Field Measurement Data Research Articles

A modeling strategy for the simulation of box sections with layered shell elements

This paper presents a numerical strategy to model box sections from bridge girders using horizontal layered shell finite elements. The basic idea is to avoid the construction of more computational expensive meshes based on the use of folded shell and brick finite elements. The numerical strategy imposes the deactivation of those layers related to empty spaces within the bridge cross-section. The performance of this technique is explored by means of two demanding practical applications related to bridge structures with constant and variable deck thicknesses. The first application deals with the static truck load test of the Caynarachi Bridge, located in Peru, and for which measured field data exists, while the second application is related to the construction stage analysis of a box bridge structure including time effects due to concrete creep, shrinkage and steel relaxation. The results demonstrate that the studied technique acceptably correlates with the measured field data,expressed in terms of vertical displacements,with correlation coefficients exceeding 0.94.Additionally, the outcomes align well with the results of other numerical techniques, allowing applicants to use this simplified modeling approach in daily design office.

Dynamic model of high-speed maglev train-guideway bridge system with a nonlinear suspension controller

To improve the anti-interference ability of maglev trains, a dynamic model of the high-speed maglev train with a nonlinear suspension controller for the guideway system is proposed in this paper. Based on the nonlinear characteristics of the magnetic suspension system, a nonlinear decoupling controller is designed using the feedback linearization theory. Then, a high-speed maglev train model is refined with a guideway coupling system, consisting of a maglev train simulated as a multi-body dynamics model with 537 degrees of freedom and a spatial finite element model of the guideway. Taking the Shanghai high-speed maglev train as an example, the correctness of the computational model is verified by comparing the modeling results with field measurement data, and the control effectiveness of the nonlinear controllers and the traditional PD controllers is compared considering different train speeds and disturbance forces. The results show that the suspension gap under the decoupling control is smaller than that under the PD control during the train operations. Under the same disturbance force, the decoupling control exhibits better control performance than the PD control. The variation amplitudes of the magnetic pole gaps are generally linearly related to the disturbance force.

Numerical simulation and optimization of the multi-stage air/gas supply system in a coke oven battery with 7.1 m coking chambers

ABSTRACT 3-D numerical simulations based on diffusion combustion technology were employed to optimize the multi-stage air/gas supply system in a coke oven battery with 7.1 m coking chambers. In the heating flues, the Eddy-Dissipation Concept (EDC) model and the ideal gas model were utilized to numerically investigate diffusion combustion. What is more, the radiation between the flue gas and the silicon brick was calculated using the Discrete Ordinates (DO) model. After validating the reliability of the model with field-measured data, insights into the temperature field and gas flow in the heating flue, and heat flux distribution over the heating wall were obtained. To characterize the vertical heating uniformity, an index of the standard deviation of the heat flux over the vertical heating walls was proposed. By optimizing the multi-stage air/gas supply design of heating flues, the vertical heating uniformity was improved by 60% according to the index values. The approach developed in this work can be a useful tool for the design of large-capacity coke oven batteries at different scales.

Performance evaluation of the Bilate and Furfuro irrigation schemes in Silti Zone, southern Ethiopia

Many irrigation schemes are performing poorly for a number of reasons, and this should be improved to increase the efficiency and productivity of the schemes. This study attempted to determine the performance of the Bilate and Furfuro irrigation schemes in Silti Zone, southern Ethiopia. For field data measurements, three farmers’ fields were selected at the head, middle, and tail end of each scheme. Average conveyance efficiencies were 53% and 56.1%, average field application efficiencies were 55.9% and 58.0%, average water storage efficiencies were 53% and 46.5%, irrigation uniformity was 91.03% and 92.9%, and overall irrigation efficiency was 28% and 32% for Bilate and Furfuro schemes respectively. This implied that the two schemes were performing inefficiently and inadequately, but water was distributed uniformly. The reason might be most canal sections had unreasonable losses of water in two schemes. Additionally, relative water supply was 0.68 and 0.79, relative irrigation supply was 0.61 and 0.77, output per unit irrigated area was 4140.4 and 1781.5 ($/ha), output per unit command area was 4510.3 and 1968.5 ($/ha), output per unit irrigation supply was 0.94 and 0.28 ($/m3), output per unit water consumed was 0.99 and 0.39 ($/m3), sustainability of irrigation area was 1.05 and 1.02, and irritation ratio was 1.11 and 1.09 for Bilate and Furfuro schemes respectively. This revealed that the applied water was not satisfied the crop water demand, but their irrigated lands were expanded for two irrigation schemes. Furfuro scheme was better than Bilate in terms of relative water supply and relative irrigation supply, but their results obtained were below acceptable values. However, Bilate scheme had significantly better land and water productivity than Furfuro scheme. This may be use high value crops, better agricultural inputs, and removal of grass cover and sedimentation from canal systems. Hence, Bilate irrigation scheme was better performing than Furfuro scheme. Therefore, adopt the best practices learned from Bilate irrigation scheme for the Furfuro scheme.

