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Modelling and Estimation of Damage in Structures is a comprehensiveguide to solving the type of modelling and estimation problems associated with the physics of structural damage. * Provides a model-based approach to damage identification * Presents an in-depth treatment of probability theory and random processes * Covers both theory and algorithms for implementing maximum likelihood and Bayesian estimation approaches * Includes experimental examples of all detection and identification approaches * Provides a clear means by which acquired data can be used to make decisions regarding maintenance and usage of a structure

A comprehensive guide to the application and processing of condition-based data to produce prognostic estimates of functional health and life. Prognostics and Health Management provides an authoritative guide for an understanding of the rationale and methodologies of a practical approach for improving system reliability using conditioned-based data (CBD) to the monitoring and management of health of systems. This proven approach uses electronic signatures extracted from conditioned-based electrical signals, including those representing physical components, and employs processing methods that include data fusion and transformation, domain transformation, and normalization, canonicalization and signal-level translation to support the determination of predictive diagnostics and prognostics. Written by noted experts in the field, Prognostics and Health Management clearly describes how to extract signatures from conditioned-based data using conditioning methods such as data fusion and transformation, domain transformation, data type transformation and indirect and differential comparison. This important resource: Integrates data collecting, mathematical modelling and reliability prediction in one volume Contains numerical examples and problems with solutions that help with an understanding of the algorithmic elements and processes Presents information from a panel of experts on the topic Follows prognostics based on statistical modelling, reliability modelling and usage modelling methods Written for system engineers working in critical process industries and automotive and aerospace designers, Prognostics and Health Management offers a guide to the application of condition-based data to produce signatures for input to predictive algorithms to produce prognostic estimates of functional health and life.

A comprehensive guide to the application and processing of condition-based data to produce prognostic estimates of functional health and life. Prognostics and Health Management provides an authoritative guide for an understanding of the rationale and methodologies of a practical approach for improving system reliability using conditioned-based data (CBD) to the monitoring and management of health of systems. This proven approach uses electronic signatures extracted from conditioned-based electrical signals, including those representing physical components, and employs processing methods that include data fusion and transformation, domain transformation, and normalization, canonicalization and signal-level translation to support the determination of predictive diagnostics and prognostics. Written by noted experts in the field, Prognostics and Health Management clearly describes how to extract signatures from conditioned-based data using conditioning methods such as data fusion and transformation, domain transformation, data type transformation and indirect and differential comparison. This important resource: Integrates data collecting, mathematical modelling and reliability prediction in one volume Contains numerical examples and problems with solutions that help with an understanding of the algorithmic elements and processes Presents information from a panel of experts on the topic Follows prognostics based on statistical modelling, reliability modelling and usage modelling methods Written for system engineers working in critical process industries and automotive and aerospace designers, Prognostics and Health Management offers a guide to the application of condition-based data to produce signatures for input to predictive algorithms to produce prognostic estimates of functional health and life.

Earthquake and Volcano Deformationis the first textbook to present the mechanical models of earthquake and volcanic processes, emphasizing earth-surface deformations that can be compared with observations from Global Positioning System (GPS) receivers, Interferometric Radar (InSAR), and borehole strain- and tiltmeters. Paul Segall provides the physical and mathematical fundamentals for the models used to interpret deformation measurements near active faults and volcanic centers. Segall highlights analytical methods of continuum mechanics applied to problems of active crustal deformation. Topics include elastic dislocation theory in homogeneous and layered half-spaces, crack models of faults and planar intrusions, elastic fields due to pressurized spherical and ellipsoidal magma chambers, time-dependent deformation resulting from faulting in an elastic layer overlying a viscoelastic half-space and related earthquake cycle models, poroelastic effects due to faulting and magma chamber inflation in a fluid-saturated crust, and the effects of gravity on deformation. He also explains changes in the gravitational field due to faulting and magmatic intrusion, effects of irregular surface topography and earth curvature, and modern concepts in rate- and state-dependent fault friction. This textbook presents sample calculations and compares model predictions against field data from seismic and volcanic settings from around the world. Earthquake and Volcano Deformationrequires working knowledge of stress and strain, and advanced calculus. It is appropriate for advanced undergraduates and graduate students in geophysics, geology, and engineering. Professors: A supplementary Instructor's Manual is available for this book. It is restricted to teachers using the text in courses. For information on how to obtain a copy, refer to: http://press.princeton.edu/class_use/solutions.html

Western Hubei Province, China, lies in the transition zone between the second and third topographic steps of China’s terrain ladder system. Influenced by the deep incision of the Yangtze River and its tributaries, numerous high-steep slopes have been widely developed in this region.This study focuses on the Heicao dangerous rock mass in Xingshan County, Hubei Province. Through field investigations and Unmanned Aerial Vehicle (UAV) photogrammetry, a discrete element numerical model was developed to investigate the progressive failure mechanisms of high-steep dangerous rock masses under varying lengths of the main structural plane.This study will contribute to future prevention and control of such hazardous rock disasters.The principal conclusions are as follows: (1) The failure surface of the Heicao rock mass exhibits composite form,with the upper section displaying a polyline geometry and the lower section approximating an arc-shaped profile. (2) The main structural plane length significantly affects both the damage extent and propagation velocity in the upper rock mass. (3) Dangerous rock mass instability is jointly influenced by the basal rock mass and the overlying rock mass. Under gravity, progressive failure of the basal rock mass triggers crack development and anti-sliding force attenuation, while main structural plane propagation exacerbates damage. Ultimately, rock bridge shearing and crack coalescence lead to the formation of a progressively penetrating failure surface, resulting in global instability. (4) The results of this study have important theoretical and practical implications for future geological disaster assessment and prevention. In particular, the effective protection of the basement rock mass is the key factor to prevent the formation of dangerous rock mass disasters.

