scholarly journals PROBABILISTIC ANALYSIS OP SEAFLOOR LIQUEFACTION

1988 ◽  
Vol 1 (21) ◽  
pp. 101 ◽  
Author(s):  
Rafael Blazquez ◽  
Felipe M. Martinez
Keyword(s):  
Soil Layer ◽  
Water System ◽  
Deterministic Models ◽  
Risk Models ◽  
First Order ◽  
Sensitivity Indices ◽  
Reliability Method ◽  
Input Variables ◽  
Relationship Of ◽  
The Relationship

To investigate the reliability of a sandy soil layer in an ocean wave environment a liquefaction model is used in conjunction with a first order reliability method. Thus, sensitivity indices of the soil-water system with respect to the uncertain strength and input variables are computed, and the relative importance of the various factors defining the problem can be determined. The relationship of this approach with more conventional design methods (deterministic models, risk models) is discussed along with the range of applicability of the different safety measurements.

An improvement to the ANN-enhanced flow rating method

2021 ◽  
Author(s):  
Bernhard Schmid
Keyword(s):  
Neural Network ◽  
Electrical Conductivity ◽  
Water Resources ◽  
Flow Rate ◽  
Major Ions ◽  
Rate Of Change ◽  
Data Set ◽  
Input Variables ◽  
Relationship Of ◽  
The Relationship

<p>The work reported here builds upon a previous pilot study by the author on ANN-enhanced flow rating (Schmid, 2020), which explored the use of electrical conductivity (EC) in addition to stage to obtain ‘better’, i.e. more accurate and robust, estimates of streamflow. The inclusion of EC has an advantage, when the relationship of EC versus flow rate is not chemostatic in character. In the majority of cases, EC is, indeed, not chemostatic, but tends to decrease with increasing discharge (so-called dilution behaviour), as reported by e.g. Moatar et al. (2017), Weijs et al. (2013) and Tunqui Neira et al.(2020). This is also in line with this author’s experience.</p><p>The research presented here takes the neural network based approach one major step further and incorporates the temporal rate of change in stage and the direction of change in EC among the input variables (which, thus, comprise stage, EC, change in stage and direction of change in EC). Consequently, there are now 4 input variables in total employed as predictors of flow rate. Information on the temporal changes in both flow rate and EC helps the Artificial Neural Network (ANN) characterize hysteretic behaviour, with EC assuming different values for falling and rising flow rate, respectively, as described, for instance, by Singley et al. (2017).</p><p>The ANN employed is of the Multilayer Perceptron (MLP) type, with stage, EC, change in stage and direction of change in EC of the Mödling data set (Schmid, 2020) as input variables. Summarising the stream characteristics, the Mödling brook can be described as a small Austrian stream with a catchment of fairly mixed composition (forests, agricultural and urbanized areas). The relationship of EC versus flow reflects dilution behaviour. Neural network configuration 4-5-1 (the 4 input variables mentioned above, 5 hidden nodes and discharge as the single output) with learning rate 0.05 and momentum 0.15 was found to perform best, with testing average RMSE (root mean square error) of the scaled output after 100,000 epochs amounting to 0.0138 as compared to 0.0216 for the (best performing) 2-5-1 MLP with stage and EC as inputs only.    </p><p> </p><p>References</p><p>Moatar, F., Abbott, B.W., Minaudo, C., Curie, F. and Pinay, G.: Elemental properties, hydrology, and biology interact to shape concentration-discharge curves for carbon, nutrients, sediment and major ions. Water Resources Res., 53, 1270-1287, 2017.</p><p>Schmid, B.H.: Enhanced flow rating using neural networks with water stage and electrical conductivity as predictors. EGU2020-1804, EGU General Assembly 2020.</p><p>Singley, J.G., Wlostowski, A.N., Bergstrom, A.J., Sokol, E.R., Torrens, C.L., Jaros, C., Wilson, C.,E., Hendrickson, P.J. and Gooseff, M.N.: Characterizing hyporheic exchange processes using high-frequency electrical conductivity-discharge relationships on subhourly to interannual timescales. Water Resources Res. 53, 4124-4141, 2017.</p><p>Tunqui Neira, J.M., Andréassian, V., Tallec, G. and Mouchel, J.-M.: A two-sided affine power scaling relationship to represent the concentration-discharge relationship. Hydrol. Earth Syst. Sci. 24, 1823-1830, 2020.</p><p>Weijs, S.V., Mutzner, R. and Parlange, M.B.: Could electrical conductivity replace water level in rating curves for alpine streams? Water Resources Research 49, 343-351, 2013.</p>