A New Inversion Method for Obtaining Underwater Spatial Information of Subsidence Waterlogging Based on InSAR Technology and Subsidence Prediction

Surface waterlogging disasters due to underground mining and geological status have caused the abandonment of fertile land, seriously damaged the ecological environment, and have influenced the sustainable development of coal resource-based cities, which has become a problem that some mining areas need to face. However, the traditional underwater terrain measurement method using sonar encompasses a time-consuming and labor-intensive process. Thus, an inversion method for obtaining the underwater spatial information of subsidence waterlogging in coal mining subsidence waterlogging areas is proposed, based on differential interferometric synthetic aperture radar (D-InSAR) and the probability integral prediction method. First, subsidence values are obtained in the marginal area of the subsidence basin using D-InSAR technology. Then, the subsidence prediction parameters of the probability integral method (PIM) are inverted by a genetic algorithm (GA) based on the subsidence values. Finally, the underwater spatial information of subsidence waterlogging is calculated on the basis of the prediction parameters. The subsidence waterlogging area in the Wugou coal mine was adopted as the study area, and the underwater spatial information of subsidence waterlogging was inverted by the proposed method. The results show that this method can effectively provide the underwater spatial information of subsidence waterlogging, including the maximum subsidence value, waterlogging volume, subsidence waterlogging area, and underwater terrain in the subsidence waterlogging area. Compared with field-measured data from the same period, the RMSE of water depth is 99 mm, and the relative error is 9.9%, which proves that this inversion method is accurate and can meet engineering precision requirements.

Reliability analysis of vegetated slope considering spatial variability of soil and root properties

Vegetation acts as a natural engineering approach that can enhance the stability of shallow soil slopes. However, the intrinsic uncertainties of vegetation, particularly the randomness of root features, have rarely been considered in vegetated slope stability analysis. To address the issue, a modified random field model is proposed to simulate the spatial variability of root parameters (e.g., root volume ratio, Rv) with different root orientations and architectures. The proposed random field model, combined with the finite element method (FEM) and limit equilibrium method (LEM), is utilised to investigate the effects of root architecture, orientation, and depth on vegetated slope reliability, considering spatial variability of soil and root properties simultaneously under rainfall infiltration. It is found that the proposed model effectively characterises the spatial variability of root parameters with different root orientations and architectures, as validated against theoretical and field-measured data. Ignoring root orientation during simulation can lead to a misestimation of the slope reliability index by up to nearly 17.1%. Moreover, without considering the spatial variability of Rv within the root zone or spatially variable soil properties (i.e., void ratio, saturated water permeability, and soil water retention curve) beyond the root zone, the vegetated slope reliability index can be overestimated by up to 4.8 times. It is recommended to adopt a triangular root system, concentrating most of the roots in the shallow depth zone and extending horizontally, which can reduce slope stability uncertainty and improve overall slope reliability.

