Physical Model Data Research Articles

Spherical multifocusing method for irregular topography

Moveout correction for irregular topography has been a longstanding challenge in processing seismic exploration data. Irregular topography usually results in large moveout among traces, a low signal-to-noise ratio (S/N), and difficulty in modeling near-surface velocities. Conventional normal moveout (NMO) corrections and elevation static methods are imprecise and tend to introduce significant errors for large offsets. Over the past two decades, several multiparameter time corrections and stacking techniques to reduce noise and improve resolution have been proposed in place of the classic NMO and common-midpoint stack. These include the common-reflection-surface (CRS), common-offset CRS, nonhyperbolic CRS, implicit CRS, multifocusing (MF), irregular surface MF (IS-MF), spherical MF (SMF), and common-offset MF methods. Various CRS-type operators that consider the top-surface topography have been proposed. For MF-type operators, only IS-MF can be applied directly to the irregular topography with no elevation statics required. In this study, we have developed a new MF formulation, modifying the SMF method to consider nonzero elevations of sources and receivers and we corrected moveout of nonplanar data directly without prior elevation static corrections. The proposed extension combines the sensitivity to spherical reflectors of SMF with the applicability of the IS-MF method to irregular topography. We investigated the behavior of the new operator using a physical model data set and compared the results with those from the conventional IS-MF method. The results revealed that the new operator is more robust over a wide range of source and receiver elevations and has advantages on strongly curved interfaces. We also confirmed the potential of the proposed approach by comparing stacking results for a real-land data set with a low S/N.

Below the Data Range Prediction of Soft Computing Wave Reflection of Semicircular Breakwater

Coastal defenses such as the breakwaters are important structures to maintain the navigation conditions in a harbor. The estimation of their hydrodynamic characteristics is conventionally done using physical models, subjecting to higher costs and prolonged procedures. Soft computing methods prove to be useful tools, in cases where the data availability from physical models is limited. The present paper employs adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN) models to the data obtained from physical model studies to develop a novel methodology to predict the reflection coefficient (Kr) of seaside perforated semicircular breakwaters under low wave heights, for which no physical model data is available. The prediction was done using the input parameters viz., incident wave height (Hi), wave period (T), center-to-center spacing of perforations (S), diameter of perforations (D), radius of semicircular caisson (R), water depth (d), and semicircular breakwater structure height (hs). The study shows the prediction below the available data range of wave heights is possible by ANFIS and ANN models. However, the ANFIS performed better with R2 = 0.9775 and the error reduced in comparison with the ANN model with R2 = 0.9751. Study includes conventional data segregation and prediction using ANN and ANFIS.

Sparse Bayesian Learning-Based Seismic High-Resolution Time-Frequency Analysis

Time-frequency (TF) analysis is a useful tool for seismic data processing and interpretation. We introduce sparse Bayesian learning (SBL) to TF analysis and propose a new SBL-based high-resolution TF method. The method decomposes the seismic trace into a series of Ricker wavelets using SBL-based sparse representations and subsequently implements Wigner-Ville distribution (WVD) on the decomposed wavelets to produce TF spectra. By iteratively solving a Bayesian maximum posterior and a type-II maximum likelihood, SBL-based decomposition can sequentially obtain an optimal number of Ricker wavelets with different peak frequencies or phases from a preset wavelet dictionary, and can simultaneously invert for the associated sparse TF pseudoreflectivity with the prediction uncertainty. The WVD of SBL-based decomposed wavelets can assemble TF distribution of the reconstructed signals to approximately characterize WVD of the original data. Therefore, the linear stack of WVD of all decomposed independent wavelets is immune from both the notorious cross-term interferences of the traditional WVD and random noise. Synthetic data example involving thin beds and laboratorial physical modeling data example involving several known multicave combinations are used to demonstrate the effectiveness of the proposed SBL-based TF analysis method and illustrate its advantages over WVD and the orthogonal matching pursuit-based TF analysis method. The 3-D real seismic data example is adopted to test its application potential for interpreting deep channels and the karst slope fracture zone. The results show that the proposed SBL-based TF method is a potentially effective, stable and high-resolution seismic TF analysis tool even in the presence of thin beds.

