TIME AND FREQUENCY LOADING ANALYSIS OF SUBMARINE PIPELINES

The paper decribes the revised guideline design wave force calculation procedure approved for the 20th edition of the API-RP2A WSD and the first edition of the API-RP2A LRFD and contrasts it with the procedures in previous editions of RP2A. It also briefly dicusses the new metocean criteria for the Gulf of Mexico. The revised procedure was developed by the API Task Group on Wave Force Commentary. It embodies research results obtained over the last 25 years. It is a significant revision of the guideline wave force calculation procedures that have been part of the RP2A since the 1976 edition. INTRODUTION The paper decribes the revised guideline design wave force calculation procedure approved for the 20th edition of the API-RP2A WSD1 and the first edition of the API-LRFD2 and contrasts it with the procedure in the 19th edition of RP2A3. it also briefly discuesses the new metocean criteria for the Gulf of Mexico. The intent of the paper is to make personnel involved in structure design and assessment aware of the significant changes in the new editions of RP2A and the bases for these changes. The main reference for this paper is the 20th edition of the RP2A, which has a detailed commentary, with an extensive set of reference, that discusses the basis for each element of the revised wave force procedure. The same information is also contained in the first edition of RP2A LRFD. The revised procedure was developed by the API Task Group on Wave Force Commentary. It embodies research results obtained over the last 25 years. It is a significant revision of the guideline wave force calculation procedures that have been part of RP2A since the 1976 edition. BACKGROUND The task group was formed at the request of API to write a commentary on the existing RP2A procedure. The first task group meeting was held in December 1987 to discuss objectives and scope, and procedures to archieve them. After reviewing the RP2A procedures the task group concluded that a commentary consistent with the existing guideline disign calculation procedures could not be written. A considerable body of new knowlegde on wave forces had been developed since the first guidelines appeared in the 1976 edition of RP2A. Therefore the task group decided to expand the scope by developing new guidelines and a supporting commentary. Before defining the new guidelines, the task group performed a series of wave force comparison studies to (a) ascertain the accurancy of the computer codes in performing wave force calculations for given environmental conditions, force coeffients, and structure geometry; (b) evaluate differences in Gulf of Mexico (GOM) design wave forces that were being used at that time; (c) and evaluate differences in "best" estimates of GOM 100-yr wave forces. Results of these studies showed significant differences in GOM design force levels (up to a factor of two) but better agreement in the "best" estimates of the 100-yr wave forces. And very importantly, the "best" 100-yr wave forces were considerably higher than the values obtained using RP2A. The study, its conclusions, and recommendations were presented to the API Subcommittee on Fixed Systems Criteria In October 1989. Before accepting the higher forces the task group recommended the following (a) set up an API task group to review uncertainties and biases in structural capacity; (b) have the wave force task group complete its work and expand the scope to develop 100-yr hurricane wave, wind, and current criteria for the GOM incorporating the latest hindcasts; and (c) have industry try the wave force recipe to see if it is consistent with experience in the Gulf of Mexico. The Subcommittee supported the recom

This paper presents new laboratory data on long-wave (surf-beat) forcing by the random breaking of shorter gravity water waves on a plane beach. The data include incident and outgoing wave amplitudes, together with shoreline oscillation amplitudes at long-wave frequencies, from which the correlation between forced long waves and short-wave groups is examined. A detailed analysis of the cross-shore structure of the long-wave motion is presented, and the observations are critically compared with existing theories for two-dimensional surf-beat generation. The surf beat shows a strong dependency on normalized surf-zone width, consistent with long-wave forcing by a time-varying breakpoint, with little evidence of the release and reflection of incident bound long waves for the random-wave simulations considered. The seaward-propagating long waves show a positive correlation with incident short-wave groups and are linearly dependent on short-wave amplitude. The phase relationship between the incident bound long waves and radiated free long waves is also consistent with breakpoint forcing. In combination with previous work, the present data suggest that the breakpoint variability may be the dominant forcing mechanism during conditions with steep incident short waves.

