Complex Terrain Conditions Research Articles

Application of power grid wind monitoring data in transmission line accident warning and handling affected by typhoon

With the increasing number of transmission line monitoring points, it is possible to obtain meteorological monitoring data of power grid, and the meteorological monitoring data of power grid can be further used to guide typhoon disaster early prevention, fault repair and disposal of transmission faults. This paper innovatively proposes a typhoon microscale (100 m) wind field simulation method suitable for the complex terrain conditions in different coastal areas of China, and uses the power grid meteorological monitoring data to improve the early warning accuracy and credibility in the local terrain space of typhoon disasters. The prediction robustness and accuracy of the scale reduction prediction model are improved through continuous observation and statistical correction, several engineering examples show that the method is correct and effective. The dynamic typhoon prevention strategy of the power grid and the timely adjustment of the power grid operation mode can be guided for the preliminary analysis of the cause of the transmission failure after the typhoon transit, so as to provide scientific guidance for the subsequent emergency repair. This method has a general practical and guiding value for the coastal power grid of the typhoon influence area.

Fitness-Based Hierarchical Reinforcement Learning for Multi-human-robot Task Allocation in Complex Terrain Conditions

Fitness-Based Hierarchical Reinforcement Learning for Multi-human-robot Task Allocation in Complex Terrain Conditions

Influence of the turbulence conditions of crosswind on the aerodynamic responses of the train when running at tunnel-bridge-tunnel

High-speed trains (HSTs) often encounter crosswinds with complex pulsating components when running at a tunnel-bridge-tunnel section (TBTS), and their running safety may deteriorate sharply due to the complex terrain conditions in mountainous areas. This study aims to discuss the influence relationship of different turbulent conditions of the crosswind on the aerodynamic response of the HST passing through the TBTS. On the basis of the measured wind field data of a typical TBTS site, the pulsating wind field is numerically reconstructed by large eddy simulation, and the influence of the incoming flow dimension, the turbulence intensity and the average wind speed on the aerodynamic loads of the HST running at the TBTS are analysed. The corresponding influence mechanisms are explained in terms of the pressure distribution and flow field structure of the HST. The influence of the loading dimension of aerodynamic load and incoming turbulence intensity on the dynamic response index of the train body and wheel-rail contact is further discussed by establishing a wind-vehicle-bridge-tunnel coupling dynamic calculation model. The main conclusions are as follows: At the TBTS, the 1D pulsating incoming flow simulation scheme can be used rather than the 3D incoming flow scheme in calculating the aerodynamic response of the HST. The influence of the incoming turbulence intensity on the aerodynamic load of the HST is mainly reflected at the bridge section (BS), The fluctuation extent of the aerodynamic load of the HST increases with the increase in the turbulent intensity of the incoming flow. When the incoming flow turbulence intensity increases from 0 to 0.09, at the BS, the pitching acceleration of the train body and the vertical contact force of the wheel-rail on the leeward side increase by 18% and 16%, respectively. The average wind speed of the incoming flow has an important effect on the aerodynamic load of the HST, especially the head train, running at the TBTS. A linear positive correlation is found between the average wind speed of the incoming flow and the corresponding change amplitude of the aerodynamic load coefficient of the head train. When the HST runs at the TBTS, the five aerodynamic loads should be loaded in the calculation process of the aerodynamic response index of the HST, and the calculated wheel-rail response results are conservative when only two aerodynamic loads are applied to the train body.

Low-Elevation Target DOA Estimation Based on Multi-Scattering Center Equivalent Model

In very-high-frequency (VHF) radar, the direction-of-arrival (DOA) estimation performance of low-angle targets tracking is strongly affected by the multipath phenomenon. Especially in the complex terrain conditions, the multipath echo comes from a region where the different scattering media make the multipath echo show the characteristics of multi-channel and uneven energy distribution. In this case, the received signal mismatches with the signal model, which leads to performance degradation and even failure of the traditional DOA algorithm. To deal with this problem, the authors propose a new signal model based on multiple scattering center. A multipath signal equivalent model is deduced and analyzed using multipath vector synthesis. Subsequently, the fitness function is established based on the equivalent model, and the target elevation angle is estimated by particle swarm optimization (PSO) algorithm. Simulation results and real data analysis show that the proposed model and algorithm can effectively improve the DOA estimation accuracy of low elevation target under complex terrain and less snapshot condition.

