The Impact of Model Based Offset Scaling Technique on the Amplitude Variation with Offset Responses from 3D Seismic Data Acquired from the Tano Basin, Offshore Ghana

Amplitudes have been found to be a function of incident angle and offset. Hence data required to test for amplitude variation with angle or offset needs to have its amplitudes for all offsets preserved and not stacked. Amplitude Variation with Offset (AVO)/Amplitude Variation with Angle (AVA) is necessary to account for information in the offset/angle parameter (mode converted S-wave and P-wave velocities). Since amplitudes are a function of the converted S- and P-waves, it is important to investigate the dependence of amplitudes on the elastic (P- and S-waves) parameters from the seismic data. By modelling these effects for different reservoir fluids via fluid substitution, various AVO geobody classes present along the well and in the entire seismic cube can be observed. AVO analysis was performed on one test well (Well_1) and 3D pre-stack angle gathers from the Tano Basin. The analysis involves creating a synthetic model to infer the effect of offset scaling techniques on amplitude responses in the Tano basin as compared to the effect of unscaled seismic data. The spectral balance process was performed to match the amplitude spectra of all angle stacks to that of the mid (26°) stack on the test lines. The process had an effect primarily on the far (34° - 40°) stacks. The frequency content of these stacks slightly increased to match that of the near and mid stacks. In offset scaling process, the root mean square (RMS) amplitude comparison between the synthetic and seismic suggests that the amplitude of the far traces should be reduced relative to the nears by up to 16%. However, the exact scaler values depend on the time window considered. This suggests that the amplitude scaling with offset delivered from seismic processing is only approximately correct and needs to be checked with well synthetics and adjusted accordingly prior to use for AVO studies. The AVO attribute volumes generated were better at resolving anomalies on spectrally balanced and offset scaled data than data delivered from conventional processing. A typical class II AVO anomaly is seen along the test well from the cross-plot analysis and AVO attribute cube which indicates an oil filled reservoir.

Direct scaling of residual displacements for bilinear and pinching oscillators

The estimation of residual displacements in a structure due to an anticipated earthquake event has increasingly become an important component of performance-based earthquake engineering because controlling these displacements plays an important role in ensuring cost-feasible or cost-effective repairs in a damaged structure after the event.An attempt is made in this study to obtain statistical estimates of constant-ductility residual displacement spectra for bilinear and pinching oscillators with 5%initial damping,directly in terms of easily available seismological,site,and model parameters.None of the available models for the bilinear and pinching oscillators are useful when design spectra for a seismic hazard at a site are not available.The statistical estimates of a residual displacement spectrum are proposed in terms of earthquake magnitude,epicentral distance,site geology parameter,and three model parameters for a given set of ductility demand and a hysteretic energy capacity coefficient in the case of bilinear and pinching models,as well as for a given set of pinching parameters for displacement and strength at the breakpoint in the case of pinching model alone.The proposed scaling model is applicable to horizontal ground motions in the western U.S.for earthquake magnitudes less than 7 or epicentral distances greater than 20 km.

A sub-grid scale model for Burgers turbulence based on the artificial neural network method

The present study proposes a sub-grid scale model for the one-dimensional Burgers turbulence based on the neuralnetwork and deep learning method.The filtered data of the direct numerical simulation is used to establish thetraining data set,the validation data set,and the test data set.The artificial neural network(ANN)methodand Back Propagation method are employed to train parameters in the ANN.The developed ANN is applied toconstruct the sub-grid scale model for the large eddy simulation of the Burgers turbulence in the one-dimensionalspace.The proposed model well predicts the time correlation and the space correlation of the Burgers turbulence.

Underwater Sea Cucumber Target Detection Based on Edge-Enhanced Scaling YOLOv4

Sea cucumber detection is widely recognized as the key to automatic culture.The underwater light environment is complex and easily obscured by mud,sand,reefs,and other underwater organisms.To date,research on sea cucumber detection has mostly concentrated on the distinction between prospective objects and the background.However,the key to proper distinction is the effective extraction of sea cucumber feature information.In this study,the edge-enhanced scaling You Only Look Once-v4(YOLOv4)(ESYv4)was proposed for sea cucumber detection.By emphasizing the target features in a way that reduced the impact of different hues and brightness values underwater on the misjudgment of sea cucumbers,a bidirectional cascade network(BDCN)was used to extract the overall edge greyscale image in the image and add up the original RGB image as the detected input.Meanwhile,the YOLOv4 model for backbone detection is scaled,and the number of parameters is reduced to 48%of the original number of parameters.Validation results of 783images indicated that the detection precision of positive sea cucumber samples reached 0.941.This improvement reflects that the algorithm is more effective to improve the edge feature information of the target.It thus contributes to the automatic multi-objective detection of underwater sea cucumbers.