Terrain methods on spectral analysis for paleoclimate interpretations: A novel visualization technique using python

A constant drag coefficient of 0.61 was calculated over a Reynolds number range of 2×105 to 8×105 from simultaneous measurements of-wave-induced velocities and forces. The average inertia coefficient was 1. 20. The constant drag coefficient found for a Reynolds number as low as 2×105 allows a simulation of design wave force with a smaller scale space frame structure. The drag (inertia) coefficients were determined from drag (inertia11y) dominant portions of individual wave cycles. The measured wave force power spectrum agrees well with that calculated from measured velocities with average drag and inertia coefficients. INTRODUCTION The objective of this study was to establish the feasibility of measuring wave forces on a small-scale structure that could be scaled up to typical design loads on a conventional jacket-type offshore platform. It is essential to show that a supercritical flow condition (typified by constant drag coefficient) occurs over the entire structure to make such scaling possible. It is not possible, however, with existing wave-force data to show at what Reynolds number this supercritica1 condition begins, because the water-particle velocity must be inferred from the surface wave elevation. By measuring both the wave force and the particle velocity, one can remove the uncertainty due to wave theory and possible steady ocean currents affecting the calculated drag coefficient. When unambiguous data that can be scaled up to typical design loads are obtained from a smaller scale test structure, they can be used to calibrate present-day design wave-force calculations [4]. Currently used design force calculations for a space-frame structure are based on wave-force measurements on a single pile, typically the wave-force data collected by Chevron during Hurricane Carla [2,3,9]. Design waves are assumed to be smooth and long crested (two-dimensional). Actual waves, however, are neither. The spatial distribution of particle velocities calculated for idealized design waves can be different from those for real, random waves. For the same average velocities, the drag forces on structural members are subject to random variation due to turbulence. The net result of these effects can be randomly varying force vectors over the space of a structure. Because of the changing directions of force vectors, not all of the wave forces are additive. The actual structural load in real waves may be different from when the forces are assumed in the same direction over the entire structural space, as in present design wave-force calculations. Scaling Wave Forces In order to simulate one physical system with another of different size, the two systems are required to be geometrically similar. In addition to geometrical similarity, certain dimensionless physical parameters must be preserved so that the experimental results of one system can be applied to another. Such parameters can be found by dimensional analysis of the governing equations for the physical system under consideration.

When deriving a directional ocean wave spectrum from a synthetic-aperture radar (SAR) image of the ocean surface, spectral analysis of the image data is a key step. In this paper, a quantitative comparison of spectral analysis techniques for analysis of multilook SAR image data of ocean waves is presented. Performance is rated using a spectral SNR, defined as the ratio of the desired spectral signature to the speckle noise as it appears in the SAR image spectrum. Spectral techniques considered cover all of those now in use (including SAR processor focus adjustment) as well as new experimental methods. It is shown that the spectral-phase-shift technique, introduced in this paper, is the best approach: it maximizes the spectral SNR, it allows resolution of the 180 degrees directional ambiguity, and it applies simultaneously to all wave components present in the scene.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

To the Editor: In a recent issue of Circulation , Stambler et al1 provide an intriguing but possibly misleading set of results regarding the variability of atrial flutter cycle length (AFCL) and the role of the autonomic nervous system in AFCL modulation. Previous studies2 3 4 5 identified in the AFCL variability the existence of 2 rhythmic oscillations, 1 controlled by the ventricular rate and 1 by respiratory activity, suggesting a modulatory effect of atrial stretch. Using spectral analysis, Stambler et al claimed the existence of an additional low-frequency oscillation (band 1) mediated by sympathetic tone. Their conclusions are not supported by their study design and results. In fact, the newly proposed low-frequency oscillation band was concentrated in the extremely low-frequency region of the spectrum and on average was centered around 0.006±0.002 Hz (Table 2 of the article by Stambler et al). This should correspond to an AFCL oscillation with a period of 166 seconds, clearly longer than the 2 minutes of analyzed recording time. This means that we are dealing with a baseline trend rather than a rhythmic oscillation. In other words, band 1 is simply a DC component of the spectrum reflecting the nonstationary nature of the analyzed time series and thus should be avoided in the interpretation of the power spectra.6 In their study, Stambler et al also examined the role of the autonomic nervous system in the modulation of AFCL by studying the effect of pharmacological interventions on the power-band distribution of AFCL spectra. Stimulation and inhibition of sympathetic tone obtained by intravenous infusion of isoproterenol and long-term therapy with …