Coherence analysis of a family of weighted star-composed networks

2019 ◽  
Vol 33 (23) ◽  
pp. 1950264
Author(s):  
Meifeng Dai ◽  
Tingting Ju ◽  
Yongbo Hou ◽  
Jianwei Chang ◽  
Yu Sun ◽  
...  
Keyword(s):  
Kronecker Product ◽  
Future Research ◽  
Weight Factor ◽  
Node Number ◽  
Laplacian Eigenvalues ◽  
First Order ◽  
Successive Generations ◽  
Network Consistency ◽  
Relationship Of ◽  
The Relationship

Recently, the study of many kinds of weighted networks has received the attention of researchers in the scientific community. In this paper, first, a class of weighted star-composed networks with a weight factor is introduced. We focus on the network consistency in linear dynamical system for a class of weighted star-composed networks. The network consistency can be characterized as network coherence by using the sum of reciprocals of all nonzero Laplacian eigenvalues, which can be obtained by using the relationship of Laplacian eigenvalues at two successive generations. Remarkably, the Laplacian matrix of the class of weighted star-composed networks can be represented by the Kronecker product, then the properties of the Kronecker product can be used to obtain conveniently the corresponding characteristic roots. In the process of finding the sum of reciprocals of all nonzero Laplacian eigenvalues, the key step is to obtain the relationship of Laplacian eigenvalues at two successive generations. Finally, we obtain the main results of the first- and second-order network coherences. The obtained results show that if the weight factor is 1 then the obtained results in this paper coincide with the previous results on binary networks, otherwise the scalings of the first-order network coherence are related to the node number of attaching copy graph, the weight factor and generation number. Surprisingly, the scalings of the first-order network coherence are independent of the node number of initial graph. Consequently, it will open up new perspectives for future research.

Kinetics of aquation of the fluoropentaamminecobalt(III) ion

1970 ◽  
Vol 48 (7) ◽  
pp. 1054-1058 ◽  
Author(s):  
T. W. Swaddle ◽  
W. E. Jones
Keyword(s):  
Ionic Strength ◽  
Rate Coefficient ◽  
Hydrogen Ion ◽  
Fluoride Ion ◽  
Kcal Mole ◽  
First Order ◽  
Order Rate ◽  
Relationship Of ◽  
The Relationship ◽  
Kinetics Of

The kinetics of the hydrogen-ion-independent pathway for the replacement of fluoride in aqueous (NH3)5CoF2+ by H2O have been reinvestigated using a specific fluoride-ion electrode, with due regard for the concomitant autocatalytic loss of the ammine ligands. In perchlorate media of ionic strength 0.1 M, the first-order rate coefficient is 1.22 × 10−6 s−1 at 45°, and the kinetics are represented by ΔH* = 24.4 kcal mole−1 and ΔS* = −9 cal deg−1 mole−1 over the range 35–75° at least. The relationship of these data to those for the aquation of other species of the type ML5Xn+ is discussed.

A Weighted Three-Point-Based Strategy for Variance Estimation

2004 ◽  
Author(s):  
Thaweepat Buranathiti ◽  
Jian Cao ◽  
Wei Chen
Keyword(s):  
Variance Estimation ◽  
Order Approximation ◽  
Computational Effort ◽  
Normal Space ◽  
System Response ◽  
Test Problems ◽  
Deterministic Models ◽  
Analysis And Design ◽  
First Order ◽  
Input Variables