Full-scale experimental simulation of the stack effect pressure acting on an elevator door system in a high-rise building

The pressure-bearing performance of an elevator system under the stack effect in a super high-rise building is usually difficult to simulate directly in a laboratory environment due to the difficulty in fully meeting the similarity requirements. In this paper, a new full-scale experimental device for simulating stack pressure was designed in a large boundary layer wind tunnel laboratory, which was based on using wind pressure to simulate the action of thermal pressure on an elevator door system. By employing this approach, the pressure-bearing performances of an elevator door system under different levels of wind pressure of the static and dynamic conditions were systematically investigated, and the malfunction of the elevator door system due to the strong stack effect was successfully simulated. The critical pressure threshold of the elevator door system, which was difficult to evaluate accurately in previous studies, was then measured and it was approximately equal to 150 Pa. Meanwhile, the pressure-bearing state of the elevator door system was numerically simulated and compared with the wind tunnel experiment results. The study shows that the simulation employing the dynamic mesh model can accurately reflect the force characteristics of an elevator lobby door during its physical process of opening and closing. Finally, based on the experimental simulation results, the pressure-bearing thresholds of the elevator door systems of several typical high-rise buildings were estimated, and the reasonability of the full-scale simulation was finally verified by comparisons with field measurement data.

Experimental Behavior of a Steel Girder–Stringer–Floorbeam Bridge

The presented case study summarizes a quick-response project for the Tennessee Department of Transportation (TDOT), which focused on the steel-stringer behavior for a girder–stringer–floorbeam bridge. TDOT was confronted with relatively low stringer load ratings for many of their 31 similar structures. As a result, TDOT initiated this field study to ultimately produce refined load ratings. This information was then to be utilized for deciding whether an intervention (e.g., retrofit) was necessary. Diagnostic load testing was the approach selected and a representative bridge was chosen. Then load testing was comprehensively designed and executed. This included the installation of 42 strain gauges, data-acquisition quality-control testing, weighing and measuring test trucks, load testing of the structure, and then removal of the system. The load-test data provided insight into the true behavior of the bridge. The stringers were subjected to a combined interaction of the global and local response. Overall, the local demands were the largest component, but the magnitudes were well below the predicted values. This was partly because of the lateral distribution of the load. Additionally, partial composite action was identified between the steel stringers and concrete slab. Refined load ratings were calculated using the field-measured data and following the AASHTO Manual for Bridge Evaluation. The comparison of predicted to measured responses clearly indicated the conservative nature of the prior analytical calculations. The stringer load ratings were increased by 68% based on the field testing. In the end, the steel-stringer load ratings were sufficient, with no intervention necessary.

Predicting carob tree physiological parameters under different irrigation systems using Random Forest and Planet satellite images.

In the context of climate change, monitoring the spatial and temporal variability of plant physiological parameters has become increasingly important. Remote spectral imaging and GIS software have shown effectiveness in mapping field variability. Additionally, the application of machine learning techniques, essential for processing large data volumes, has seen a significant rise in agricultural applications. This research was focused on carob tree, a drought-resistant tree crop spread through the Mediterranean basin. The study aimed to develop robust models to predict the net assimilation and stomatal conductance of carob trees and to use these models to analyze seasonal variability and the impact of different irrigation systems. Planet satellite images were acquired on the day of field data measurement. The reflectance values of Planet spectral bands were used as predictors to develop the models. The study employed the Random Forest modeling approach, and its performances were compared with that of traditional multiple linear regression. The findings reveal that Random Forest, utilizing Planet spectral bands as predictors, achieved high accuracy in predicting net assimilation (R² = 0.81) and stomatal conductance (R² = 0.70), with the yellow and red spectral regions being particularly influential. Furthermore, the research indicates no significant difference in intrinsic water use efficiency between the various irrigation systems and rainfed conditions. This work highlighted the potential of combining satellite remote sensing and machine learning in precision agriculture, with the goal of the efficient monitoring of physiological parameters.

Serviceability analysis of sea-crossing bridges under correlated wind and wave loads

With coupled wind and wave loads suffered by sea-crossing bridges, it is challenging to include uncertainties for assessing bridge serviceability. In this study, an efficient probabilistic peak response framework with surrogate models is developed for the serviceability analysis of sea-crossing bridges under coupled wind and wave loads. The joint probability distribution functions (JPDF) of the mean wind speed, significant wave height, and peak wave period are first derived based on long-term field measurement data and using a C-vine copula model. The JPDF serves as an input to the bridge to calculate the peak response of the bridge through finite-element analyses. To improve computational efficiency and make the problem manageable, the surrogate models are then generated by both the support vector machine and response surface method to predict the bridge peak responses. The exceeding probabilities for the serviceability assessment are finally obtained by the Monte-Carlo method using the pre-defined threshold values of bridge serviceability. A real long-span sea-crossing bridge is used as a case study to demonstrate the feasibility and effectiveness of the proposed framework. The results elucidate the effects of correlated wind and wave loads on bridge serviceability. Ignoring the correlation of wind and wave parameters will significantly overestimate the exceeding probability of bridge serviceability.