Experimental investigation and theoretical modeling on scale behaviors of high salinity wastewater in zero liquid discharge process of coal chemical industry

Zero liquid discharge(ZLD)treatment and reuse equipment of high salinity wastewater in coal-chemical industry often occur in various types of blockage problems because of high salt content,affecting the long-term stability of the device.In this study,the effects of solution temperature,steel,reaction time and wall roughness on fouling were investigated.The changes in the contents of fouling and fouling substances were qualitatively and quantitatively analyzed by XRD and EDS respectively,and the formation of scale was observed by SEM.The results show that with temperature increasing,Q235 steel is the most difficult to scale.Scaling rate of all salt scales reaches a maximum after 12 h,and the fouling rate decreases significantly from 12 to 48 h.It gradually stabilizes at 48 to 96 h.With the roughness increasing,the thickness of fouling layer increases,and a linear relationship is presented for 1 to 10 h.By comparing actual and simulated wastewater scaling rates,the relationship between actual and simulated wastewater scaling rates is y=ax-0.494.The composition of the scale was analyzed,calcium carbonate is the main product and increases with fouling time.Based on the above-mentioned results combining literatures,the hybrid prediction model with calcium carbonate as the main product is put forward.It is discussed microscopically that calcium carbonate is converted from aragonite and vaterite in a thermodynamically metastable state to calcite in a thermodynamically stable state.

Unstable evolution of railway slope under the rainfall-vibration joint action

Understanding the unstable evolution of railway slopes is the premise for preventing slope failure and ensuring the safe operation of trains.However,as two major factors affecting the stability of railway slopes,few scholars have explored the unstable evolution of railway slopes under the joint action of rainfall-vibration.Based on the model test of sandy soil slope,the unstable evolution process of slope under locomotive vibration,rainfall,and rainfall-vibration joint action conditions was simulated in this paper.By comparing and analyzing the variation trends of soil pressure and water content of slope under these conditions,the change laws of pore pressure under the influence of vibration and rainfall were explored.The main control factors affecting the stability of slope structure under the joint action conditions were further defined.Combined with the slope failure phenomena under these three conditions,the causes of slope instability resulting from each leading factor were clarified.Finally,according to the above conclusions,the unstable evolution of the slope under the rainfall-vibration joint action was determined.The test results show that the unstable evolution process of sandy soil slope,under the rainfall-vibration joint action,can be divided into:rainfall erosion cracking,vibration promotion penetrating,and slope instability sliding three stages.In the process of slope unstable evolution,rainfall and vibration play the roles of inducing and promoting slide respectively.In addition,the deep cracks,which are the premise for the formation of the sliding surface,and the violent irregular fluctuation of soil pressure,which reflects the near penetration of the sliding surface,constitute the instability characteristics of the railway slope together.This paper reveals the unstable evolution of sandy soil slopes under the joint action of rainfall-vibration,hoping to provide the theoretical basis for the early warning and prevention technology of railway slopes.

Experimental study on a pre-damaged scaled tunnel model strengthened with CFRP grids

The effectiveness of carbon fiber reinforced polymer（CFRP） grids as the strengthening materials for a pre-damaged scaled tunnel model is experimentally investigated. First, the bond performances between the CFRP grid and the concrete under different types of adhesive and surface treatment were tested. The most efficient anchoring system was adopted for the subsequent scaled tunnel strengthening. Test results show that when the epoxy structural adhesive was used as the bonding material, the failure mode was CFRP grids rupturing,and the anchorage performance was optimal. When the polymer mortar was used as the adhesive, the surface treatments with anchored bolts and grooves can improve the bond performance, and the failure mode was sliding failure with the polymer mortar peeled off. After strengthening with CFRP grids, both the stiffness and the load capacity of the pre-damaged scaled tunnel model were improved. Additionally,the results obtained by fiber bragg grating（FBG） sensors indicate that the strains across tunnel segments were reduced,and the overall performance of the tunnel was improved.

