Predicting scour depth around non-uniformly spaced pile groups

Pile scour may cause instability to the structures they support. Ensuring a safe and economically sound design is essential for the wider community. Although much laboratory research has been carried out on scour at pile groups, there are still significant gaps in prediction formulae. This study has been conducted to develop a formula for scour at pile arrangements of non-uniform spacing. The study was based on a laboratory experiment found in the literature. Previous empirical formulae for uniformly spaced pile groups were first used to gauge an idea of their performance. The formula that predicted the scour depth more accurately was then modified. The approach of Ghaemi et al. (2013) outperformed the other trialled empirical formulas. Using this formula, a correction factor was suggested to increase the prediction accuracy. The gap to diameter ratio was also corrected to include the non-uniformity of spacing in two directions

How does the driver's Perception Reaction Time affect the performances of crash surrogate measures?

© 2015 Kuang et al. With the merit on representing traffic conflict through examining the crash mechanism and causality proactively, crash surrogate measures have long been proposed and applied to evaluate the traffic safety. However, the driver's Perception-Reaction Time (PRT), an important variable in crash mechanism, has not been considered widely into surrogate measures. In this regard, it is important to know how the PRT affects the performances of surrogate indicators. To this end, three widely used surrogate measures are firstly modified by involving the PRT into their crash mechanisms. Then, in order to examine the difference caused by the PRT, a comparative study is carried out on a freeway section of the Pacific Motorway, Australia. This result suggests that the surrogate indicators' performances in representing rear-end crash risks are improved with the incorporating of the PRT for the investigated section

Spatial changes of beach profiles for a small tidal inlet (Currumbin Creek, Australia)

Many tidal inlets are actively monitored to investigate the change in flood or ebb shoals, as these sand deposits can have a major influence on the sediment budget of the adjacent coast. However, here it is hypothesized that the shores of the back barrier area can also act as a source of sediment to be considered in the sediment budget. Therefore, profile changes around Currumbin Creek tidal inlet were considered to identify the extent of such a contribution on the surrounding beach and the overall evolution of the inlet system. The results of 16 weeks survey showed that in general, the shores of the back barrier lagoon had a very marginal effect in the provision of material to the sand budget, although the gorge area is highly vulnerable and dynamic. Even an intense storm event and heavy rainfall during the data collection period, resulting in erosion of the surrounding beaches, showed no significant influence on the shore face of the lagoon

Wave height forecasting in Dayyer, the Persian Gulf

Forecasting of wave parameters is necessary for many marine and coastal operations. Different forecasting methodologies have been developed using the wind and wave characteristics. In this paper, artificial neural network (ANN) as a robust data learning method is used to forecast the wave height for the next 3, 6, 12 and 24 h in the Persian Gulf. To determine the effective parameters, different models with various combinations of input parameters were considered. Parameters such as wind speed, direction and wave height of the previous 3 h, were found to be the best inputs. Furthermore, using the difference between wave and wind directions showed better performance. The results also indicated that if only the wind parameters are used as model inputs the accuracy of the forecasting increases as the time horizon increases up to 6 h. This can be due to the lower influence of previous wave heights on larger lead time forecasting and the existing lag between the wind and wave growth. It was also found that in short lead times, the forecasted wave heights primarily depend on the previous wave heights, while in larger lead times there is a greater dependence on previous wind speeds

Modelling of flow around hexagonal and textured cylinders

The flow regime around a hexagonal polygon with low Reynolds numbers Re<200 is numerically investigated in two different orientations namely face-oriented and corner-oriented. The basic flow characteristics, including drag coefficient, lift coefficient, Strouhal number and critical Reynolds number of the hexagonal cylinders, are calculated using 2D transient numerical analysis. Within the studied range of Re, the predicted lift coefficient and Strouhal number of the face-oriented hexagon were higher than those of the corner-oriented hexagon. In contrast, the predicted drag coefficient and critical Reynolds number of the corner-oriented hexagon were greater than those of the face-oriented. Flow characteristics of a novel textured geometry are also studied using 3D transient analysis. The Strouhal number St of the textured geometry was found to be in between the St of both the hexagonal cylinders, and its lift coefficient is lower than that of the hexagonal cylinders

Uncertainties in wave-driven longshore sediment transport projections presented by a dynamic CMIP6-based ensemble

In this study four experiments were conducted to investigate uncertainty in future longshore sediment transport (LST) projections due to: working with continuous time series of CSIRO CMIP6-driven waves (experiment #1) or sliced time series of waves from CSIRO-CMIP6-Ws and CSIRO-CMIP5-Ws (experiment #2); different wave-model-parametrization pairs to generate wave projections (experiment #3); and the inclusion/exclusion of sea level rise (SLR) for wave transformation (experiment #4). For each experiment, a weighted ensemble consisting of offshore wave forcing conditions, a surrogate model for nearshore wave transformation and eight LST models was used. The results of experiment # 1 indicated that the annual LST rates obtained from a continuous time series of waves were influenced by climate variability acting on timescales of 20-30 years. Uncertainty decomposition clearly reveals that for near-future coastal planning, a large part of the uncertainty arises from model selection and natural variability of the system (e.g., on average, 4% scenario, 57% model, and 39% internal variability). For the far future, the total uncertainty consists of 25% scenario, 54% model and 21% internal variability. Experiment #2 indicates that CMIP6 driven wave climatology yield similar outcomes to CMIP5 driven wave climatology in that LST rates decrease along the study area’s coast by less than 10%. The results of experiment #3 indicate that intra- and inter-annual variability of LST rates are influenced by the parameterization schemes of the wave simulations. This can increase the range of uncertainty in the LST projections and at the same time can limit the robustness of the projections. The inclusion of SLR (experiment #4) in wave transformation, under SSP1-2.6 and SSP5-8.5 scenarios, yields only meagre changes in the LST projections, compared to the case no SLR. However, it is noted that future research on SLR influence should include potential changes in nearshore profile shapes

