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Robust

Environmental vulnerability varies considerably from area to area. For example the North Sea, which is displaced into the Atlantic over a two year period,-is a much more robust area than the Caspian Sea which is enclosed. Regional standards should reflect those differences. [Pg.70]

Once the production potential of the producing wells is insufficient to maintain the plateau rate, the decline periodbegins. For an individual well in depletion drive, this commences as soon as production starts, and a plateau for the field can only be maintained by drilling more wells. Well performance during the decline period can be estimated by decline curve analysis which assumes that the decline can be described by a mathematical formula. Examples of this would be to assume an exponential decline with 10% decline per annum, or a straight line relationship between the cumulative oil production and the logarithm of the water cut. These assumptions become more robust when based on a fit to measured production data. [Pg.209]

Another useful profitability indicator is the internal rate of return (IRR), already introduced in the last section. This shows what discount rate would be required to reduce the NPV to zero. The higher the IRR, the more robust the project is, i.e. the more risk it can withstand before the IRR is reduced to the screening value of discount rate. Screening values are discussed below. [Pg.323]

In order to test the economic performance of the project to variations in the base case estimates for the input data, sensitivity analysis is performed. This shows how robust the project is to variations in one or more parameters, and also highlights which of the inputs the project economics is more sensitive to. These inputs can then be addressed more specifically. For example if the project economics is highly sensitive to a delay in first production, then the scheduling should be more critically reviewed. [Pg.325]

Our first instrument had to be robust tmd very easy to operate this has been an objective for every instrument made by this company and we would be happy to be remembered for it. [Pg.274]

Thanks to this technology,films with a high quality,very robust and environmentally friendly have been designed. [Pg.448]

Neuronal networks are nowadays predominantly applied in classification tasks. Here, three kind of networks are tested First the backpropagation network is used, due to the fact that it is the most robust and common network. The other two networks which are considered within this study have special adapted architectures for classification tasks. The Learning Vector Quantization (LVQ) Network consists of a neuronal structure that represents the LVQ learning strategy. The Fuzzy Adaptive Resonance Theory (Fuzzy-ART) network is a sophisticated network with a very complex structure but a high performance on classification tasks. Overviews on this extensive subject are given in [2] and [6]. [Pg.463]

The specific advanced properties of the ceramic insulator eliminate the need for oil or resin insulation. The metal vacuum envelope of the tube provides higher beam stability, more robust design, and even X-ray shielding up to certain levels. Furthermore, even difScult mechanical problems (e.g. mounting, coohng, or beam emission) can be solved by an appropriate customised tube design. [Pg.532]

The tubes of the new MCB series are a highly integrated and reliable ready-to-use component for radiation applications, which until now were not feasible due to the lack of robustness, size, or stability requirements. [Pg.532]

Our company is dedicated solely to metal-ceramic X-ray tubes since 25 years over this time, we have made lots of different tube models especially for tyre inspection systems. The major reasons for the use of metal-ceramic tubes in this inspection technology are robustness, their small and individual shapes, and the frequent need for modifications of their design due to custom designed systems. [Pg.535]

Taking into account that size and weight can change tremendously fi-om one object to the next, it is obvious that the CT- system had to be build in a very versatile but robust manner. For example heavy objects have to be moved very carefully, whereas small objects have to be measured as fast as possible and as accurate as possible. For that reason the turntable is equipped with an instrument, which limits the velocity, if the weight of the object is above a preselectable threshold. [Pg.585]

One remarkably simple yet seemingly robust outcome of Turnbull s experiments was his empirical finding that the solid-liquid interfacial free energy was... [Pg.336]

Li and Neumann sought an equation of state of interfacial tensions of the form 7 l = /(Tlv. TSv). Based on a series of measurements of contact angles on polymeric surfaces, they revised an older empirical law (see Refs. 216, 217) to produce a numerically robust expression [129, 218]... [Pg.377]