The spectral analysis techniques has been widely used to extract information about certain signals and the process in which those are generated. Ultrasonic (US) signal acquired from biological tissues are a particular case of that. Spectral analysis has been used to extract information from US signal related to biological tissue condition, mainly related with the internal scattering structure distribution and regularity. High-resolution spectral analysis techniques are applied to determine pathological characteristics that could indicate the presence of disease in the tissue. Some small changes in harmonics location could be drastically affected by the presence of noise in the analyzed signal. In this work, an evaluation of two parametric HR spectral analysis techniques is performed, first applied to signals acquired from a biological tissue phantom in a temperature range from 21°C to 45°C. A second evaluation was performed, considering simulated US signals, which were added with three different levels of SNR, and then they were analyzed with two parametric methods, which present variations in the error estimated for different noise level conditions. But the general behavior is a smaller error when noise decreases.

A computerized system is discussed that permits at-sea managers to anticipate best modes of operation in advance and thereby schedule accordingly. This approach employs spectral techniques to forecast motions of vessels induced by the seaway. Use of this system has permitted tighter operational control of semisubmersibles, drillships, and barges. Introduction All semisubmersibles, ship shapes, and barges respond to the kinematics of the random seaway. Indeed, the irregular vessel motions induced by ocean waves often dictate the ability of vessels to operate.The ocean varies between benign and extremely hostile, when dangerous wave conditions disrupt or prevent work. Weather-sensitive operations require prevent work. Weather-sensitive operations require that waves be within certain limits during the entire duration of a given undertaking, whether it be the placing of a construction module on a jacket, the placing of a construction module on a jacket, the raising of a blowout-prevention stack, or the handling of anchors. In these and other circumstances, the go/no-go decision depends on knowledge of the upcoming wave state and, as such, is predictive in nature.An offshore operator's problem with planning upcoming mark can be viewed as being threefold:to predict properly wave conditions in advance of occurence,to estimate the resulting vessel motions induced by the forecast waves, andto evaluate what effects these motions will have on scheduled work. All three steps are integral components of the operator's decision-making process.An operator's problem of planning work at sea never has been easy, nor has it ever been approached in a totally objective manner. With regard to the first step of the decision process, predictions of ocean waves have been recognized for a long time as often being inaccurate. This situation has been true particularly for forecasts of long-period swells that particularly for forecasts of long-period swells that seriously affect offshore operations. The problem also has been compounded by the wave forecasts usually being given only in terms of characteristic parameters, (i.e., significant heights and periods), parameters, (i.e., significant heights and periods), which has limited the utility of these forecasts in quantifying vessel motions. In short, the prediction techniques and general use have failed to keep abreast with new knowledge of wave generation, propagation, and dissipation and with advancements propagation, and dissipation and with advancements in the fields of computer simulation and the dynamic analysis of floating structures.Application of spectral wave models can help overcome these deficiencies. Why use the spectral approach? There are two basic reasons. First, if properly done, the spectral approach is the most properly done, the spectral approach is the most accurate technique for forecasting wave conditions, giving two-dimensional details of wave states that are unobtainable otherwise. Second, the spectral approach bridges the gap between wave descriptions and wave-induced loads and motions in a way consistent with modern dynamical techniques.The concept of incorporating the spectral approach into a practical wave forecasting method originated in 1953 with the work of Pierson, Neumann, and James. JPT P. 555

To the Editor: We read with interest the recent article by Elvan et al in Circulation: Arrhythmia and Electrophysiology .1 They compared the reliability of time-domain versus frequency-domain methods in determining the local activation rate in patients during atrial fibrillation (AF).2 The study provided potentially important information regarding the analysis of unipolar versus bipolar recordings. Unfortunately, essential details regarding the methods used for both the time-domain and the frequency-domain analyses were not presented. For example, information on the noise and frequency rejection criteria used for determination of AF cycle length in the time domain was nowhere to be found. Also crucial information on the …