Uncertainties in the projected patterns of wave-driven longshore sediment transport along a non-straight coastline

This study quantifies the uncertainties in the projected changes in potential longshore sediment transport (LST) rates along a non-straight coastline. Four main sources of uncertainty, including the choice of emission scenarios, Global Circulation Model-driven offshore wave datasets (GCM-Ws), LST models, and their non-linear interactions were addressed through two ensemble modelling frameworks. The first ensemble consisted of the offshore wave forcing conditions without any bias correction (i.e., wave parameters extracted from eight datasets of GCM-Ws for baseline period 1979–2005, and future period 2081–2100 under two emission scenarios), a hybrid wave transformation method, and eight LST models (i.e., four bulk formulae, four process-based models). The differentiating factor of the second ensemble was the application of bias correction to the GCM-Ws, using a hindcast dataset as the reference. All ensemble members were weighted according to their performance to reproduce the reference LST patterns for the baseline period. Additionally, the total uncertainty of the LST projections was decomposed into the main sources and their interactions using the ANOVA method. Finally, the robustness of the LST projections was checked. Comparison of the projected changes in LST rates obtained from two ensembles indicated that the bias correction could relatively reduce the ranges of the uncertainty in the LST projections. On the annual scale, the contribution of emission scenarios, GCM-Ws, LST models and non-linear interactions to the total uncertainty was about 10–20, 35–50, 5–15, and 30–35%, respectively. Overall, the weighted means of the ensembles reported a decrease in net annual mean LST rates (less than 10% under RCP 4.5, a 10–20% under RCP 8.5). However, no robust projected changes in LST rates on annual and seasonal scales were found, questioning any ultimate decision being made using the means of the projected changes

The modification of bottom boundary layer turbulence and mixing by internal waves shoaling on a barrier reef

Author Posting. © American Meteorological Society, 2011. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Physical Oceanography 41 (2011): 2223–2241, doi:10.1175/2011JPO4344.1.Results are presented from an observational study of stratified, turbulent flow in the bottom boundary layer on the outer southeast Florida shelf. Measurements of momentum and heat fluxes were made using an array of acoustic Doppler velocimeters and fast-response temperature sensors in the bottom 3 m over a rough reef slope. Direct estimates of flux Richardson number Rf confirm previous laboratory, numerical, and observational work, which find mixing efficiency not to be a constant but rather to vary with Frt, Reb, and Rig. These results depart from previous observations in that the highest levels of mixing efficiency occur for Frt < 1, suggesting that efficient mixing can also happen in regions of buoyancy-controlled turbulence. Generally, the authors find that turbulence in the reef bottom boundary layer is highly variable in time and modified by near-bed flow, shear, and stratification driven by shoaling internal waves.Funding was provided by grants from the National Oceanic and Atmospheric Administration’s National Undersea Research Program, National Science Foundation Grants OCE-0622967 and OCE- 0824972 to SGM, and the Singapore Stanford Program. Kristen Davis was supported by a National Defense Science and Engineering Graduate Fellowship and an ARCS Foundation Fellowship

Predicting wave run-up on rubble-mound structures using M5 model tree

Prediction of run-up level is a key task in design of the coastal structures. For the design of the crest level of coastal structures, the wave run-up level with a 2% exceedance probability, Ru2%, is most commonly used. In this study, the performance of M5 model tree for prediction of the wave run-up on rubble-mound structures was investigated. The main advantage of model trees, unlike the other soft computing tools, is their easier use and more importantly their understandable mathematical rules. Experimental data set of Van der Meer and Stam was used for developing model trees. The conventional governing parameters were selected as the input variables and the obtained results were compared with Van der Meer and Stam's formula, recommended by the Coastal Engineering Manual (CEM, 2006). The predictive accuracy of the model tree approach was found to be superior to that of Van der Meer and Stam's empirical formula. Furthermore, to judge the generalization capability of the model tree method, the model developed based on laboratory data set was validated with the prototype run-up measurements on the Zeebrugge breakwater, Belgium. Results show that the model tree is more accurate than empirical formulas and TS Fuzzy approach in estimating the full-scale run-up

Prediction of tidal excursion length in estuaries due to the environmental changes

Tidal excursion is an important parameter that indicates hydraulic and mixing characteristics of estuarine environments. Prediction of the tidal excursion length provides a proper tool for environmental management of estuaries. In this study, the governing equations of the salinity transport were scaled first to recognize the effective dimensionless parameters of tidal excursion length. Then, a laterally averaged two-dimensional numerical model called CE-QUAL-W2 was used as a virtual laboratory to simulate the salinity intrusion length. Existing field data of Limpopo estuary, as a case study, was used for calibration and verification of the model and reasonable agreement was observed between the model results and the field data. Finally, the verified model was used to assess the influences of the governing parameters. The results showed that simple power functions can be used to describe the effects of dimensionless parameters obtained by scaling of the governing equations. As a result, a new formula in form of a power function was derived to predict the tidal excursion length based on the geometric and hydrodynamic characteristics of alluvial estuaries. Comparison of the computed tidal excursion lengths using the derived formula with the observed measurements in several estuaries showed the robustness of the developed formula