While a number of proteins have been crystallized in this manner, the majority of studies have focused on a robust system comprising the tetrameric protein streptavidin and the vitamin biotin. The choice of this system is primcirily motivated by the strong bond between biotin and streptavidin (having an association equilibrium constant, Ka Tbe binding properties were recently... [Pg.543]

The third alternative is a more robust, sensitive and specialized fonn of the first, in that only hydrogen nuclei indirectly spin-spin coupled to in a specific molecular configuration are imaged. In achieving selectivity, the technique exploits the much wider chemical shift dispersion of compared to H. The metliod involves cyclic transfer from selected H nuclei to indirectly spin-spin coupled C nuclei and back according to the sequence... [Pg.1533]

Bain A D and Duns G J 1994 Simultaneous determination of spin-lattioe (T1) and spin-spin (T2) relaxation times in NMR a robust and faoile method for measuring T2. Optimization and data analysis of the offset-saturation experiment J. Magn. Reson. A 109 56-64... [Pg.2113]

For a recent critical evaluation of situations where current DFT approaches experience difficulties, see Davidson E R 1998 How robust is present-day DFT ... [Pg.2199]

The mean field teclmique is one of the most robust and simple methods used to handle larger molecules in gas and liquid enviromnents [M, 134. 135 and 136]. The basic premise of all mean-field methods is that the fiill wavefiinction represents N very weakly coupled modes (2 ) and can be approximated as... [Pg.2312]

Altliough an MOT functions as a versatile and robust reaction cell for studying cold collisions, light frequencies must tune close to atomic transitions and an appreciable steady-state fraction of tire atoms remain excited. Excited-state trap-loss collisions and photon-induced repulsion limit achievable densities. [Pg.2471]

The Fresnel equations predict that reflexion changes the polarization of light, measurement of which fonns the basis of ellipsometry [128]. Although more sensitive than SAR, it is not possible to solve the equations linking the measured parameters with n and d. in closed fonn, and hence they cannot be solved unambiguously, although their product yielding v (equation C2.14.48) appears to be robust. [Pg.2838]

Schaaff T G efa/1997 Isolation of smaller nanocrystal Au molecules robust quantum effects in the optical spectra J. Phys. Chem. B 101 7885... [Pg.2919]

The long term behavior of any system (3) is described by so-called invariant measures a probability measure /r is invariant, iff fi f B)) = ft(B) for all measurable subsets B C F. The associated invariant sets are defined by the property that B = f B). Throughout the paper we will restrict our attention to so-called SBR-measures (cf [16]), which are robust with respect to stochastic perturbations. Such measures are the only ones of physical interest. In view of the above considerations about modelling in terms of probabilities, the following interpretation will be crucial given an invariant measure n and a measurable set B C F, the value /r(B) may be understood as the probability of finding the system within B. [Pg.103]


See other pages where Robust is mentioned: [Pg.262]    [Pg.293]    [Pg.105]    [Pg.106]    [Pg.464]    [Pg.527]    [Pg.532]    [Pg.550]    [Pg.1063]    [Pg.397]    [Pg.73]    [Pg.890]    [Pg.1178]    [Pg.1474]    [Pg.1474]    [Pg.1484]    [Pg.1791]    [Pg.1868]    [Pg.1968]    [Pg.1969]    [Pg.1973]    [Pg.2472]    [Pg.2702]    [Pg.2702]    [Pg.2772]    [Pg.2865]    [Pg.3049]    [Pg.298]    [Pg.214]   
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A Robust Approach to Inorganic Aerogels The Use of Epoxides in Sol-Gel Synthesis