3D Tomographic Inversion of TEM Sounding Data

Abstract —One of the main objectives of geoelectric prospecting is mapping of the consolidated low-conductivity basement geometry. To resolve the issue, it will be equally important to delineate local structures at the bottom of the sedimentary complex and to estimate the misinterpretation of results due to the presence of areas with nonuniform conductivity in the stratified geologic cross section. Another relevant objective of EM sounding is to resolve the problem of delineation of anticlinal oil and gas traps. The horizontally layered model with a local inclusion of 3D abnormal areas is certain to fit for the above-mentioned objectives. The study is concerned with the technique of nonstationary EM sounding. When applied for the solution of structural problems, this technique considers the uniform distribution of fields within relatively large volume units of the space explored. Consequently, it results in the more efficient application of the perturbation technique (Born approximation) for the solution of the forward electrodynamics problem. The study presents the findings of 3D tomographic inversion with the use of synthetic and physical modeling data. They definitely allow us to acknowledge that the proposed mathematical apparatus for 3D inversion based on Born linearization of the forward problem has proved to be quite applicable.

AVAZ inversion for fracture weakness based on three-term Rüger equation

Fracture is one of the most important migration channels and accumulation spaces in hydrocarbon reservoirs. For unconventional hydrocarbon reservoirs, especially for shale reservoirs, the accurate prediction of fracture distribution can help improve the hydrocarbon production. With the development of seismic monitoring techniques, wide-azimuth acquisition and processing techniques are being increasingly used to describe the distribution of subsurface factures. The P-wave AVAZ inversion based on seismic anisotropy is one of the most important and commonly used methods for fracture prediction. In this paper, we develop an inversion algorithm to acquire the normal and tangential fracture weakness based on P-wave reflection anisotropy and wide-azimuth seismic data. The newly developed algorithm can effectively utilize the amplitude information of large offset data to retrieve the fracture weakness which is related to the fracture density and fluid fillings. Two synthetic data examples show that the fracture weakness can be accurately estimated by using the newly proposed AVAZ inversion method. Our inversion method can obtain reliable fracture identification results even when seismic data are contaminated by random noise, which demonstrates the reliability and noise resistance of the inversion method. Finally, the method is successfully applied to a 3-D physical model data with an equivalent area of 100 km2. The predicted fracture distribution result is consistent with the designed physical model and is highly related to the locally geological structures of the target reservoir. Through synthetic and physical model data studies, we demonstrate that the proposed inversion method is an effective approach to directly evaluate the fracture distribution in the reservoir.

A Cyber-Physical Production System Framework of Smart CNC Machining Monitoring System

Computer numerical control (CNC) machine tools are now moving toward high precision, high speed, and complex functional machining. Machining monitoring system is important to achieve intelligent control of machining process to produce complex geometric features and precision parts. Traditional NC machining monitoring system is limited in data features, low in adaptability, and slow in transmission efficiency, and hard to achieve intelligent online assessment. To overcome these difficulties, this study proposes a smart monitoring system for CNC machining based on Cyber-Physical Production System (CPPS) framework. It is built on the CNC machine tool physical and virtual modeling, process monitoring, and big data analytics, and then synergized into a system through a distributed network. Under the CPPS framework, the smart monitoring system is divided into control layer, network layer, and decision layer. The function of each layer and the key technologies of the CPPS involved are discussed. Case studies of machining process monitoring are studied in the applications.

A correct validation of the National Solar Radiation Data Base (NSRDB)

The physical solar model (PSM) data from the National Solar Radiation Data Base offers half-hourly and hourly satellite-derived irradiance data on a regular 0.04°×0.04° grid over most of America, from 1998 to 2016. Previously in “The National Solar Radiation Data Base (NSRDB)” [Renewable & Sustainable Energy Reviews 89 (2018) 51–60] and “Evaluation of the National Solar Radiation Database (NSRDB): 1998–2015” [National Renewable Energy Laboratory technical report NREL/TP-5D00-67722], the accuracy of the PSM data is validated against the ground data from the SURFRAD network. Unfortunately, those validations appear to be incorrect, most likely due to a data-aggregation issue. Whereas the PSM data is valuable for solar system design, simulation and evaluation, the high data uncertainty reported limits the confidence in using the dataset. The validation of the PSM data is herein reiterated. It is found that the actual uncertainty is much lower than those reported earlier.