Integrated Application of SWAT and L-THIA Models for Nonpoint Source Pollution Assessment in Data Scarce Regions

Nonpoint source pollution (NPS) has become the most important reason for the deterioration of water quality, while relevant studies are often limited to African river and lake basins with insufficient data. Taking the Simiyu catchment of the Lake Victoria basin as the study area, we set up a NPS model based on the soil and water assessment tool (SWAT). Furthermore, the rationality of this model is verified with the field-measured data. The results manifest that: (1) the temporal variation of NPS load is consistent with the variation pattern of rainfall, the average monthly output of total nitrogen (TN) and total phosphorus (TP) in the rainy season was 1360.6 t and 336.2 t, respectively, while in the dry season was much lower, only 13.5 t and 3.0 t, respectively; (2) in view of spatial distribution among 32 sub-basins, TN load ranged from 2.051 to 24.288 kg/ha with an average load of 12.940 kg/ha, and TP load ranged from 0.263 to 8.103 kg/ha with an average load of 3.321 kg/ha during the 16-month study period; (3) Among the land use types, the cropland contributed the highest proportion of TN and TP pollution with 50.28% and 76.29%, respectively, while the effect of forest on NPS was minimal with 0.05% and 0.02% for TN and TP, respectively. (4) Moreover, the event mean concentration (EMC) values of different land use types have been derived based on the SWAT model, which are key parameters for the application of the long-term hydrological impact assessment (L-THIA) model. Therefore, this study facilitates applying the L-THIA model to other similar data-deficient catchments in view of its relatively lower data requirement.

Analysis of Technologies for Degassing MSW Landfill by Visualization of Isolines of Concentrations of Biogas Components

To detail the distribution of biogas components by height from the surface of landfill, this article proposes a method for visualizing multidimensional data that complements the flat map of field measurements of gas generation with a vertical coordinate reflecting the isolines of concentrations of biogas components by height above the landfill surface. The three-dimensional surface obtained by combining the data of field measurements of gas generation and calculations, according to empirical models, of isolines of concentrations in height, visualizes the zone of the atmosphere of the MSW landfill.

Inversion of Soil Salinity in the Irrigated Region along the Southern Bank of the Yellow River Using UAV Multispectral Remote Sensing

Inversion of Soil Salinity in the Irrigated Region along the Southern Bank of the Yellow River Using UAV Multispectral Remote Sensing

Traffic Congestion Prediction Using Feature Series LSTM Neural Network and a New Congestion Index

Large and expanding cities suffer from a traffic congestion problem that harms the environment, travelers, and the economy. This paper aims to predict short term traffic congestion on a road section of expressway in Delhi city. For this purpose, we first propose a traffic congestion index based on traffic speed and flow. Clustering techniques and the Greenshield’s model were used for the derivation of the congestion index. Using this congestion index, congested time intervals of each day and each location of a weekday were identified. This study also introduces a feature series long short-term memory neural network (FSLSTMNN), which links a long short-term memory (LSTM) layer to each feature. It is trained using the many heterogeneous traffic features data collected in Delhi city for the next five minutes of traffic flow and speed prediction. FSLSTMNN achieved the good capability to learn feature series data. We also trained several traditional and deep-learning models using the same traffic data. The FSLSTMNN reduces mean absolute error 12.90% and 17.13%, respectively, in speed and traffic flow prediction compared to the second good-performance long short-term memory neural network (LSTMNN). Finally, traffic congestion is predicted classwise (light, medium, and congested) using the developed congestion index and traffic speed and flow predicted by the FSLSTMNN. Predicted results are consistent with the measured field data. Study results confirm that the developed congestion index and FSLSTMNN can be used successfully to predict traffic congestion.