A continuum traffic flow model with the consideration of coupling effect for two-lane freeways

A new higher-order continuum model is proposed by considering the coupling and lane changing effects of the vehicles on two adjacent lanes. A stability analysis of the proposed model provides the conditions that ensure its linear stability. Issues related to lane changing, shock waves and rarefaction waves, local clustering and phase transition are also investigated with numerical experiments. The simulation results show that the proposed model is capable of providing explanations to some particular traffic phenomena commonly observable in real traffic flows.

Settlement characteristics of bridge approach embankment based on scale model test

In order to analyze the effects of backfill materials, geometries and slab setting on the settlement of bridge approach embankment, scale model was built based on the structural characteristics of bridge approach embankment, and scale model tests were carried out under different conditions. The results show that when graded gravels were selected as the backfill materials, the effect of setting approach slab to reduce the differential settlement is more prominent. When lime soils were selected as the backfill material, approach slab can moderate the longitudinal settlement slope. When using different backfill materials, the ultimate settlement of the positive trapezoidal backfill geometries is less than that of the inverted trapezoid, and the backfill geometries have little effect on the settlement slope.

Remote Control and Telemetry System for Large-scale Model Test at Sea

Physical testing of large-scale ship models at sea is a new experimental method.It is a cheap and reliable way to research the environment adaptability of a ship in complex and extreme wave conditions.It is necessary to have a stable experimental system for the test.Since the experimental area is large, a remote control system and a telemetry system are essential, and were designed by the authors.An experiment was conducted on the Songhuajiang River to test the systems.The relationship between the model's speed and its electromotor's revolutions was also measured during the model test.The results showed that the two systems make it possible to carry out large-scale model tests at sea.

Experimental Study on the Ride Comfort of a Crawler Power Chassis Scale Model Based on the Similitude Theory

The ride comfort experimental assessment of crawler off-road vehicle is relatively overlooked, and is expensive and difficult to execute with higher and higher ride comfort performance requirements. To trade off between precise and cost, an experimental method based on the similitude theory is proposed. Under the guidance of the similitude theory, a 1：5 crawler power chassis scale model equipped with a kind of variable stiffness suspension system is used. The power spectrum density（PSD）, the root mean square（RMS） of weighed acceleration, peak factor, average absorbed power（AAP） and vibration dose value（VDV） are selected as ride comfort evaluation indexes, and tests results are transformed via similarity indexes to predict the performance of full-scale power chassis. PSD shows that the low-order natural frequency of the vertical natural frequency（z axis） is 1.1 Hz, and the RMS, AAP and VDV values indicate the ride comfort performance of this kind of power chassis is between the ＂A little uncomfortable＂ and ＂Rather uncomfortable＂. From the results, low-order vertical natural frequency, obtained by PSD, validates that the similarity relationship between two models is satisfied, and 1：5 scale model used in experiment meets the similarity relationship with the full-scale model; consequently, the ride comfort prophase evaluation with the 1：5 scale model is feasible. The attempt of applying the similitude theory to crawler vehicle ride comfort test study decreases the cost and improves the test feasibility with sufficient test precise.

Joint modelling of location and scale parameters of the skew-normal distribution

Joint location and scale models of the skew-normal distribution provide useful ex- tension for joint mean and variance models of the normal distribution when the data set under consideration involves asymmetric outcomes. This paper focuses on the maximum likelihood estimation of joint location and scale models of the skew-normal distribution. The proposed procedure can simultaneously estimate parameters in the location model and the scale model. Simulation studies and a real example are used to illustrate the proposed methodologies.

A skew–normal mixture of joint location, scale and skewness models

Normal mixture regression models are one of the most important statistical data analysis tools in a heterogeneous population. When the data set under consideration involves asymmetric outcomes, in the last two decades, the skew normal distribution has been shown beneficial in dealing with asymmetric data in various theoretic and applied problems. In this paper, we propose and study a novel class of models： a skew-normal mixture of joint location, scale and skewness models to analyze the heteroscedastic skew-normal data coming from a heterogeneous population. The issues of maximum likelihood estimation are addressed. In particular, an Expectation-Maximization （EM） algorithm for estimating the model parameters is developed. Properties of the estimators of the regression coefficients are evaluated through Monte Carlo experiments. Results from the analysis of a real data set from the Body Mass Index （BMI） data are presented.