The influence of recreational load on the anti-erosion properties of the soils of park stands

Changes related to urban infrastructure directly affect the ecological environment, including soil properties. The purpose of this study is to investigate the anti-erosion and flow-regulating effect of park stands in complex terrain conditions of Kyiv. Forestry and tax indicators of plantings are established according to recognized tax methods. The upper layers of the soil were studied by determining the hardness, water permeability, density, and humidity on paths and in stands. Soil hardness in plantations increases from 9.1 ± 0.76-10.8 ± 1.01 kg/cm2 to 15.4 ± 0.25-30.8 ± 0.15 kg/cm2 , which is associated with the intensity of trampling them. Therewith, the soil changes from loose to medium loose and even dense. Determination of water permeability also showed a significant discrepancy, from 18.6 ± 0.76-20.6 ± 0.66 mm/min to 1.9 ± 0.10-5.7 ± 0.33 mm/min, respectively. Research has confirmed the inverse correlation between soil hardness and water permeability. The obtained indicators of soil density in the stands (1.12-1.20 g/cm3) and on the paths (1.34-1.66 g/cm3), albeit without sharp differences, in both cases indicate their criticality for further normal development of stands. Changes in soil moisture data in stands (16.9-20.6%) are decreasing in comparison with paths (11.2-12.6%), which also indicates the deterioration of growing conditions. The presence of active roots in the upper thickness of the soil on the control was 5.8-9.8 g, and on the paths, depending on the intensity of trampling, from 0.0 to 2.2 g. The territories under study were surveyed to identify characteristic erosion processes. It was established that the park spaces are in a satisfactory condition and fully perform an anti-erosion effect. The threat of erosion processes occurs on paths of intense load. The results obtained can be used for monitoring and regulating anthropogenic load

Simulated Influence of Mountainous Wind Farms Operations on Local Climate

Renewable energy sources, especially wind power, were believed to be able to slow down global warming; however, evidence in recent years shows that wind farms may also induce climate change. With the rapid development of wind power industry, the number of wind farms installed in mountains has gradually increased. Therefore, it is necessary to study the impact of wind farms in mountainous areas on local climate. The Suizhou and Dawu wind farms in northern Hubei Province were chosen for the present study on the impact of wind farm operations on the local climate in mountainous areas. The mesoscale meteorological numerical model Weather Research and Forecasting Model (WRF) and the Fitch model, together with turbulence correction factor, were used to simulate wind farm operations and study their effects on local climate. The results showed the characteristics of wind speed attenuation in mountainous wind farms: the amplitude and range of wind speed attenuation were stronger in the nighttime than in the daytime, and stronger in summer than in winter. The surface temperature increased and became more significant in summer. However, a cooling variation was observed above the surface warming center. The height of this center was higher in the daytime than it was in the nighttime. The latent heat flux in the wind farms decreased at night, accompanied by an increase in sensible heat flux. However, these changes were not significant. Some differences were observed between the impact of wind farms on the climate in the plains and the mountains. Such differences are more likely to be related to complex terrain conditions, climate conditions, and the density of wind turbines. The present study may provide support for the development and construction of wind farms in mountainous areas.

Bayesian network safety risk analysis for the dam–foundation system using Monte Carlo simulation

Gravity dams are mostly located in alpine and gorge regions with complex terrain and geological conditions, facing challenges of large peak flows, developed weak structural planes, high-stress levels, etc. The determination of failure risks of different failure modes in gravity dams is closely related to structural characteristics, materials properties, and loading conditions. However, the failure risks in the traditional risk analysis methods are usually calculated based on the expert evaluation methods and statistical data, ignoring the uniqueness of dam characteristics, and leading to an unreasonable risk assessment. Therefore, an improved probabilistic risk analysis method for the dam–foundation system using Bayesian network (BN) and Monte Carlo simulation is proposed in this study, which considers the combined action of overtopping, foundation stability, and structural failure. Based on the Monte-Carlo method, the risk analysis of overtopping is proposed by considering the influences of peak flows and maximum wind speeds, and the dam–foundation system is developed by establishing response surface equations of performance functions. Then, the BN safety risk analysis method for gravity dams is formed. This improved method is applied in the GD gravity dam project and finds that the system risk is 2.10 × 10−3. The most critical failure factor is the foundation instability, and the importance and sensitivity analysis also proved it, implying the validity and reasonability of the proposed method. Thus, the BN safety risk analysis method for gravity dams enables an improved and more reliable estimate of dam risk.