HYDRODYNAMIC ASSESSMENT ALONG THE COAST OF TANJUNG SEDELI, MALAYSIA

Tidal influence plays a significant role in coastal hydrodynamics as the impact may lead to coastal erosion. Tanjung Sedeli located on the southern coast of Malaysia is exposed to low tidal issues which disrupts the navigation of local fishermen due to the shallow river mouth in the area. This study presents the hydrodynamic processes along the shoreline of Tanjung Sedeli. BLUEKENUE was used as the pre-processor to create a bathymetry file and perform mesh generation to set up the initial model boundary which functions as input files for numerical study. TELEMAC2D further processes the hydrodynamic data (tides and currents), calibrated, and validated with the measured field data collected between 24th September to 6th October 2020 covering both spring and neap tide conditions. The nature of tides in the area was mainly mixed tides, predominantly semidiurnal tides. Modelled hydrodynamic values show good conformity with field measurements with an error of 1.4% for water level values, 10.6% and 20o for current speed and direction respectively. Water flows north into the estuary during spring tide with maximum velocity is 0.756m/s surrounding the river mouth and Pulau Tagal. Low velocity values were recorded at the left bank of the river (0.028 m/s) and Pulau Tagal (0.085 m/s) during spring tide. This study provides information on current hydrodynamic condition of the study area.

Quantification of three-dimensional added turbulence intensity for the horizontal-axis wind turbine considering the wake anisotropy

The accurate evaluation of wake turbulence intensity (TI) is of great significance for the layout optimization of wind farms and research on control strategies. However, the existing engineering wake models still have many shortcomings in evaluating the TI in the wake of horizontal-axis wind turbines (HAWTs), especially in the near wake region. In response to this, this article proposed an analytical model based on the double-Gaussian ellipse function that can describe the three-dimensional added TI distribution in the entire wake region. Firstly, the anisotropy of wake expansion is taken into account in both the horizontal and vertical directions, assuming that the added TI distribution downstream of the HAWT is a double-Gaussian elliptical shape. Secondly, taking into account the self-similarity characteristics of flow TI, the maximum added TI and its position in the entire wake region are evaluated. In addition, considering the influence of the ground effect, the vertical turbulence distribution was corrected. Finally, the proposed added turbulence model was validated and relative error analysis was conducted using large eddy simulation (LES) data, wind field measurement data, and wind tunnel experimental data. The results show that the model had good prediction accuracy in the entire wake region, and its prediction performance was significantly improved compared to traditional models, especially in the near wake region, with the lowest even relative error of 3.66%. This model has significant advantages such as low computational cost, wide applicability, and high accuracy. It can reduce energy losses in wind farms, improve wind energy utilization efficiency, and has great potential for widespread application in large-scale wind farms.

Analisis Daya Solar Cell pada Lampu Parkiran di Bandara Sultan Muhammad Kaharuddin Sumbawa

This research aims to analyze the condition of parking lights that use renewable energy, namely solar cells. Basically, the condition of the parking lights is not working optimally or not in accordance with the predetermined light on time settings due to the lack of power supplying the parking lights, resulting in a lack of live time for the solar cell parking lights. Data on the equipment module used in the solar cell parking lights is collected and real data in the field or manual measurement data will then be analyzed. The results will be a comparison between the data in the tool module and the measurement data in the field. The impact is the lack of lighting in the parking area of Sumbawa's Sultan Muhammad Kaharuddin Airport. Equipment checking and routine maintenance must be carried out to resolve problems that occur with parking lights. This research provides a better understanding of renewable energy, namely solar cells.