Systematic rationalization approach for multivariate correlated alarms based on interpretive structural modeling and Likert scale

Alarm flood is one of the main problems in the alarm systems of industrial process. Alarm root-cause analysis and alarm prioritization are good for alarm flood reduction. This paper proposes a systematic rationalization method for multivariate correlated alarms to realize the root cause analysis and alarm prioritization. An information fusion based interpretive structural model is constructed according to the data-driven partial correlation coefficient calculation and process knowledge modification. This hierarchical multi-layer model is helpful in abnormality propagation path identification and root-cause analysis. Revised Likert scale method is adopted to determine the alarm priority and reduce the blindness of alarm handling. As a case study, the Tennessee Eastman process is utilized to show the effectiveness and validity of proposed approach. Alarm system performance comparison shows that our rationalization methodology can reduce the alarm flood to some extent and improve the performance.

Scaled down model design of shaking table test of Taizhou Bridge

Taizhou Bridge is the first kilometer level three-pylon two-span suspension bridge in the world and the structural complexity has significant effects on the seismic performance of the bridge. Shaking table test of Taizhou Bridge is arranged to investigate the effects of non-uniform ground motion input, collision between main and side spans and optimal seismic structural system. It's very important and difficult to design and manufacture the scaled down model of Taizhou Bridge used during the shaking table test. The key point is that the girder and pylons are very hard to be manufactured if the similarity ratio is strictly followed. Based on the finite element method (FEM) analysis, a simplified scaled down model is designed and the bending stiffness of the girder and pylon are strictly simulated, and the torsion stiffness and axial stiffness are not strictly simulated. The inner forces and displacements of critical sections, points of simplified model and theoretical model are compared by FEM analysis, and it's found out that the difference between the seismic responses is relatively small. So, the simplified model can be used to conduct the shaking table test by the FEM verification.

Effect of Spatial and Temporal Scales on Habitat Suitability Modeling:A Case Study of Ommastrephes bartramii in the Northwest Pacific Ocean

Temporal and spatial scales play important roles in fishery ecology,and an inappropriate spatio-temporal scale may result in large errors in modeling fish distribution.The objective of this study is to evaluate the roles of spatio-temporal scales in habitat suitability modeling,with the western stock of winter-spring cohort of neon flying squid （Ornmastrephes bartramii） in the northwest Pacific Ocean as an example.In this study,the fishery-dependent data from the Chinese Mainland Squid Jigging Technical Group and sea surface temperature （SST） from remote sensing during August to October of 2003-2008 were used.We evaluated the differences in a habitat suitability index model resulting from aggregating data with 36 different spatial scales with a combination of three latitude scales （0.5°,1 ° and 2°）,four longitude scales （0.5°,1°,2° and 4°）,and three temporal scales （week,fortnight,and month）.The coefficients of variation （CV） of the weekly,biweekly and monthly suitability index （SI） were compared to determine which temporal and spatial scales of SI model are more precise.This study shows that the optimal temporal and spatial scales with the lowest CV are month,and 0.5° latitude and 0.5° longitude for O.bartramii in the northwest Pacific Ocean.This suitability index model developed with an optimal scale can be cost-effective in improving forecasting fishing ground and requires no excessive sampling efforts.We suggest that the uncertainty associated with spatial and temporal scales used in data aggregations needs to be considered in habitat suitability modeling.

Equality Testing for Soil Grid Unit Resolutions to Polygon Unit Scales with DNDC Modeling of Regional SOC Pools

