improve the understanding of the behavior and long-term performance of the aging reinforced soil walls from the 1970s for asset management purposes. An asset-scale model was created to simulate the effects of weather on these walls. The model included a system to track how moisture-driven corrosion affects wall stability and performance over time. The model outputs provide implications on the wall progressive deterioration over time and estimates for the wall remaining service life. Unlike newer wall generations constructed with strict specifications that limit fill corrosivity, early wall generations may maintain high levels of moisture for prolonged periods that can significantly increase corrosion rates. Accordingly, it is recommended that fill moisture monitoring be added to asset management measures for early generation walls that could have been constructed with highly corrosive or poorly drainable fills. The results of this study indicate that even though corrosion rates vary with changes in fill moisture, the overall loss in reinforcement thickness happens at a steady rate, showing a linear relationship between cumulative corrosion and time. The results also indicate that 25% fluctuation in fill moisture has no to little effect on the cumulative corrosion, and that the average fill moisture can be used to predict an approximate long-term cumulative corrosion. Thus, it is recommended to use one year of seasonal climate data for a specific location to estimate the annual variation in fill moisture. This can predict the yearly corrosion of reinforcements, which can then be multiplied by the number of service years to estimate long-term cumulative corrosion. Finally, an asset-scale performance model based on performance-requirement failure framework was developed using the outputs of the asset-scale numerical model. These performance models can inform decisions about critical transportation infrastructure maintenance, repair, or replacement strategies, and optimizing resource allocation.
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6

Rundle, John B., and William Klein. Collaborative Research. Damage and Burst Dynamics in Failure of Complex Geomaterials. A Statistical Physics Approach to Understanding the Complex Emergent Dynamics in Near Mean-Field Geological Materials. Office of Scientific and Technical Information (OSTI), September 2015. http://dx.doi.org/10.2172/1221851.

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Francis, Andrew, Chas Jandu, and Mike Taylor. PR-408-124500-R01 Mechanical Damage Instantaneous Failure Model Numerical Simulation of Physical Tests. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), March 2013. http://dx.doi.org/10.55274/r0010819.

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The overall objective was to develop two models for determining the effect of mechanical damage on the structural integrity of buried pipelines. The models that are to be developed are the instantaneous failure model (MD4-3) and the delayed failure model (MD4-4). The subject of this report is part of the work that has been undertaken in support of the development of the instantaneous failure model which is being undertaken within the remit of MD4-3. The overall objective of MD4-3 to produce a closed form expression that will be used as: (i) A Limit State Function in structural reliability and risk assessment methodologies and associated software. (ii) A means of determining the safety margin associated with known existing damage to establish whether immediate repair is required (iii) An initial condition for the delayed failure model (MD4-4) which is being developed separately. The objective of this report is to present the outcomes of detailed numerical simulation of physical tests that have been performed as part of MD4-1. The development is progressing based on a combination of physical testing and numerical simulation and analysis. The objective of this report is to present the outcomes of detailed numerical simulation of physical tests that have been performed as part of MD4-1.
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Giannoulakis, Stylianos, and Arrigo Beretta. PR-471-18210-R01 Pump Failure and Performance Degradation Prediction. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), September 2020. http://dx.doi.org/10.55274/r0011801.

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Sulzer Pumps Incorporation is performing fundamental research for developing an early pump failure prediction method, for better supporting its customers. Target is to protect critical equipment and reduce unplanned outages. This effort focuses on combining modern machine learning anomaly detection techniques with pump physical know-how. The developed approach was tested with real life failure datasets, provided by Pipeline Research Council International members. In addition, a performance degradation technique was inspired by anomaly detection learnings and tested at this project.
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Phillips, Paul. The Adoption of Digital Twins in Integrated Vehicle Health Management. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, October 2023. http://dx.doi.org/10.4271/epr2023024.

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<div class="section abstract"><div class="htmlview paragraph">To many, a digital twin offers “functionality,” or the ability to virtually rerun events that have happened on the real system and the ability to simulate future performance. However, this requires models based on the physics of the system to be built into the digital twin, links to data from sensors on the real live system, and sophisticated algorithms incorporating artificial intelligence (AI) and machine learning (ML). All of this can be used for integrated vehicle health management (IVHM) decisions, such as determining future failure, root cause analysis, and optimized energy performance. All of these can be used to make decisions to optimize the operation of an aircraft—these may even extend into safety-based decisions.</div><div class="htmlview paragraph"><b>The Adoption of Digital Twins in Integrated Vehicle Health Management</b>, however, still has a range of unsettled topics that cover technological reliability, data security and ownership, user presentation and interfaces, as well as certification of the digital twin’s system mechanics (i.e., AI, ML) for use in safety-critical applications.</div><div class="htmlview paragraph"><a href="https://www.sae.org/publications/edge-research-reports" target="_blank">Click here to access the full SAE EDGE</a><sup>TM</sup><a href="https://www.sae.org/publications/edge-research-reports" target="_blank"> Research Report portfolio.</a></div></div>
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Unknown, Author. WINMOP-R03 Performance of Offshore Pipelines. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), June 2003. http://dx.doi.org/10.55274/r0011744.

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The objective of the project was to validate existing pipeline integrity prediction models through field testing multiple pipelines, validate the performance of in-line instrumentation through smart pig runs, and finally, to assess the actual integrity of aging damaged and defective pipelines. The objectives were accomplished by the testing of aging out-of-service lines using "smart pigs", followed by hydrotesting of the lines to failure, recovery of the failed sections, and determination of the pipeline characteristics in the vicinity of the failed sections (failure analysis). One objective of the project was to validate the dented, gouged, and corroded pipeline burst strength prediction models currently in existence, such as ASME B31-G, R-Streng, and DNV 99 for pipelines. Another model was being developed as a joint international project sponsored by the U. S. Minerals Management Service, Petroleos Mexicanos (PEMEX), and Instituto Mexicano del Petroleo (IMP) titled RAM PIPE REQUAL and an associated JIP identified as PIMPIS (Pipeline Inspection, Maintenance, and Performance Information System), this would be tested and validated as well. The validation was provided by hydrotesting in-situ pipelines to failure. Sustained and rapidly applied hydro-pressures were used to investigate the effects of delayed and dynamic pressure related failures. After testing, the pipelines were scheduled for decommissioning; with the failed sections located, and brought to the laboratory for testing and analysis. Class A predictions were made before the pipelines were hydrotested to failure based on results from in-line instrumentation (instrumented) and from knowledge of the pipeline products and other characteristics (not instrumented). Based on the results from the testing, the analytical models were to be revised to provide improved agreement between the measured and predicted burst pressures. Since the pipelines were inspected with smart pigs before the hydro-tests, it was possible to compare the smart-pig data gathered during pig runs to the actual condition of the pipeline. This was accomplished by recovering sections of the pipeline that were identified by the pig as having pits or metal-loss areas. Reviewed pipeline decommissioning inventory and selected a pipeline candidate. The specific scope of work included: � Selected pipelines for testing. � Conducted field tests with an instrumented pig to determine pipeline denting, gouging and corrosion conditions. � Used existing analytical models to determine burst strength for both instrumented and non-instrumented pipelines. � Hydrotested the selected pipelines to failure (sustained and rapidly applied pressures). � Located and retrieve failed sections and other sections identified as problem spots by the "smart-pig." � Compared "smart pig" data to actual pipeline condition. � Analyzed the failed sections to determine their physical and material characteristics. � Revised the analytical models to provide improved agreements between predicted and measured burst pressures.
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