In manufacturing processes, it is widely accepted that uncertainty plays an important role and should be taken into account during analysis and design processes. However, uncertainty quantification of its effects on an end-product is a very challenging task, especially when an expensive computational effort is already needed in deterministic models such as sheet metal forming simulations. In this paper, we focus our work on the variance estimation of the system response. A weighted three-point-based strategy is proposed to efficiently and effectively estimate the variance of the system response. Three first-order derivatives for each variable are used to estimate the nonlinear behavior and variance of the system. The details of the derivation of the approach are presented in the paper. The optimal locations of the three points along each axis in the standard normal space and weights for input variables following normal distributions are proposed as (−1.8257,0.0,+1.8257) and (0.075,0.850,0.075), respectively. For input variables following uniform distributions U(−1,1), the optimal locations and weights are proposed as (−0.84517,0.0,+0.84517) and (0.04667,0.90666,0.04667), respectively. The proposed approach is applicable to nonlinear and multivariable systems as well as problems having no explicit function such as those design simulations based on finite element methods. The significant accuracy improvement over the traditional first-order approximation is demonstrated with a number of test problems. The proposed method requires significantly less computational effort compared with the Monte Carlo simulations. Discussions and conclusions of this work are given at the end of the paper.

Moment Matching for Sensitivity Analysis of Probabilistic Model Output

2004 ◽  
Author(s):  
Mahmoud Awad ◽  
Agus Sudjianto ◽  
Nanua Singh
Keyword(s):  
Sensitivity Analysis ◽  
Simulation Models ◽  
Moment Matching ◽  
Model Output ◽  
Sensitivity Indices ◽  
Variance Contribution ◽  
Complex Engineering ◽  
Input Variables ◽  
The Relationship ◽  
Effective Sensitivity

With the advent of highly complex engineering simulation models that describe the relationship between input variables and output response, the need for an efficient and effective sensitivity analysis is more demanding. In this article, a generalized approach that can provide efficient as well as accurate global sensitivity indices is developed. The approach consists of two steps: running an orthogonal array based experiment using moment-matched levels of the input variables and followed by a variance contribution analysis. The benefits of the approach are demonstrated through three different examples.

scholarly journals New Importance Measures Based on Failure Probability in Global Sensitivity Analysis of Reliability

Mathematics ◽  
2021 ◽  
Vol 9 (19) ◽  
pp. 2425
Author(s):  
Zdeněk Kala
Keyword(s):  
Sensitivity Analysis ◽  
Global Sensitivity Analysis ◽  
Binary Outcome ◽  
Global Sensitivity ◽  
First Order ◽  
Sensitivity Measure ◽  
Sensitivity Indices ◽  
Alternative Measures ◽  
Input Variables ◽  
Dome Shape

This article presents new sensitivity measures in reliability-oriented global sensitivity analysis. The obtained results show that the contrast and the newly proposed sensitivity measures (entropy and two others) effectively describe the influence of input random variables on the probability of failure Pf. The contrast sensitivity measure builds on Sobol, using the variance of the binary outcome as either a success (0) or a failure (1). In Bernoulli distribution, variance Pf(1 − Pf) and discrete entropy—Pfln(Pf) − (1 − Pf)ln(1 − Pf) are similar to dome functions. By replacing the variance with discrete entropy, a new alternative sensitivity measure is obtained, and then two additional new alternative measures are derived. It is shown that the desired property of all the measures is a dome shape; the rise is not important. Although the decomposition of sensitivity indices with alternative measures is not proven, the case studies suggest a rationale structure of all the indices in the sensitivity analysis of small Pf. The sensitivity ranking of input variables based on the total indices is approximately the same, but the proportions of the first-order and the higher-order indices are very different. Discrete entropy gives significantly higher proportions of first-order sensitivity indices than the other sensitivity measures, presenting entropy as an interesting new sensitivity measure of engineering reliability.

Analysis of sequential events in intestinal absorption of folylpolyglutamate

1988 ◽  
Vol 255 (3) ◽  
pp. G361-G366 ◽  
Author(s):  
B. Darcy-Vrillon ◽  
J. Selhub ◽  
I. H. Rosenberg
Keyword(s):  
Intestinal Absorption ◽  
Competitive Inhibitor ◽  
First Order ◽  
Rate Determining Step ◽  
In Vivo Absorption ◽  
Rate Of Hydrolysis ◽  
The Individual ◽  
Relationship Of ◽  
The Relationship