Matching soil grid unit resolutions with polygon unit map scales is important to minimize the uncertainty of regional soil organic carbon(SOC) pool simulation due to their strong influences on the modeling.A series of soil grid units at varying cell sizes was derived from soil polygon units at six map scales,namely,1:50 000(C5),1:200 000(D2),1:500 000(P5),1:1 000 000(N1),1:4 000 000(N4) and 1:14 000 000(N14),in the Taihu Region of China.Both soil unit formats were used for regional SOC pool simulation with a De Nitrification-DeC omposition(DNDC) process-based model,which spans the time period from 1982 to 2000 at the six map scales.Four indices,namely,soil type number(STN),area(AREA),average SOC density(ASOCD) and total SOC stocks(SOCS) of surface paddy soils that were simulated by the DNDC,were distinguished from all these soil polygon and grid units.Subjecting to the four index values(IV) from the parent polygon units,the variations in an index value(VIV,%) from the grid units were used to assess its dataset accuracy and redundancy,which reflects the uncertainty in the simulation of SOC pools.Optimal soil grid unit resolutions were generated and suggested for the DNDC simulation of regional SOC pools,matching their respective soil polygon unit map scales.With these optimal raster resolutions,the soil grid units datasets can have the same accuracy as their parent polygon units datasets without any redundancy,when VIV < 1% was assumed to be a criterion for all four indices.A quadratic curve regression model,namely,y = – 0.80 × 10^(–6)x^2 + 0.0228 x + 0.0211(R^2 = 0.9994,P < 0.05),and a power function model R? = 10.394?^(0.2153)(R^2 = 0.9759,P < 0.05) were revealed,which describe the relationship between the optimal soil grid unit resolution(y,km) and soil polygon unit map scale(1:10 000x),the ratio(R?,%) of the optimal soil grid size to average polygon patch size(?,km^2) and the ?,with the highest R^2 among different mathematical regressions,respectively.This knowledge may facilitate the grid partitioning of regions during the investigation and simulation of SOC pool dynamics at a certain map scale,and be referenced to other landscape polygon patches' mesh partition.

Design of scale model of plate-shaped absorber in a wide frequency range

In order to design the scale model in a wide frequency range,a method based on the reflective loss is proposed according to the high-frequency approximation algorithm,and an example of designing the scale model of a plate-shaped absorber is given in this paper.In the example,the frequency of the full-size measurement ranges from 2.0 GHz to 2.4 GHz,the thickness of the full-size absorber is 1 mm and the scale ratio is 1/5.A two-layer scale absorber is obtained by the proposed method.The thickness values of the bottom and top layer are 0.4 mm and 0.5 mm,respectively.Furthermore,the scattering properties of a plate model and an SLICY model are studied by FEKO to verify the effectiveness of the designed scale absorber.Compared with the corresponding values from the theoretical scale model,the average values of the absolute deviations in 10 GHz～12 GHz are 0.53 d Bm^2,0.65 d Bm^2,0.76 d Bm^2 for the plate model and 0.20 d Bm^2,0.95 d Bm^2,0.77 d Bm^2 for the SLICY model while the incident angles are 0°,30°,and 60°,respectively.These deviations fall within the Radar cross section（RCS） measurement tolerance.Thus,the work in this paper has important theoretical and practical significance.

Variable selection for skew-normal mixture of joint location and scale models

Although there are many papers on variable selection methods based on mean model in the nite mixture of regression models,little work has been done on how to select signi cant explanatory variables in the modeling of the variance parameter.In this paper,we propose and study a novel class of models:a skew-normal mixture of joint location and scale models to analyze the heteroscedastic skew-normal data coming from a heterogeneous population.The problem of variable selection for the proposed models is considered.In particular,a modi ed Expectation-Maximization(EM)algorithm for estimating the model parameters is developed.The consistency and the oracle property of the penalized estimators is established.Simulation studies are conducted to investigate the nite sample performance of the proposed methodolo-gies.An example is illustrated by the proposed methodologies.

Impact of the Time Scale of Model Sensitivity Response on Coupled Model Parameter Estimation

That a model has sensitivity responses to parameter uncertainties is a key concept in implementing model parameter es- timation using filtering theory and methodology. Depending on the nature of associated physics and characteristic variability of the fluid in a coupled system, the response time scales of a model to parameters can be different, from hourly to decadal. Unlike state estimation, where the update frequency is usually linked with observational frequency, the update frequency for parameter estimation must be associated with the time scale of the model sensitivity response to the parameter being esti- mated. Here, with a simple coupled model, the impact of model sensitivity response time scales on coupled model parameter estimation is studied. The model includes characteristic synoptic to decadal scales by coupling a long-term varying deep ocean with a slow-varying upper ocean forced by a chaotic atmosphere. Results show that, using the update frequency deter- mined by the model sensitivity response time scale, both the reliability and quality of parameter estimation can be improved significantly, and thus the estimated parameters make the model more consistent with the observation. These simple model results provide a guideline for when real observations are used to optimize the parameters in a coupled general circulation model for improving climate analysis and prediction initialization.