Using salt tectonic structures as proxies to reveal post-rift crustal tectonics: The example of the Eastern Sardinian margin (Western Tyrrhenian Sea)

Abstract The METYSS project (Messinian Event in the Tyrrhenian from Seismic Study) is based on high-resolution seismic data acquired along the Eastern Sardinian margin, Western Tyrrhenian Sea. The main aim is to study the Messinian Salinity Crisis (MSC) in the Western Tyrrhenian Basin, but we also investigated the thinning processes of the continental crust and the timing of crustal vertical movements across this backarc domain. Our first results shown that rifting ended before the MSC, but that crustal activity persisted long after the end of the rifting. This has been particularly observed on the proximal margin, the East-Sardinia Basin, where the Mobile Unit (MU, mobile Messinian salt) is thin or absent. In this study, we examined the distal margin, the Cornaglia Terrace, where the MU accumulated during the MSC and acted as a decollement, thus potentially decoupling the basement from the sedimentary cover. Our observations provide evidence for lateral flow and gravity gliding of the salt and its brittle sedimentary overburden along local basement slopes generated by the post-MSC tilting of some basement blocks formerly generated during the rifting. We also investigated an intriguing wedge-shaped body of MU located in a narrow N-S half graben bounded to the west by a major, east-dipping, crustal normal fault. Classically, one could think that this salt wedge is related to the syn-tectonics deposition of the MU, but we propose an original scenario, in which the post-rift vertical motion of the major fault has been cushioned by lateral flow of an initially tabular salt layer, leaving the supra-salt series apparently unaffected by the crustal motions of the basement. We tested this scenario by comparing natural data and physical (analogue) modelling data. Our results reveal that salt tectonics provides a powerful tool to understand the deep crustal tectonics of the margin and to constrain the timing of vertical motions in the Western Tyrrhenian Basin, results that can be applied to rifted salt-bearing margins worldwide.

Influence of Clay on Time Domain Induced Polarization

The main problem in mineral exploration is how to determine the existence of deposits at subsurface based on resistivity and chargeability parameters. Clay almost exists in rocks. Here, this study was to understand the influence of clay on time domain induced polarization. To clarify the clay parameters, field physical modeling was conducted. The results showed physical modeling data of 20-cm diameter spherical target with a total content of 28.3% of iron did not show any significant response. The high content of clays on the medium used in field physical modeling seems to be the main reason for the change in sample. In the case of the subsurface spherical model that is near to the soil medium, the presence of clay leads to the medium resistivity value to be identical to the target value. As a consequence, the resistivity response can not be identified clearly. The chargeability between the medium and the target remains small but the chargeability response remains constant.

Variation of hydraulic parameters with different wing of a T-shape spur dike in bend channels

In the present research, by using a numerical model, some analyses were performed on flows around a T-shape spur dike and a support structure located at its upstream under different wing to length ratios of T-shape spur dike in the order of 0.25, 0.50, 0.75 and 1.00. In order to verify numerical model, physical model data were used in presence of a single T shape spur dike. Results from numerical model are desirably in agreement with those of physical one because the regression between both data is 0.86 up to 0.92. In this research, all hydraulic parameters of flows, streamlines and dimensions of flow separation zones were studied in order to select the most practical model. Increased W/L results in 7%–12% increase in the length of flow separation zone and in 2% increase in the width of this zone compared to W/L=0.25.

Carbonate Reservoirs study by seismic inversion using a physical modeling data

The storage spaces of Karsts carbonate reservoir are characterized as heterogeneity. Due to low signal to noise ratio, seismic inversion using partially stacked data is often used to characterize the carbonate reservoir. A physical model is used to analyze influence of seismic inversion on heterogeneity. On the one hand, the difference in lateral resolution is quantitatively studied. On the other hand, the influence of noise on the lateral resolution in seismic inversion is discussed by adding random noise of different degree. The results demonstrate that the signal to noise ratio can be improved by seismic inversion while the lateral resolution is reduced subsequently. Additionally, random noise influences the lateral resolution, that is, the inverted volume of heterogeneity become smaller as the noise increased.

Analysis of the Thermophysical Processes and Operating Modes of Electrothermic Reactor Using a Computer Model

Based on the proposed algorithm for the computer simulation of thermophysical processes in an electrothermal ore-reduction reactor, the finite element method was used to analyze the regime parameters of the working volume. In this case, the computer calculation of the interconnected thermal-hydraulic fields has been carried out for the entire volume of the reactor. A comparison of the results of the computational experiment with the experimental data on the reactor survey and physical modeling data has shown quite satisfactory agreement. Based on an analysis of the reactor operation modes, regime maps have been presented that provide an idea of the change in technical and economic indicators depending on the control parameters. This information allows operators to know the trends in the behavior of the reactor when the regime changes.