AN OPTIMIZED REMOTE SENSING RECOGNITION APPROACH FOR STRAW BURNING IN HENAN PROVINCE, CHINA

Abstract. In the paper, Henan Province with prevalent straw burning was taken as the study case. Aimed at remote sensing recognition of the straw burning fire points in a large-scale area with complex terrain and climate conditions, an optimized recognition strategy of straw burning was proposed based on the MOD021KM data. In our new recognition strategy, the threshold determination method was optimised by systematic statistical analysis of spectral features. Then the non-straw burning fire points were eliminated by extracting the agricultural land from MCD12Q1 image. Thus, the true straw-burning fire points were determined. The results showed that the recognition accuracy of straw burning fire points was effectively improved by optimized threshold determination method.

Water Inrush Mechanism of Fault Zone in Karst Tunnel under Fluid-Solid Coupling Field considering Effective Stress

At present, the tunnel construction engineering is increasingly transferring to southwest mountainous areas with complex terrain and geological conditions in China and presents a trend of “large buried depth, long tunnel line, high stress, strong karst, high water pressure, complex structure and frequent disasters.” Taking water inrush disaster of karst tunnel fault zone as the research object, an evolutionary mechanical model of rock damage under the coupling action of stress-seepage is proposed in this paper. Besides, based on Comsol Multiphysics numerical software, the tunnel excavation is simulated, and the stress field, seepage field, and rock damage during the excavation are analyzed; thus, the mechanical mechanism of water inrush disaster from tunnel fault in karst area is obtained. The research results indicate that the tunnel excavation is a dynamic construction process, and the construction disturbance redistributes the original rock stress field and changes the state of seepage field. With the increase of excavation steps, the contour distribution of vertical stress ratio near the tunnel face is a circle shape, indicating that the rock mass is obviously disturbed by excavation, and the ratio of principal stress difference of rock mass at arch crown and bottom plate is large. Besides, the fault fissures expand and penetrate under the influence of tunnel excavation disturbance, increasing the permeability of fault zone in karst tunnel. In addition, the water seepage erosion takes away the granular rock mass, and the lithology becomes more weaker, which makes it possible for the occurrence of water inrush disaster in karst tunnel. Therefore, the advanced geological prediction is important in tunnel construction in karst area. The research results can be treated as an important theoretical basis for the prevention and treatment for water inrush disaster of fault zone in karst tunnel.

CO2 exchange of the ecosystem–atmosphere in a mountain forest ecosystem: Combining stable carbon isotope (δ13C) and soil respiration measurements

Stable carbon isotopes (δ13C) are a useful technique to partition the net ecosystem–atmosphere exchange (NEE) of carbon dioxide (CO2) into gross primary productivity (GPP) and respiratory (R) components. The acquisition of ecosystem flux is usually performed using the eddy covariance (EC) technique, but this method is limited under complex terrain conditions and stable atmospheric conditions. Here, we try to develop the flux partitioning theory of mountain forest ecosystem by combining isotope technology and soil respiration. We used a full growing season of isotopic profile data and soil respiration data from a temperate deciduous forest on Jiufeng Mountain to demonstrate the method and quantify its uncertainties. We found that the assessable systematic uncertainty was ± 29.97% for NEE, ±24.87% for GPP, and ± 36.82% for R. The factors that most strongly affected the uncertainties of GPP and R were canopy CO2 stomatal conductance (gco2), calculated by the Köstner model, and the carbon isotope value of the total respiration in the ecosystem at night (δ13Cn-eco), calculated by the Keeling plot method. The advantage of isotopic methods is not only the relief of terrain restrictions but also the stable atmospheric conditions. The method provides an innovative vision for the partitioning of flux in forest ecosystems, especially for mountain forests.

Adequacy of satellite derived data for streamflow simulation in three Hexi inland river basins, Northwest China

