The current state-of-the-art allows seismologists to give statistical estimates of the probability of a large earthquake striking a given region, identifying the areas in which the seismic hazard is the highest. However, the usefulness of these estimates is limited, without information about local subsoil conditions and the vulnerability of buildings. Identifying the sites where a local ampli?cation of seismic shaking will occur, and identifying the buildings that will be the weakest under the seismic shaking is the only strategy that allows effective defence against earthquake damage at an affordable cost, by applying selective reinforcement only to the structures that need it. Unfortunately, too often the Earth’s surface acted as a divide between seism- ogists and engineers. Now it is becoming clear that the building behaviour largely depends on the seismic input and the buildings on their turn act as seismic sources, in an intricate interplay that non-linear phenomena make even more complex. These phenomena are often the cause of observed damage enhancement during past ear- quakes. While research may pursue complex models to fully understand soil dyn- ics under seismic loading, we need, at the same time, simple models valid on average, whose results can be easily transferred to end users without prohibitive expenditure. Very complex models require a large amount of data that can only be obtained at a very high cost or may be impossible to get at all.
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Too often the Earth's surface acted as a divide between seismologists and engineers. Now it is becoming clear that the building behaviour largely depends on the seismic input and the buildings on their turn act as seismic sources, in an intricate interplay that non-linear phenomena make even more complex. These phenomena are often the cause of observed damage enhancement during past earthquakes. While research may pursue complex models to fully understand soil dynamics under seismic loading, we need also simple models valid on average, whose results can be easily transferred to end users.Under the title "Increasing Seismic Safety by Combining Engineering Technologies and Seismological Data", we grouped several topics to be discussed together by engineers and seismologists: Can we use ambient noise building and soil characterisation to extract useful information for engineers? How we can tell apart a frequency decrease due to distributed damage, concentrated damage, time- varying building and soil behaviour? Which is the role of transients in ambient noise analysis? Can we quantify the influence of existing buildings on ground-motion recordings?
To which extent soil-building resonance is a cause of damage enhancement? How to couple soil and building non-linear behaviour? On most questions there is an unanimous answer, but in some cases different views are present and the disagreement is faithfully reported."About this title" may belong to another edition of this title.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The current state-of-the-art allows seismologists to give statistical estimates of the probability of a large earthquake striking a given region, identifying the areas in which the seismic hazard is the highest. However, the usefulness of these estimates is limited, without information about local subsoil conditions and the vulnerability of buildings. Identifying the sites where a local ampli cation of seismic shaking will occur, and identifying the buildings that will be the weakest under the seismic shaking is the only strategy that allows effective defence against earthquake damage at an affordable cost, by applying selective reinforcement only to the structures that need it. Unfortunately, too often the Earth's surface acted as a divide between seism- ogists and engineers. Now it is becoming clear that the building behaviour largely depends on the seismic input and the buildings on their turn act as seismic sources, in an intricate interplay that non-linear phenomena make even more complex. These phenomena are often the cause of observed damage enhancement during past ear- quakes. While research may pursue complex models to fully understand soil dyn- ics under seismic loading, we need, at the same time, simple models valid on average, whose results can be easily transferred to end users without prohibitive expenditure. Very complex models require a large amount of data that can only be obtained at a very high cost or may be impossible to get at all. 382 pp. Englisch. Seller Inventory # 9781402091940
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - The current state-of-the-art allows seismologists to give statistical estimates of the probability of a large earthquake striking a given region, identifying the areas in which the seismic hazard is the highest. However, the usefulness of these estimates is limited, without information about local subsoil conditions and the vulnerability of buildings. Identifying the sites where a local ampli cation of seismic shaking will occur, and identifying the buildings that will be the weakest under the seismic shaking is the only strategy that allows effective defence against earthquake damage at an affordable cost, by applying selective reinforcement only to the structures that need it. Unfortunately, too often the Earth's surface acted as a divide between seism- ogists and engineers. Now it is becoming clear that the building behaviour largely depends on the seismic input and the buildings on their turn act as seismic sources, in an intricate interplay that non-linear phenomena make even more complex. These phenomena are often the cause of observed damage enhancement during past ear- quakes. While research may pursue complex models to fully understand soil dyn- ics under seismic loading, we need, at the same time, simple models valid on average, whose results can be easily transferred to end users without prohibitive expenditure. Very complex models require a large amount of data that can only be obtained at a very high cost or may be impossible to get at all. Seller Inventory # 9781402091940
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