Real-Time Localization for Underwater Moving Object Using Precalculated DC Electric Field Template

Underwater object detection and tracking are of considerable interest in offshore defense. Recently, a new method that takes advantage of direct-current resistivity survey techniques has been introduced as a complement to the conventional detection method for use in acoustically noisy conditions. However, dedicated rapid target localization methods are required to enable real-time tracking in this detection method. Therefore, in this paper, we propose a real-time localization method using grid-based template matching. The main features of our method are as follows: 1) measurement data sets from two separate detection lines are used; 2) template matching based on correlation is used; 3) the templates are precalculated by numerical modeling; and 4) real-time localization processing is implemented by efficient calculations. To verify our method, we first performed experiments for stationary target object positions under a water tank condition: template versus numerical modeling data and template versus physical modeling data. Next, real-time localization experiments for a moving target in the water tank were conducted using the real-time data at 3-Hz refresh rate. In the real-time experiments, we confirmed that the estimated positions could keep track of the actual target positions continuously. We expect that this paper will contribute positively to offshore defense and surveillance.

Study on the Compaction Effect Factors of Lime-treated Loess Highway Embankments

Morning-glory spillways are usually used in dams constructed in narrow valleys or those on steeply sloped supports. Furthermore, one can adopt this type of spillway in cases where guiding and diversion tunnels of adequate diameter are available. One of positive characteristics of these spillways is that, their maximum capacity can be approached at relatively low head. This characteristic can be seen as an advantage in cases wherein maximum outflow from the spillway shall be limited. On the other hand, should water head on top of the spillway exceeds the project baseline head, changes in output discharge will be negligible. Morning-glory spillways are commonly used in large dam construction projects across Iran (e.g. Sefid-Rood Dam, Alborz Dam, Haraz Dam, etc.). Given that spillway is one of the most important axillary structures for dams, accurate and realistic characterization of the hydraulic conditions affecting them seems to be necessary. On this basis, the present research is aimed at accurate determination of flow behavior and discharge coefficient of morning-glory spillways from the flow inlet down to horizontal tunnel of the morning-glory spillway of Haraz Dam. For this purpose, the most significant hydraulic parameters (including flow depth, flow velocity, flow pressure at different sections of the spillway, and rate of outflow at spillway) will be determined. In this study, an effort was made to use the numerical model of Flow3D to numerically model three-dimensional flow based on physical model and actual data from one of the largest and most important morning-glory spillways for calibration and verification purposes, and determine accuracy of the numerical modeling and associated error with simulating the numerical model. Results of this study show that, the flow at morning-glory spillways is controlled in either of three modes: flow control at crest, orifice control, and pipe control.

Predicting temporal rate coefficient of bar volume using hybrid artificial intelligence approaches

To project the structures to be built in the coastal zone and to make the best use of the coastal area, the mechanism of sediment transport, including both longshore and cross-shore transport, in this region should be well known. Within this context, temporal change rate of cross-shore sediment transport is of vital importance, especially to predict the erosion quantitatively. In this study, hybrid artificial intelligence models based on physical model data were established to determine the α coefficient used to describe the temporal change of cross-shore sediment transport. Teaching–learning-based optimization (TLBO) and artificial bee colony (ABC) algorithms were used for training of artificial neural network (ANN) in the model setup. Then, these models were compared with the classical back propagation ANN (ANN-BP) model. Wave height and period, bed slope and sediment diameter were considered as input parameters in the models. In all models, the used data for training and testing sets were 42 and 10 of total 52 experimental data, respectively. In the end of the analyses, it has been determined that the ANN-TLBO and ANN-ABC models have resulted in better results than the BP models. Also, the smallest mean absolute error and root mean square error values for testing set have been obtained from the ANN-TLBO model with 0.0068 and 0.0081, respectively. Therefore, it has been concluded that the best model ANN-TLBO can be successfully applied to predict the α coefficient.

Processes of dike-break induced flows: A combined experimental and numerical model study

Dike breaking is a disaster that could cause extensive damage. It could lead to flood flows outside the dike and induce water level fluctuations in the main channel. Numerical models are increasingly used to simulate flood flows due to dike-break, because direct observations from field surveys and physical models are rather limited. Existing knowledge concerning dam-break flows cannot be applied directly to dike-break flows because the effect of channel discharge cannot be neglected in the latter. In this study, physical experiments are done in a large laboratory flume to simulate the process of dike-break induced flood wave propagation in the floodplain and flow fluctuations in the main channel. The variations of water levels and velocities are measured and recorded using an array of pressure sensors and two acoustic Doppler velocimetry devices. A numerical model has been set up according to the experimental layout. The experiments have high repeatability and the numerical model predictions agree closely with the physical model data. The experimental results provide reliable information for improving the understanding of dike-break flow dynamics and for the verification of numerical models.