Although it is clear that the intestinal absorption of folylpolyglutamates is associated with hydrolysis to monoglutamyl folate, the precise sequence and relative velocity of the events involved in this absorption are not fully elucidated. In the present study, we used biosynthetic, radiolabeled folylpolyglutamates purified by affinity chromatography to analyze the relationship of hydrolysis and transport in rat jejunal loops in vivo. Absorption was best described by a series of first-order processes: luminal hydrolysis to monoglutamyl folate followed by tissue uptake of the product. The rate of hydrolysis in vivo was twice as high as the rate of transport. The latter value was identical to that measured for folic acid administered separately. The relevance of this sequential model was confirmed by data obtained using inhibitors of the individual steps in absorption of "natural" folate. Heparin and sulfasalazine were both effective in decreasing absorption. The former affected hydrolysis solely, whereas the latter acted as a competitive inhibitor of transport of monoglutamyl folate. These studies confirm that hydrolysis is obligatory and that the product is subsequently taken up by a transport process, common to monoglutamyl folates, that is the rate-determining step in transepithelial absorption.

scholarly journals STUDIES ON A SARCOSINE OXIDASE OF BACTERIAL ORIGIN

1950 ◽  
Vol 34 (1) ◽  
pp. 9-17 ◽  
Author(s):  
Paul H. Kopper ◽  
Keyword(s):  
Chemical Compounds ◽  
Enzyme Concentration ◽  
Order Reaction ◽  
Effect Of Temperature ◽  
Heat Inactivation ◽  
Sarcosine Oxidase ◽  
First Order ◽  
Optimal Activity ◽  
Relationship Of ◽  
The Relationship

A "sarcosine oxidase" was prepared from a creatinine-decomposing strain of Pseudomonas aeruginosa. The enzyme is inactivated by drying, lyophilization, and dialysis against distilled water. No dialyzable cofactor was found. Optimal activity of the enzyme is reached at pH 7.8. Enzyme activity is directly proportional to enzyme concentration and also to substrate concentration up to the point of saturation of enzyme with substrate molecules. One molecule of enzyme combines with one molecule of substrate. Data concerning the effect of temperature and of a variety of chemical compounds on the enzyme are presented. Its inactivation by heat follows the course of a first order reaction, and the critical thermal increment between 48° and 52°C. was calculated to be 103,000 calories per mol. The relationship of enzyme concentration to heat inactivation rates is illustrated.

Substituent effects on the electronic spectra of aromatic hydrocarbons II. The quantitative determination of the inductive effect on π-electrons

1964 ◽  
Vol 278 (1372) ◽  
pp. 64-70 ◽  
Keyword(s):  
Aromatic Hydrocarbons ◽  
Substituent Effects ◽  
Negative Ion ◽  
First Order ◽  
Spin Resonance ◽  
Inductive Effects ◽  
Inductive Parameter ◽  
Relationship Of ◽  
The Relationship

The inductive effects of substituent groups on the π-electrons of aromatic hydrocarbons are estimated quantitatively from electronic spectroscopic data. Two methods are used to evaluate the parameters. The first is based on the first-order changes in the energy of the first transition of azulene on mono-substitution and the second is based on the second-order changes in the energy of the first transition of benzene on poly substitution. The agreement between the values obtained by the two methods is good except for acceptor substituents for which the values obtained by the first method are considerably smaller than those obtained by the second. Using these values of the inductive parameter we have calculated the splitting of the ground state of the benzene negative ion brought about by substituents; and the relationship of this splitting to the electron spin resonance spectra of these ions is discussed.

A Reliability Approach to Inverse Simulation Under Uncertainty

2012 ◽  
Author(s):  
Xiaoping Du
Keyword(s):  
Reliability Analysis ◽  
High Efficiency ◽  
Probability Distributions ◽  
Random Parameters ◽  
Inverse Simulation ◽  
First Order ◽  
Reliability Method ◽  
Simulation Input ◽  
Input Variables ◽  
Impact Problem

Inverse simulation is an inverse process of a direct simulation. During the process, the simulation input variables are identified for a given set of simulation output variables. Uncertainties such as random parameters may exist in engineering applications of inverse simulation. A reliability method is developed in this work to estimate the probability distributions of unknown simulation input. The First Order Reliability Method is employed and modified so that the inverse simulation is embedded within the reliability analysis algorithm. This treatment avoids the separate executions of reliability analysis and inverse simulation and consequently maintains high efficiency. In addition, the means and standard deviations of unknown input variables can also be obtained. A particle impact problem is presented to demonstrate the proposed method for inverse simulation under uncertainty.

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