The durability of reinforced concrete structures has always been an important problem in civil engineering because steel rebars rust easily. Therefore, fiber-reinforced polymer (FRP) rebars possessing good corrosion resistance, low weight, and easy construction has become a substitute for reinforcement. However, since FRP rebar has a low elastic modulus and is a brittle failure material, large deflections and cracks occur in the FRP concrete beam with no obvious warning before failure. A hybrid reinforced concrete beam that combines the advantages of steel rebar and FRP rebar is a good structural form. The reliability of hybrid reinforced beams must be analyzed to ensure their safety. A flexural performance test of the hybrid basalt FRP (BFRP)–steel-reinforced beam was performed, the failure mode was explored, and the numerical models were established. The accuracy of the models was verified by comparing them with the test results. The numerical models were used to establish a database (630 cases) that was combined with existing research results (33 cases), to obtain the statistics of the uncertainty of the prediction model. Reliability analysis of a large-scale design space was conducted to calibrate the BFRP. Finally, the average deviation from the target reliability index suggested that the values of the partial coefficient of the materials range from 1.2 to 1.4.

This contribution studies failure by elastic buckling and plastic collapse of wall structures during extrusion-based 3D printing processes. Results obtained from the parametric 3D printing model recently developed by Suiker (Int J Mech Sci, 137: 145–170, 2018), among which closed-form expressions useful for engineering practice, are validated against results of dedicated FEM simulations and 3D concrete printing experiments. In the comparison with the FEM simulations, various types of wall structures are considered, which are subjected to linear and exponentially decaying curing processes at different curing rates. For almost all cases considered, the critical wall buckling length computed by the parametric model turns out to be in excellent agreement with the result from the FEM simulations. Some differences may occur for the particular case of a straight wall clamped along its vertical edges and subjected to a relatively high curing rate, which can be ascribed to the approximate form of the horizontal buckling shape used in the parametric model. The buckling responses computed by the two models for a wall structure with imperfections of different wavelengths under increasing deflection correctly approaches the corresponding bifurcation buckling length. Further, under a specific change of the material properties, the parametric model and the FEM model predict a similar transition in failure mechanism, from elastic buckling to plastic collapse. The experimental validation of the parametric model is directed towards walls manufactured by 3D concrete printing, whereby the effect of the material curing rate on the failure behaviour of the wall is explored by studying walls of various widths. At a relatively low curing rate, the experimental buckling load is well described when the parametric model uses a linear curing function. However, the experimental results suggest the extension of the linear curing function with a quadratic term if the curing process under a relatively long printing time is accelerated by thermal heating of the 3D printing facility. In conclusion, the present validation study confirms that the parametric model provides a useful research and design tool for the prediction of structural failure during extrusion-based 3D printing. The model can be applied to quickly and systematically explore the influence of the individual printing process parameters on the failure response of 3D-printed walls, which can be translated to directives regarding the optimisation of material usage and printing time.

The number of bridges approaching or exceeding their initial design life has been increasing dramatically. Meanwhile, bridges are withstanding an ever-increasing traffic volume, both in number and weight of vehicles. Analytical and numerical models can predict bridges’ response to traffic loads and their ultimate capacity with low uncertainties; however, such uncertainties increase as bridges age due to deterioration mechanisms. Non-destructive tests of material specimens and full-scale load tests allow for updating structural models and predicting bridges’ responses with higher accuracy. On-site load tests with different load levels provide different information on the bridge behaviour (e.g., elastic response, first-crack load, and ultimate capacity), which impact the model updating differently. This paper compares the observed response of the Alveo Vecchio viaduct, a prestressed concrete (PC) bridge subjected to a controlled load test up to its failure, with its predicted response provided by four structural models. The observed response is measured by an extensive structural health monitoring system, while the structural models are developed with different levels of refinement and uncertainty in the input parameters. This study gives an insight into the ultimate load-carrying capacity of existing PC bridges and their behaviour during a whole load test to failure. The results show that the load-carry capacity of the Alveo Vecchio viaduct is almost four times higher than the design load; likely, many other Italian highway bridges with similar structural characteristics have a similar capacity.

Faults are rarely completely smooth, with topographic undulations coming from the distribution of asperities along the fault surface. Understanding the effects of fault surface topography on fault strength and earthquake source properties has been limited due to a lack of in situ observations in the field. Here we use simulated earthquake cycles on metre-scale laboratory faults to show the effects of the degree of fault topographic heterogeneity, especially on macroscopic peak strength represented by the shear force required to commence macroscopic failure. Our results demonstrate that the less heterogeneous fault is weaker, due to its lower macroscopic peak strength, and produces a larger stress drop on average than the more heterogeneous fault. Rupture along the less heterogeneous fault tends to propagate at subshear speed while the more heterogeneous fault accommodates a wider range of rupture speeds, including slow slip and supershear rupture. These results reveal how fault topographic heterogeneity affects macroscopic peak strength at rupture initiation and stress drop during rupture propagation, which has important implications for understanding natural faults and earthquakes.Simulated earthquakes on metre-scale laboratory faults reveal that fault surfaces with more heterogeneous topography are stronger, and rupture at a wider range of propagation speeds, than those that are less heterogeneous.