A comprehensive prediction model of drilling wellbore temperature variation mechanism under deepwater high temperature and high pressure

Comprehensively considering the impact of properties of drilling fluid at high temperature and high pressure (HTHP), drill string eccentricity, rotation, and rock breaking of drill bit on the annular temperature profile, transient temperature variations were predicted by using a wellbore heat transfer model. The model was numerically solved using the finite difference method. Compared to DRILLBENCH simulations, the predicted model was more consistent with the field-measured data. The calculations revealed that comprehensively considering various heat source factors made the annular temperature closer to the actual wellbore value, with a temperature difference of up to 10.66 °C. When considering variations of properties of drilling fluid at HTHP, the lower section of the annulus showed a significant decrease in temperature with depth, with a bottom-hole temperature difference of 5.4 °C. The bottom-hole temperature decreased by about 2.6 °C from concentric to eccentric drill string, and the pressure difference was about 1 MPa. Compared to drill string eccentricity, rotation and rock breaking of drill bit had a greater impact on annular temperature, with bottom-hole temperature differences of 13 °C and 22 °C, respectively. Accurate temperature modeling can better understand and predict the variation patterns of wellbore temperature, providing important guidance for the development of deepwater drilling.

Application of ERT, IP and VLF-EM Methods to Investigate Landslide-Prone Structures at Archaeological Sites in Lamreh, Aceh Besar, Indonesia

Since the 21st century, Lamreh, Aceh Besar Regency, Indonesia played an important role during the maritime silk route at the gate of the Malacca strait. This article investigates the subsurface structure of landslide-prone areas in cultural heritage based on 2D resistivity, chargeability and current density models of ERT, IP and VLF-EM methods, respectively. Field data measurements were carried out on 2 crossing profiles along the cliff suspected of experiencing landslides. The length of each profile is 220 with 4 m distance between stations. The 2D models reveal that the subsurface geological structure of Lamreh is composed of a mixed layer of clastic sediment and volcanic material at the top, followed by a layer of calcareous sandstone, and volcanic breccia at the bottom. The 3 layers are most easily distinguished in the resistivity model. The topmost layer is permeable but dry, i.e., characterized by a more resistive layer in the models. While the second layer is characterized by an intermediate conductivity and the bottom layer is highly conductive. The conductivity in these 2 layers is influenced by the degree of water content within the rocks. The chargeability models derived from IP data can distinguish between the dry layer on the surface and the saturated layer below. Meanwhile, the current density models obtained from VLF-EM data have proven the presence of fractures and faults along the profiles due to weathering as also seen in the resistivity models. HIGHLIGHTS Investigation of subsurface structure in landslide-prone area of Lamreh, Aceh Besar Regency, Indonesia, a cultural heritage site with historical significance in the maritime silk route. Utilization of 2D resistivity, chargeability and current density models (ERT, IP and VLF-EM) to analyze the subsurface structure. Field data measurements conducted on 2 crossing profiles along the suspected landslide cliff, with a profile length of 220 and 4 m station distance. Subsurface geological structure of Lamreh identified as a mixed layer of clastic sediment and volcanic material at the top, followed by calcareous sandstone and volcanic breccia at the bottom. Resistivity models most effectively distinguish the 3 layers, highlighting permeable but dry top layer, intermediate conductivity in the second layer, and high conductivity in the bottom layer influenced by water content. Chargeability and current density models confirm surface dryness and presence of fractures and faults due to weathering GRAPHICAL ABSTRACT

Mapping pedestrian heat stress in current and future heatwaves in Cardiff, Newport, and Wrexham in Wales, UK

The paper describes a study that uses computer simulation to assess the extent of heat stress experienced by pedestrians in three Welsh cities during heatwaves, with a view to identifying implications for urban planning and design practice. The simulation model used localized radiant temperature, wind speed, air temperature, as well as the metabolic rate and clothing insulation of occupants. Simulated results were partially evaluated using field measurement data and from the Land Surface Temperature data obtained from Landsat satellite thermography. Results suggest that peak heat stress is expected to increase by 4.5 °C in Universal Thermal Climate Index equivalent temperature by 2080, especially for urban areas exposed to direct sunlight. The percentage of daytime hours without heat stress are expected to decrease significantly, from 30 to 80% in 2020 to 10–70% by 2080. The study suggests that mitigation measures are essential to reduce future heat stress in Welsh cities and towns; these include interventions such as green and blue infrastructure, choice of trees and artificial shading, choice of both artificial surface materials and vegetation cover, and street layout with proper orientation and aspect ratio. The results have significant implications for local authorities, town planning, and landscape practice.