The limited gauge measurements usually constrain the accurate hydrological modeling of runoff, especially in the ungauged or gauge-sparsely areas with complex terrain conditions. Satellite derived data provide alternative forcing data for hydrological modeling in ungauged areas, while quantitative evaluation on their performance is still needed. This study explores the adequacy and accuracy of satellite derived data based on the gauge observations over three inland river basins in the arid Hexi Corridor, Northwest China, where the satellite-based products are adopted to drive the HBV-Light model, including six satellite precipitation datasets (CHIRPS, CMORPH, GPM, GSMaP, MSWEP, PERSIANN) and the widely used evaporation product (GLEAM) combing with MODIS land surface temperature product (MOD11A1). Seven statistical metrics (CC, ME, RMSE, BIAS, POD, FAR, CSI) are adopted to assess satellite-based precipitation estimates, and three indices (NSE, R2, PBIAS) are used to evaluate the hydrological performance. Results indicate that: (1) For precipitation evaluation at point-to-pixel scale, all products have a relatively poor agreement with gauged observations with the CC ranging from 0.16 to 0.56. Both MSWEP and GPM outperformed other products at daily scale with higher CC values, and showed the capability of detecting the precipitation events with higher POD and CSI. PERSIANN, GSMaP, GPM, and CMORPH tend to underestimate the precipitation amount in three river basins. (2) For the hydrological evaluation, the statistical assessment showed that the GPM presents the best results at daily scale, while underestimates streamflow amount in three watersheds. All the grided precipitation datasets show higher NSE and R2 in the relatively humid HHRB and XYRB than SLRB. (3) The combination of MOD11A1, GLEAM and satellite-based precipitation as forcing data of the HBV-Light can achieve good performance in the three inland river basins. This study aims to provide an additional reference for the hydrological application of satellite derived data in gauge-sparsely areas located in high altitude and arid regions.

Development of visual helicopter emergency rescue system

Abstract Helicopter rescue is an important part of emergency rescue syste m, an d is oft en ca r r ie d out under complex terrain and low-visibility meteorological conditions. In order to ensure the safety of helicopter flight and the timely and efficient implementation of emergency rescue, it is necessary to establish a visual emergency rescue system. This paper selects Chongqing as the reference city, and it is preliminarily planned to take “GeoSim” as the 3D simulation platform, combined with the secondary development technology of geographic information system (GIS). According to the current flight performance of helicopters, and through the analysis of obstacle crossing, the intelligent algorithm can realize the visual simulation demonstration of single helicopter rescue system and multi-helicopter rescue system along the optimized path and user-defined path, and give the quality evaluation of emergency rescue drills, as well as the suggestions of the best emergency rescue plan.

Incorporation of Net Radiation Model Considering Complex Terrain in Evapotranspiration Determination with Sentinel-2 Data

Evapotranspiration (ET) is the primary mechanism of water transformation between the land surface and atmosphere. Accurate ET estimation given complex terrain conditions is essential to guide water resource management in mountainous areas. This study is based on the ETWatch model driven by Sentinel-2 remote sensing data at a spatial resolution of 10 m incorporating a net radiation model considering the impact of a complex terrain. We tested our model with two years of data in two regions with a high relief near the Huairou (2020) and Baotianman (2019) weather stations. Regarding the validation results of the ET model, the coefficient of determination (R2) reached 0.84 in Huairou and 0.86 in Baotianman, while the root mean square error (RMSE) value reached 0.59 mm in Baotianman and 0.82 mm in Huairou. The validation results indicated that the model is applicable in regions with a complex terrain, and the ET results can capture topographic textures. In terms of the slope aspect, the ET value on south-facing slopes is higher than that on north-facing slopes in both study areas. Accurate ET monitoring in mountainous regions with a high relief yields a profound meaning in obtaining a better understanding of the characteristics of heat and water fluxes at different vegetation growth stages and underlying surface types, which can provide constructive suggestions for water management in mountainous areas.

The influence of depositional and diagenetic processes on rock electrical properties: A case study of the Longmaxi shale in the Sichuan Basin

Primary depositional and diagenetic processes exert very important influences on shale gas reservoirs. Rock electrical properties are an important basis for making reservoir prediction using the electromagnetic method (EM). However, there is still a lack of understanding about the impact of the sedimentary diagenesis process on shale electrical properties, this study focuses on the impact of diagenesis on rock properties. In this study, rock electrical properties are studied based on electromagnetic experiments. We systematically studied the lithofacies of different depositional paleoenvironments and diagenetic processes, and the influence of diagenetic evolution on the rock electrical properties was discussed, by means of X-ray diffraction (XRD) analysis, field-emission scanning electron microscopy (FE-SEM), low-temperature nitrogen adsorption (LTNA), and trace element (TE) geochemical analysis. Based on the study of mineral composition, grain assemblages and pore systems, we identified four lithofacies in the Longmaxi Formation: siliceous shale, siliceous-argillaceous mixed shale, silty shale and argillaceous shale. Redox proxies (U/Th, V/Cr, and Ni/Co) indicate that the siliceous shale was deposited in a relatively anoxic and reducing environment, indicating a deep-water shelf depositional paleoenvironment. The siliceous-argillaceous shale, silty shale and argillaceous shale were deposited under a relatively dysoxic-oxic environment, indicating a shallow-water shelf depositional paleoenvironment. The order of resistivity values of the lithofacies within the Longmaxi Formation is 36.78 Ω m (siliceous shale), 66.81 Ω m (siliceous-argillaceous mixed shale), 79.54 Ω m (silty shale), and 107.00 Ω m (argillaceous shale), and the resistivity decreases with an increase in porosity. The siliceous shale has the most abundant authigenic quartz, which filled the primary pores forming a rigid framework during the gas window, inhibited compaction, increased the distribution of organic matter (OM), and enhanced the development of OM pores. The high TOC content and high maturity of siliceous shale at the bottom of Longmaxi Formation make the OM pores more developed. Pyrite, conductive fluid and pore network under the main control of OM pores in shale form a conductive circuit when AC voltage is input, which increases the exchange capacity of cations and leads to the phenomenon of low resistivity. The interconnected OM pore network, both depositionally and diagenetically derived, affects the electrical properties of the Longmaxi shale. This study reveals that electrical properties of shale rocks and its variations can be impacted by the depositional environment and diagenetic processes. This work provides resistivity parameters for the electromagnetic exploration of shale gas under complex terrain conditions and provides a theoretical basis for later interpretation.