An estimate of wave heights is needed for risk and venture analysis, for platform design, and for operational planning. Very little reliable data on hurricane waves have been available for a number of years. The present hindcast system uses a moving, two-dimensional wind field to generates and propagate waves to a location of interest. The propagate waves to a location of interest. The wind-wave model is based on work reported in the literature by Wilson. Wave Program I uses a synoptic wind field based on measurements or observations. Wave Program II generates its own wind field based on the track, the time history of the radius to maximum Winds, and the barometric pressure of the storm. Wave Program III also pressure of the storm. Wave Program III also generates its own wind fields, but the storm is moved along a predetermined path. The results of all three hindcast methods have been compared with data gathered from Hurricane Carla. Other hurricanes have also been studied and each of the programs gives comparable results. Introduction The most critical environmental factor in deepwater platform design is the selection of wave heights to which the platform will be subjected. Regardless of the design theory, wave loading contributes a major portion of the environmental force on a deep-water platform. To date there has been little sound historical evidence of the magnitude of wave heights that could occur in the Gulf of Mexico. To overcome this problem the offshore oil industry has sought an answer by two related methods. The first method consists of several measuring programs to gather both wave force and wave height information. Since reliable measuring techniques have existed for only a short time, the second method consists of developing techniques to predict historical waves that probably occurred in the Gulf of Mexico. The purpose of this paper is to document Shell's efforts in hindcasting paper is to document Shell's efforts in hindcasting waves for hurricanes that have passed through the Gulf since 1900. In order to hindcast waves, it was necessary to find a mathematical simulation model that would generate waves from a moving wind field. Such wind fields may be taken from synoptic charts or developed from empirical equations based on hurricane data such as radius to maximum winds, central pressure, and forward speed.

