Uncertainty in Bearing Capacity of Sands

Ingra, Thomas S.; Baecher, Gregory B.

doi:10.1061/(asce)0733-9410(1983)109:7(899)

Cited by 39 publications

(23 citation statements)

References 12 publications

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“…The maximum soil pressure (ultimate bearing capacity) can be calculated according to Terzaghi's superposition method and leads for a circular foundation on the seabed surface (see, e.g., [17,18]) to:…”

Section: Bearing Capacity Failurementioning

confidence: 99%

Reliability-Based Structural Optimization of Wave Energy Converters

2014

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More and more wave energy converter (WEC) concepts are reaching prototype level. Once the prototype level is reached, the next step in order to further decrease the levelized cost of energy (LCOE) is optimizing the overall system with a focus on structural and maintenance (inspection) costs, as well as on the harvested power from the waves. The target of a fully-developed WEC technology is not maximizing its power output, but minimizing the resulting LCOE. This paper presents a methodology to optimize the structural design of WECs based on a reliability-based optimization problem and the intent to maximize the investor's benefits by maximizing the difference between income (e.g., from selling electricity) and the expected expenses (e.g., structural building costs or failure costs). Furthermore, different development levels, like prototype or commercial devices, may have different main objectives and will be located at different locations, as well as receive various subsidies. These points should be accounted for when performing structural optimizations of WECs. An illustrative example on the gravity-based foundation of the Wavestar device is performed showing how structural design can be optimized taking target reliability levels and different structural failure modes due to extreme loads into account.

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Section: Bearing Capacity Failurementioning

confidence: 99%

Reliability-Based Structural Optimization of Wave Energy Converters

2014

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“…Ingra and Baecher [7] performed logarithmic regression analyses on 145 model and prototype footing tests results ( Figure 1) to estimate the expected value and variance of N g for footings of length to width ratio of 1.0 as…”

Section: The Basic Methodsmentioning

confidence: 99%

“…in which R g ; S g ; E g ; I g are, respectively, corrections factors for size, shape, load eccentricity, and load inclination [7]. This generates n ¼ 5 uncertain quantities, leading to 32 calculations, simply for the case that g and f are known.…”

Section: Modifications For Large Numbers Of Variablesmentioning

confidence: 99%

“…The number of variables in a reliability analysis can easily exceed this; structural reliability problems often involve thousands of random variables. In a case closer to geotechnical practice, when using any method of slices for limiting equilibrium slope stability calculation and presuming the slices are taken wide enough to Points at which the bearing capacity is calculated using the point-estimate method with the one uncertain variable, bearing capacity factor N g; using empirical results from Ingra and Baecher [7].…”

Section: Modifications For Large Numbers Of Variablesmentioning

confidence: 99%

“…Figure 7 shows what happens in the case of a triangular distribution . Points at which the bearing capacity is calculated using the point-estimate method with 5 and 10 variables for bearing capacity factor N g; using empirical results from Ingra and Baecher [7]. f ðxÞ between 0 and 1 with its peak at x ¼ c; 05c51: The solid lines describe, as a function of c; the number of uncertain variables necessary to move the co-ordinate of the lower evaluation point in Hong's method below zero, and the dashed lines depict the number of uncertain variables that move the upper point above unity.…”

Section: How a Large Number Of Variables Affects The Location Of The mentioning

confidence: 99%

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The point‐estimate method with large numbers of variables

Christian

Baecher

2002

Num Anal Meth Geomechanics

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SUMMARYRosenbleuth's point-estimate method has become widely used in geotechnical practice for reliability calculations. Although the point-estimate method is a powerful and simple method for evaluating the moments of functions of random variables, it is limited by the need to make 2 n evaluations when there are n random variables. Modifications of the method reduce this to 2n evaluations by using points on the diameters of a hypersphere instead of at the corners of the inscribed hypercube. However, these techniques force the co-ordinates of the evaluation points farther from the means of the variables; for a bounded variable, the points may easily fall outside the domain of definition of the variable. The problem can be avoided by using other techniques for some special cases or by reducing the number of random variables that must be considered. Copyright # 2002 John Wiley & Sons, Ltd. THE BASIC METHODThe point-estimate method, originally proposed by Rosenblueth [1,2], is a simple but powerful technique for evaluating the moments of functions of random variables, and has been adopted in many geotechnical reliability analyses [3]. Miller and Rice [4] and Christian and Baecher [5] have shown that the point-estimate method is a form of Gaussian quadrature. Despite its simplicity, it can be accurate in many practical situations [3][4][5]. In this paper the authors describe current methods for dealing with the computational burdens that arise when the number of variables becomes large and show that these methods are themselves problematical. Examples from geotechnical reliability practice are used to illustrate both difficulties and alternative approaches.As in any Gaussian quadrature scheme, including more points in the calculation increases the order of polynomial functions that are integrated exactly, but the most widely used form of the method employs two points per variable. When there is one independent variable X ; the two values of X where calculations are made are chosen such that

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Bearing Capacity of Shallow Foundations

Chen¹,

McCarron

1991

Foundation Engineering Handbook

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Uncertainty in Bearing Capacity of Sands

Cited by 39 publications

References 12 publications

Reliability-Based Structural Optimization of Wave Energy Converters

Reliability-Based Structural Optimization of Wave Energy Converters

The point‐estimate method with large numbers of variables

Bearing Capacity of Shallow Foundations

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