Stratigraphic forward modelling (SFM) provides the means to produce geologically coherent and realistic models. In this paper, we demonstrate the possibility of matching lithological variability simulated with a basin...
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Stratigraphic forward modelling (SFM) provides the means to produce geologically coherent and realistic models. In this paper, we demonstrate the possibility of matching lithological variability simulated with a basin-scale advection-diffusion SFM to a data-rich real-world setting, i.e. the Holocene Rhine-Meuse fluvio-deltaic system in the Netherlands. SFM model calibration to real-world data in general has proven non-trivial. This study focuses on a novel inversion process constrained by the top surface and the sand proportion observed at specific pseudo-wells in the study area. Goodness-of-fit expressed by a new fitness function gives the error calculated as the average of two calibration constraints. Computational efficiency was increased significantly by implementing a new optimization process in two hierarchical steps: a) optimization in terms of sediment load and discharge, which are the most influential parameters having the largest uncertainty and b) optimization with respect to the remaining uncertain parameters, these being sediment transport parameters. The calibration process described allows for the most optimal combination of achieving acceptable levels of goodness-of-fit, feasible runtimes and multiple (non-unique) solutions to obtain synthetic stratigraphic output best matching real-world datasets. By removing model realizations which are geologically unrealistic, calibrated SFM models provide a multiscale stratigraphic framework for reconstructing static models of reservoirs which are consistent with the palaeogeographic layout, basin-fill history and external drivers (e.g. sea level, sediment supply). The static reservoir models that are matched with highest certainty therefore contain the highest geological realism and may be used to improve deep subsurface reservoir or aquifer property prediction. The new methodology was applied to the well-established Holocene Rhine-Meuse dataset, which allows a rigorous testing of the optimization;the calibrate
A new bridge weigh-in-motion (WIM) algorithm is developed which makes use of strain sensors at multiple longitudinal locations of a bridge to calculate axle weights. The optimisation procedure at the core of the propo...
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A new bridge weigh-in-motion (WIM) algorithm is developed which makes use of strain sensors at multiple longitudinal locations of a bridge to calculate axle weights. The optimisation procedure at the core of the proposed algorithm seeks to minimise the difference between static theory and measurement, a procedure common in the majority of bridge WIM algorithms. In contrast to the single unique value calculated for each axle weight in common Bridge WIM algorithms, the new algorithm provides a time history for each axle based on a set of equations formulated for each sensor at each scan. Studying the determinant of this system of equations, those portions of the time history of calculated axle weights for which the equations are poorly conditioned are removed from the final reckoning of results. The accuracy of the algorithm is related to the ability to remove dynamics and the use of a precise influence line. These issues are addressed through the use of a robust moving average filter and a calibration procedure based on using trucks from ambient traffic. The influence of additional longitudinal sensor locations on the determinant of the system of equations is discussed. Sensitivity analyses are carried out to analyse the effect of a misread axle spacing or velocity on the predictions, and as a result, the algorithm reveals an ability to identify potentially erroneous predictions. The improvement in accuracy of the calculated axle weights with respect to common approaches is shown, first using numerical simulations based on a vehicle-bridge interaction finite-element model, and second using experimental data from a beam-and-slab bridge in Slovenia.
A modified two-dimensional (2D) Moses algorithm for acquiring the field-calibrated influence line (IL) of an existing bridge is presented, based on strain data acquired continuously at a high scanning rate with calibr...
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A modified two-dimensional (2D) Moses algorithm for acquiring the field-calibrated influence line (IL) of an existing bridge is presented, based on strain data acquired continuously at a high scanning rate with calibration vehicles of known axle weights and axle spacings crossing an instrumented bridge. Considering the transverse distribution of the wheel loads on each girder attributable to the 2D behavior of the slab-girder bridge, the IL of each of the girders can be calculated, which does not require the girders to possess identical material and geometric properties. By using the calculated IL of each girder as a reference, a modified 2D Moses algorithm was derived to identify axle weights of moving vehicles, taking into consideration the transverse distribution of the wheel loads on each girder. Mathematical equations to calculate ILs and axle weights were derived, and the proposed algorithms were implemented by a computer program. The accuracy of the IL calculation and axle weight identification was verified through a field test of a bridge on U.S. Route 78 in Alabama. The identified axle weights showed agreement with the static measurements from weighing pads and with results from the bending-plate weigh-in-motion (BPWIM) system near the instrumented bridge.
Through the assimilation of present-day mantle seismic structure, adjoint methods can be used to constrain the structure of the mantle at earlier times, i.e., mantle initial conditions. However, the application to geo...
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Through the assimilation of present-day mantle seismic structure, adjoint methods can be used to constrain the structure of the mantle at earlier times, i.e., mantle initial conditions. However, the application to geophysical problems is restricted through both the high computational expense from repeated iteration between forward and adjoint models and the need to know mantle properties (such as viscosity and the absolute magnitude of temperature or density) a priori. We propose that an optimal first guess to the initial condition can be obtained through a simple backward integration (SBI) of the governing equations, thus lessening the computational expense. Given a model with known mantle properties, we show that a solution based on an SBI-generated first guess has smaller residuals than arbitrary guesses. Mantle viscosity and the effective Rayleigh number are crucial for mantle convection models, neither of which is exactly known. We place additional constraints on these basic mantle properties when the convection-induced dynamic topography on Earth's surface is considered within an adjoint inverse method. Besides assimilating present-day seismic structure as a constraint, we use dynamic topography and its rate of change in an inverse method that allows simultaneous inversion of the absolute upper and lower mantle viscosities, scaling between seismic velocity and thermal anomalies, and initial condition. The theory is derived from the governing equations of mantle convection and validated by synthetic experiments for both one-layer viscosity and two-layer viscosity regionally bounded spherical shells. For the one-layer model, at any instant of time, the magnitude of dynamic topography is controlled by the temperature scaling while the rate of change of topography is controlled by the absolute value of viscosity. For the two-layer case, the rate of change of topography constrains upper mantle viscosity while the magnitude of dynamic topography determines the tempe
Spring back is the inevitable phenomenon in plates forming,and the ascertain amount of spring back compensation is the key of the design of plates parts forming *** a new kind of counting method of panel bending sprin...
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Spring back is the inevitable phenomenon in plates forming,and the ascertain amount of spring back compensation is the key of the design of plates parts forming *** a new kind of counting method of panel bending spring back is given here which offers the inverse algorithm of mould bending radius before *** some certain examples,it gives the numerical simulation with the help of finite element *** result shows that the forming precision has been greatly increased after compensation.
In order to respond to the national policy of energy saving and consumption reduction, the temperature drop formula of annular pipeline should be established to optimize the water mixing temperature and water mixing f...
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In order to respond to the national policy of energy saving and consumption reduction, the temperature drop formula of annular pipeline should be established to optimize the water mixing temperature and water mixing flow. The traditional temperature drop formula applies the high water cut actual situation to 13.7%. On the basis of the traditional Schulhof temperature drop formula, the influence of hydraulic friction on the oil flow temperature is calculated by the calculus idea. The heat transfer coefficient of the pipeline under the complex condition is obtained by the inverse algorithm, and the water mixing flow and water temperature are simulated with MATLAB. The function surface diagram of the degree and the back station temperature. The actual error can be reduced to 4.8%, and the return station temperature can be optimized by 7 degrees.
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