An evaluation of the performance of IMERG hourly precipitation estimates in a geographical sub-region with complex terrain and climate conditions: a case study in the upper Red River Basin

ABSTRACT This study comprehensively evaluates four satellite precipitation estimates (SPE) of the version 6 (V06) of Integrated Multi-satellite Retrievals for Global Precipitation Measurement Mission (IMERG) at hourly scale in the upper Red River Basin (URRB), located in Yunnan, by applying 12 rain gauges during the rainy season (May to October) from 2019 to 2020. Four SPE includes IMERG-E, IMERG-L, IMERG-FU and IMERG-FC, with IMERG-FC is calibrated by the Global Precipitation Climatology Centre (GPCC) gauge. Due to the complex terrain of the URRB, we divide the URRB into three subregions. The evaluation considers precipitation detection capability (POD, FAR and CSI), correlation (CC), error situation (RMSE and RBIAS) and the quantitative analysis index (CPI). The results show that (1) among these SPE, IMERG-FC always has higher POD and FAR, better correlation and larger RBIAS. (2) In the URRB, the results produced by all SPE are overestimates compared to ground-based observations (GBO). And, the detection capability of IMERG is better in the low precipitation threshold but worsens with the increasing precipitation thresholds. (3) IMERG shows worse performance in the dry-hot valley than in the other two areas. (4) The performance of IMERG-L is better than IMERG-FC and other SPE in the URRB.

Retrieval of forest canopy height in a mountainous region with ICESat-2 ATLAS

Forest canopy height is one of the important forest parameters for accurately assessing forest biomass or carbon sequestration. ICESat-2 ATLAS provides the potential for retrieval of forest canopy height at global or regional scale, but the current canopy height product (ATL08) has coarse resolution and high uncertainty compared to airborne LiDAR-derived canopy height (hereafter ALCH) in mountainous regions, and is not ready for such applications as biomass modeling at finer scale. The objective of this research was to explore the approach to accurately retrieve canopy height from ATLAS data by incorporating an airborne-derived digital terrain model (DTM) and a data-filtering strategy. By linking ATLAS ATL03 with ATL08 products, the geospatial locations, types, and (absolute) heights of photons were obtained, and canopy heights at different lengths (from 20 to 200 ​m at 20-m intervals) of segments along a track were computed with the aid of airborne LiDAR DTM. Based on the relationship between the numbers of canopy photons within the segments and accuracy of ATLAS mean canopy height compared to ALCH, a filtering method for excluding a certain portion of unreliable segments was proposed. This method was further applied to different ATLAS ground tracks for retrieval of canopy heights and the results were evaluated using corresponding ALCH. The results show that the incorporation of high-precision DTM and ATLAS products can considerably improve the retrieval accuracy of forest canopy height in mountainous regions. Using the proposed filtering approach, the correlation coefficients (r) between ATLAS canopy height and corresponding ALCH were 0.61–0.91, 0.65–0.92, 0.68–0.94 for segment lengths of 20, 60, and 100 ​m, respectively; RMSE were 1.90–4.35, 1.55–3.63, and 1.34–3.23 ​m for the same segment lengths. The results indicate the necessity of using high-precision DTM and using the proposed filtering method to retrieve accurate canopy height from ICESat-2 ATLAS in mountainous regions with dense forest cover and complex terrain conditions.