Detecting underground cavities using microtremor data: physical modelling and field experiment

ABSTRACTIn this paper, we study the possibilities of the use of microtremor records in the detection and delineation of near‐surface underground cavities. Three‐dimensional physical modelling data showed that the averaging amplitude spectra of a large number of microtremor records makes it possible to evaluate the frequencies and amplitudes of compressional standing waves generated by microtremor in the space between the ground surface and underground cavities. We illustrate how these parameters can be used to estimate the shape of the underground cavity horizontal projection. If the compressional wave velocity in the enclosing rock is known, it is possible to evaluate the depth to the cavity top using the frequencies of the standing waves. The results of the field experiment confirmed the possibility of underground cavities detection using microtremor data.

Minimum Reservoir Water Level in Hydropower Dams

Vortex formation over the intakes is an undesirable phenomenon within the water withdrawal process from a dam reservoir. Calculating the minimum operating water level in power intakes by empirical equations is not a safe way and sometimes contains some errors. Therefore, current method to calculate the critical submergence of a power intake is construction of a scaled physical model in parallel with numerical model. In this research some proposed empirical relations for prediction of submergence depth in power intakes were validated with experimental data of different physical and numerical models of power intakes. Results showed that, equations which involved the geometry of intake have better correspondence with the experimental and numerical data.

Efficient and robust wave overtopping estimation for impermeable coastal structures in shallow foreshores using SWASH

Estimation of wave overtopping over the crest of coastal structures is crucial to design effective and cost efficient countermeasures against storms. Semi-empirical formulas are often used for wave overtopping assessment, but they are not always applicable for complex structures which exist in reality (e.g. a storm wall on a dike in a shallow or very shallow foreshore). Detailed numerical models such as Eulerian and Lagrangian RANS models have potential to simulate overtopping of complex coastal structures with good accuracy. However such models require significant computational resources. The use of such models is often not feasible for the design of coastal structures, which often requires multiple iterations and model runs over a reasonably long period of time (e.g. wave trains with 1000 individual waves). In this paper we investigated the applicability of the simplified depth integrated wave transformation model SWASH for wave overtopping estimation of impermeable coastal structures in shallow foreshores. The validation results demonstrate the capability of SWASH to predict mean wave overtopping discharge with good accuracy compared to results from four different overtopping experimental campaigns (comprising 124 individual cases). The overall performance of SWASH to estimate mean wave overtopping discharge is as accurate as those obtained by semi-empirical equations in literature. However, in order to obtain accurate mean wave overtopping discharge with the SWASH model, the incident wave properties at the toe of the dike need to be accurately reproduced. For cases where this is not possible, a correction method is proposed in this paper. Detailed validation of the instantaneous wave overtopping also shows a good agreement with physical model data. In one example, a single, intensive overtopping event was not well resolved by the SWASH model and the instantaneous wave overtopping was under-predicted. However, this did not contribute significantly to the mean wave overtopping discharge. An additional advantage of the SWASH model is that specific coastal structure geometries can be modelled in SWASH if they are not covered by semi-empirical equations. Even in a case with rapidly varied flow (e.g. vertical wall on a dike) the model shows sufficient robustness. In this paper the details on the SWASH model configuration and post processing methods are outlined to enable the reader to reproduce reliable wave overtopping estimation over impermeable coastal structures in shallow foreshores.

Model of Delay Prediction for Signalized Intersection Based on GPS Data

To facilitate travel, many domestic bus transits have been fit with station prompt means. With this function, the bus arrival time can be forecast in real time based on the GPS data. However, the current bus arrival time prediction model features high assumption, not well adapted to urban roadway traffic congestion and delay at signalized intersection, thus compromising the accuracy of the prediction. A real time delay estimation for signalized intersection is proposed in this paper, combining the physical model derivation and data fitting, integrating the waiting time at signalized intersections into the existing prediction model. It is shown in the experiments that compared with previous models, the accuracy of our model increases by 29.1%. The mass GPS data is processed via the Hadoop platform, the performance is improved by 3600%~4000% compared with the serial program.