Accounting for Uncertainty Robust Production Network Design

Adaptation robustness

Advancing Robust Regulation Reflections and Lessons to Be Learned

Affinity chromatography robustness

Analysis of split-plot designs for robust experimentation

Analytical method validation robustness

Analytical methods ruggedness/robustness

Analytical performance parameters Robustness

Analytical procedure robustness

Are resistant insects more robust than sensitive ones

Assay methods robustness

Assay robustness

Avoided crossing robustness

Calculation, robust

Cell factory robustness

Chains, robust electron transfer protein design

Chelation robust types

Chemical Robustness

Chromatographic methods, robustness

Class for Robust Multidimensional Minimization

Classes for One-Dimensional Robust Minimization

Classes for Robust Two-Dimensional Minimization

Columns robustness

Complex ions robust complexes

Computational methods robustness

Control limit robust

Covariance robust estimation

Cross-validation robustness

Defining Inhibition, Signal Robustness, and Hit Criteria

Design of robust adaptive controller

Detection wavelength, robustness

Detector wavelength robustness

Developing a Robust Safety Management System

Development of Robust Mixed-Conducting Membranes with High Permeability and Stability

Discovery research robustness

Enforcement robustness

Enhancing Accuracy - Obtaining Robust Calibration Functions with Weighting

Enhancing Thermostability for More Robust Enzymes

Evaluating Robustness

Evolutionary robustness

Examples robustness

Experimental robustness

Extraction robustness

Fault Diagnosis with Robust Techniques

Fault diagnosis robust

Fermentation robustness

Filler robustness

Filter robust

Fixed points robust

Formulation robust formulations

Functional and Robust Modules

Functional assays assay robustness

Glassy Liquid Crystals as Self-Organized Films for Robust Optoelectronic Devices

How Robust Must the Method Be

INDEX robust performance

Immunoassay robustness

Inheritance, robustness

International regimes robustness

MATLAB robust control toolbox

Maintenance and Robustness

Materials and Robustness

Mechanical robustness

Metabolic systems robustness

Metabolomics robustness

Method development quantitative factors robustness

Method robustness 7421 Subject

Method validation robustness

Method, robustness

Mobile phase robustness

Model and Solution Robustness

Model-robust factorial design

Model-robust orthogonal design

Model-robust parameter design

Models robust

Models robustness

Molecular networks robustness

Multidimensional robust minimization

Multiple-pulse sequence robustness

Multisite robust planning

Multivariable H2 and robust control

Multivariable robust control

Natural product libraries as robust process

Network robust

Noise robustness

Non-parametric and robust methods

Nucleation robust

OPTIMAL AND ROBUST CONTROL SYSTEM DESIGN

Objective robust planning

Optical robustness protein

Optimization robust

Parameter estimation robustness

Parameters robust

Partial robust M-regression

Petrochemical robust

Planning robust

Process control robust

Process robustness

Process robustness approach

Protocol, method validation robustness

Proton transfer design robustness

Quantitation robustness

R robustness

ROBUST DESIGN AND RESPONSE SURFACE METHODOLOGY

ROBUST Project

Reaching the Final Target A Robust Commercial Process

Real robustness

Regression methods, assumptions robust

Regression robustness

Regulation robust

Relaxation time robustness

Repeller robustness

Reproducibility and robustness

Robust Adaptive Control of Conjugated Polymer Actuators

Robust Bayes

Robust Control Design Methods

Robust Covariance Estimator

Robust Design (Technique

Robust Design (Technique resources

Robust Design and

Robust Electron Transfer Protein Design

Robust Estimation Approaches

Robust FDI

Robust Function Root-Finding

Robust Information Entropy

Robust Methodology Experimental Designs and Optimisation

Robust Methods in Analysis of Multivariate Food Chemistry Data

Robust Monitoring Strategy

Robust Parameter Design Reducing Variation

Robust Planning for Petrochemical Networks

Robust Planning of Multisite Refinery Network

Robust Planning with Price Uncertainties

Robust Summaries

Robust Unconstrained Minimization

Robust actuator

Robust algorithms

Robust and Variational Fitting

Robust arrays, bridging

Robust beer foams

Robust calibration