A Fusion Method Using Terrestrial Laser Scanning and Unmanned Aerial Vehicle Photogrammetry for Landslide Deformation Monitoring Under Complex Terrain Conditions

Landslides are one of the major factors threatening human life and social development. Monitoring and early warning of landslides are important parts of disaster prevention and control. However, due to complex terrain conditions, landslide monitoring in mountainous watersheds and high mountain valleys usually faces issues of high difficulty, high danger, poor data integrity and low data accuracy compared with plains or hilly areas. Based on the fusion of terrestrial laser scanning (TLS) and unmanned aerial vehicle (UAV) photogrammetry, this paper proposes a landslide deformation monitoring method that can be applied to complex terrain conditions where there are access restrictions and blind areas. The method is based on TLS to increase the number and range of ground control points (GCPs) of UAVs within the visual range and then uses assumed control points (ACPs) to reconstruct the UAV model and calculate landslide displacement in invisible areas. In addition, this paper proposes and verifies a formula based on an allometricl equation to estimate the error between the calculated and real displacements based on this method. Then, we applied this method to a real landslide case and successfully realized landslide monitoring under the conditions of access limitation and blind areas. The proposed method enables landslide monitoring to overcome terrain restrictions, and it makes it possible to perform large-scale and high-precision ground deformation measurements with limited working ranges, which can be an effective tool for landslide monitoring in emergency situations and long-term risk evaluation.

Improving the Near-Surface Wind Forecast around the Turpan Basin of the Northwest China by Using the WRF_TopoWind Model

Wind energy is a type of renewable and clean energy which has attracted more and more attention all over the world. The Northwest China is a region with the most abundant wind energy not only in China, but also in the whole world. To achieve the goal of carbon neutralization, there is an urgent need to make full use of wind energy in Northwest China and to improve the efficiency of wind power generation systems in this region. As forecast accuracy of the near-surface wind is crucial to wind-generated electricity efficiency, improving the near-surface wind forecast is of great importance. This study conducted the first test to incorporate the subgrid surface drag into the near-surface wind forecast under the complex terrain conditions over Northwest China by using two TopoWind models added by newer versions of the Weather Research and Forecasting (WRF) model. Based on three groups (each group had 28 runs) of forecasts (i.e., Control run, Test 01 and Test 02) started at 12:00 UTC of each day (ran for 48 h) during the period of 1–28 October 2020, it was shown that, overall, both TopoWind models could improve the near-surface wind speed forecasts under the complex terrain conditions over Northwest China, particularly for reducing the errors associated with the forecast of the wind-speed’s magnitude. In addition to wind forecast, the forecasts of sea level pressure and 2-m temperature were also improved. Different geographical features (wind-farm stations located south of the mountain tended to have more accurate forecast) and weather systems were found to be crucial to forecast accuracy. Good forecasts tended to appear when the simulation domain was mainly controlled by the high-pressure systems with the upper-level jet far from it.

Experimental analysis of zero-natural-frequency damper for transmission line large cross project based on NES

The operation experience of transmission line large cross project shows that the traditional anti-aeolian-vibration devices had poor adaptability to complex terrain and micro meteorological conditions, and they were difficult to meet the application requirements of super large cross project at this stage. A zero-natural-frequency damper was designed by introducing nonlinear energy sink in this paper, and the solid prototypes were processed. According to the actual design parameters of conductor using in a large cross project, the anti-vibration effect was tested by using the indoor simulation test span. The test results showed that the anti-vibration effect of the scheme based on the zero-natural-frequency damper could meet the needs of practical engineering. The installation of this damper could improve conductors’ and fittings’ adaptability to complex terrain and enhance the wind and anti-vibration ability of transmission line.

Intention prediction of UAVs based on improved DDQN

Intention prediction plays an indispensable role in future informationized air combat, which will help the command and control center to make a more correct decision. In this paper, an intelligent intention prediction approach based on an improved double deep Q network (DDQN) is developed to generate real-time intention flight paths for unmanned aerial vehicles (UAVs) in complex air combat environment. Initially, by introducing an actual topographic map, the different threats of UAVs in different terrains on the map are analyzed, based on which, a terrain environment reward function is constructed. Secondly, by splitting a complete maneuver action into six basic maneuver units and determining the probability value of each unit, a maneuver reward function is obtained. Further, to improve the real-time performance and accuracy of the standard DDQN algorithm, an improved DDQN algorithm is proposed by using temporal-difference (TD) method and binary tree data structure. Finally, the simulation results verify show that the proposed algorithm has achieved better results under complex terrain conditions.