Geographical AnalysisVolume 13, Issue 2 p. 95-116 Free Access Maximum Entropy Spectra and the Spatial and Temporal Dimensions of Economic Fluctuations in an Urban System Claude Marchand, Claude Marchand The cartographic work of Jennifer Wilcox, University of Toronto, is gratefully acknowledged. Claude Marchand is assistant professor of geography, University of Montreal.Search for more papers by this author Claude Marchand, Claude Marchand The cartographic work of Jennifer Wilcox, University of Toronto, is gratefully acknowledged. Claude Marchand is assistant professor of geography, University of Montreal.Search for more papers by this author First published: April 1981 https://doi.org/10.1111/j.1538-4632.1981.tb00719.xCitations: 17 Claude Marchand is assistant professor of geography, University of Montreal. The cartographic work of Jennifer Wilcox, University of Toronto, is gratefully acknowledged. AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat LITERATURE CITED Bartels, C. P. A. (1977). “The structure of Regional Unemployment in the Netherlands. Regional Science and Urban Economics, 7, 103– 5. Bartels, C. P. A., M. Booleman, and W. H. Peters (1978). “A Statistical Analysis of Regional-Unemployment Series. Environment and Planning A, 10, 937– 54. Bennett, R. J. (1979). Spatial Time Series: Analysis—Forecasting—Control. London: Pion. Brechling, F. (1967). “Trends and Cycles in British Regional Unemployment. Oxford Economic Papers, 19, 1– 21. Burg, J. P. (1968). A New Analysis Technique for Time Series Data. Netherlands: Advanced Study Institute in Signal Processing. Bums, F., and W. Mitchell (1947). Measuring Business Cycles. New York: National Bureau of Economic Research. Cho, D. W., and D. S. McDougall (1978). “Regional Cyclical Patterns and Structure, 1954-1975. Economic Geography, 54, 66– 74. Fishman, G. S. (1969). Spectral Methods in Econometrics. Cambridge, Mass.: Harvard University Press. Granger, C. W. J. (1966). “The Typical Spectral Shape of an Economic Variable. Econometrica, 24, 150– 61. Granger, C. W. J., and M. Hatanaka (1964). Spectral Analysis of Economic Time Series, Princeton, N. J.: Princeton University Press. Haggett, P. (1975). “ Time Series Comparison: Unemployment. In Elements of Spatial Structure, edited by A. D. Cliff et al, Cambridge: Cambridge University Press. Hanna, F. A. (1954). “Cyclical and Secular changes in State per Capita Incomes, 1920-1950. Review of Economics and Statistics, 36, 320– 30. Hansen, A. H. (1951). Business Cycles and the National Income, New York: W. W. Norton. Harris, C. P., and A. P. Thirlwall (1968). “Interregional Variations in Cyclical Sensitivity to Unemployment in the U.K. 1949-1964. Bulletin of the Oxford University Institute of Economics and Statistics, 55– 66. Hepple, L. (1975). “ Spectral Techniques and the Study of Interregional Economic Cycles.” In Processes in Physical and Human Geography, edited by R. Peel, M. Chisholm, and P. Haggett, pp. 392– 408. London: Heinmann. Jeffrey, D. (1974). “Regional Fluctuations in Unemployment Within the Australian Urban Economic System: A Study of the Spatial Impact of Short Term Economic Change. Economic Geography, 50. Jeffrey, D. and D. J. Webb (1972). “Economic Fluctuations in the Australian Regional System 1955-70. Australian Geographical Studies, 10, 141– 60. Jenkins, G. M., and D. G. Watts (1968). Spectral Analysis and its Applications, San Francisco: Holden-Day. Kanasewich, E. R. (1973). Time Sequence Analysis in Geophysics. Edmonton: The University of Alberta Press. King, L., E. Casetti, and D. Jeffrey (1969). “Economic Impulses in a Regional System of Cities: A Study of Spatial Interaction. Regional Studies, 3, 213– 18. King, L., E. Casetti, and D. Jeffrey (1974). “Cyclical Fluctuations in Unemployment Levels in the U.S. Metropolitan Areas. Tidjdschrift Voor Economische en Social Geographie, 50, 345– 52. King, L. J., and G. R. Clark (1978). “Regional Unemployment Patterns and the Spatial Dimensions of Macro-Economic Policy: The Canadian Experience 1966-1975. Regional Studies, 12, 283– 96. Lacoss, R. T. (1971). “Data Adaptative Spectral Analysis Methods. Geophysics, 36, 661– 75. Schumpeter, J. (1935). “The Analysis of Economic Change. Review of Economic Statistics, 17, 1– 10. Thompson, W. R. (1965). A Preface to Urban Economics. Baltimore: Johns Hopkins University Press. Thompson, W. R. (1975). “ Internal and External Factors in the Development of Urban Economies.” In Regional Policy: Readings in Theory and Applications, edited by J. Friedman and W. Alonso, pp. 210– 20. Cambridge, Mass.: M. I. T. Press. Tiebout, T. M. (1975). “ Exports and Regional Economic Growth.” In Regional Policy: Readings in Theory and Applications, edited by J. Friedman and W. Alonso, pp. 348– 52. Cambridge, Mass.: M. I. T. Press. Citing Literature Volume13, Issue2April 1981Pages 95-116 ReferencesRelatedInformation

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For the traditional polyethylene and nylon nets, lots of studies have been carried out to study their hydrodynamic characteristics in waves and currents. However, the studies of the metal nets which also have wide application prospect in marine aquaculture are rare, especially on their performance in waves. In this study, a series of laboratory experiments are conducted to investigate the hydrodynamic characteristics of the chain-link type aluminum alloy nets. Two net panels of identical dimensions are placed in the ocean basin. They are parallel to each other, with a certain length of gap. The wave forces on the net panels under different wave heights, wave periods and immersion depths are measured. The wave elevations at different downstream positions of the nets and the wave forces on both upstream and downstream net panels are measured to investigate the shielding effects. The wave transmission coefficient and shielding coefficient of the horizontal wave force are therefore derived. The experimental results show that both two coefficients are around 1 under different wave conditions which indicates that the shielding effects of the chain-link type aluminum alloy nets can be ignored. Thereby, in the calculation of wave loads on upstream and downstream fish nets, it is reasonable to neglect the wave attenuation inside the nets.