Robust catalyst

Robust challenges

Robust chemical robustness

Robust clusters

Robust complex

Robust contextualism

Robust continuum regression

Robust control

Robust control problem

Robust control theory

Robust control toolbox

Robust decision procedures

Robust design

Robust estimates of location and spread

Robust estimation

Robust estimator

Robust experimentation

Robust failure probability

Robust formulation

Robust fundamentals

Robust linear discriminant analysis

Robust matrix material

Robust methods

Robust methods - Introduction

Robust methods or non-parametric tests

Robust microarray analysis

Robust mixed-conducting membranes

Robust multichip average

Robust multisite refinery network

Robust multivariable control system design

Robust multivariate statistics

Robust octahedral complexes

Robust optimizers conformational search

Robust performance

Robust petrochemical network

Robust phase stability

Robust piping system

Robust plant lead

Robust principal component analysis

Robust principal component analysis ROBPCA)

Robust principal component analysis applications

Robust principal components

Robust process

Robust production system

Robust reduced-step Newton method

Robust regression

Robust regression methods

Robust reliability analysis

Robust solutions

Robust stability

Robust statistical method

Robust statistics

Robust stochastic optimal control

Robust study summary

Robust technology

Robust test

Robust tolerance analysis

Robust tolerance toward

Robustic acid

Robustness

Robustness

Robustness Coefficient

Robustness Test in Analytical RP-HPLC by Means of Statistical Experimental Design (DoE)

Robustness analysis

Robustness and Outlier Resistance

Robustness and Ruggedness

Robustness approaches

Robustness automated methods

Robustness characteristics

Robustness characteristics measurement

Robustness checks

Robustness chemokines

Robustness chromatography purification

Robustness criteria

Robustness criteria, determination

Robustness dissolution

Robustness enhancing

Robustness evaluation

Robustness fractionation/purification

Robustness influencing variables

Robustness meta-analysis

Robustness method validation elements

Robustness of an analytical method

Robustness of method

Robustness of the Proposed Batch Operation

Robustness of the SP-PLP-MWD method

Robustness packaging

Robustness parameter

Robustness parameter 748 Subject

Robustness potency

Robustness related substances

Robustness solution stability

Robustness statistical

Robustness steps

Robustness study

Robustness survival data

Robustness test

Robustness testing

Robustness testing chromatographic factors

Robustness testing design

Robustness testing during

Robustness testing effects interpretation

Robustness testing factors

Robustness testing investigated

Robustness testing level selection

Robustness testing optimization

Robustness testing overview

Robustness testing qualitative factors

Robustness testing quantitative factors

Robustness testing ranges evaluated

Robustness thin films

Robustness validation

Robustness, defined

Robustness, definition

Robustness, metabolic states

Robustness, metabolic states modeling

Robustness, model/solution

Robustness, of analytical method

Robustness, technical requirements

Robustness/ruggedness

Ruggedness Testing (Robustness)

Schrodinger equation robustness

Sensitivity and robustness

Separations robustness

Signal robustness

Simple, Robust and Suitable for the Entire Pressure Range

Solution of the Robust Model

Solutions robust model

Solutions robustness

Standard deviation robust

Standard robustness

State robust planning

Steady-state behavior robustness

Strategies for Robust Designs

Synthon robust

System suitability test parameters robustness testing

THE ROBUSTNESS CRITERIA

Temperatures robustness

Test methods robustness

Testing Method Robustness and Ruggedness

Tests D-I robustness

The Robustness Coefficient

The Taguchi Methods and Robust Design

The Taguchi approach to robustness

The special case of robust complexes

Towards Robust Carbonaceous Films on Micro-textured Polymer Surfaces

Uncertainty estimation, robustness

Unconstrained robust

Use of Robust Statistics to Describe Plant Lead Levels Arising from Traffic

Verification Methods for Robustness in RP-HPLC

Weighted and Robust Regression

Worst-case conditions, robustness

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