Experimental Study on Stress and Strain Characteristics of Solidified Clay under Seawater Condition

This paper presents the results of a laboratory study on the stress-strain relationship of solidified clay formed in seawater corrosion condition. An automatic triaxial apparatus was used and the axial stress and strain was monitored continuously. The dry density was 1.0g/cm3, the cement contents were 4, 6, 8 and 10% by weight of dry soil particles, and the curing time was 28, 60 and 90 days respectively. Test results indicate that the stress strain relationship of cemented clay was affected by soil density, cement content and curing period. A behaviour of strain hardening to strain softening occurred with the increase of cement content. Strong structure will form in cemented clay when the admixture content is 10% or more. The increase in strength of the solidified foundation is resulted from the increase in internal friction angle and cohesive force. The cohesive force increases obviously with the increase of the cement content and the curing age, but the change of internal friction angle is not pronounced after reaching a certain value

The state-of-the-art of soot load estimation in diesel particulate filters: A review

Diesel particulate filter (DPF), as part of aftertreatment system of internal combustion engine, is considered to be the only feasible way to prominently lessen particle emissions under the requirement of today’s strict regulations such as Euro Ⅵ, US Tier 3 and China Ⅵ. This paper gives a brief introduction of the mechanism and regeneration approaches of DPF, with emphasis on soot load estimation inside the filters, which plays a vital role in formulating regeneration control strategy and ensuring exhaust systemic dependability. Various methods are covered according to different principles, including differential-pressure based methods, which are mostly used nowadays, novel model-based methods and also several newfangled soot sensors, which are progressively developed to meet the increasingly stringent on-board diagnosis (OBD) requirements. The focus of future soot detection and quantitative prediction is to improve accuracy, reliability and robustness, which may necessitate consideration of soot distribution, ash effect, failure identification and fault tolerance handling

Research on Lazy Theta* Route Planning Algorithm Based on Grid Point Optimization

In recent years, the problem of route planning in complex battlefield environments has attracted significant attention. With the increasingly worrying international situation, safety and flyability in a continuously changing threat environment are critical factors in route planning research. Thus, this paper proposes an improved Lazy Theta* algorithm that adapts to a complex battlefield environment and finds the optimal route. Specifically, given the low computational efficiency and data redundancy of the existing environmental threat modeling, the developed scheme first employs an octree grid to divide the environment into a grid. Furthermore, based on a real environmental threat model and flight constraints, we design a Lazy Theta* algorithm based on octree grid points, which shortens the planning path and reduces the path cost. Finally, this paper proposes an equally spaced B-spline to smooth the route and improve its smoothness and flyability. Several simulated experiments verify that the smoothed route improves safety and flight ability while reducing the route’s distance. Overall, the simulation results prove that the proposed method significantly improves the planning efficiency and flyability compared with traditional methods

Research on Lazy Theta* Route Planning Algorithm Based on Grid Point Optimization

In recent years, the problem of route planning in complex battlefield environments has attracted significant attention. With the increasingly worrying international situation, safety and flyability in a continuously changing threat environment are critical factors in route planning research. Thus, this paper proposes an improved Lazy Theta* algorithm that adapts to a complex battlefield environment and finds the optimal route. Specifically, given the low computational efficiency and data redundancy of the existing environmental threat modeling, the developed scheme first employs an octree grid to divide the environment into a grid. Furthermore, based on a real environmental threat model and flight constraints, we design a Lazy Theta* algorithm based on octree grid points, which shortens the planning path and reduces the path cost. Finally, this paper proposes an equally spaced B-spline to smooth the route and improve its smoothness and flyability. Several simulated experiments verify that the smoothed route improves safety and flight ability while reducing the route’s distance. Overall, the simulation results prove that the proposed method significantly improves the planning efficiency and flyability compared with traditional methods

Inner Dynamic Detection and Prediction of Water Quality Based on CEEMDAN and GA-SVM Models

Urban water quality is facing strongly adverse degradation in rapidly developing areas. However, there exists a huge challenge to estimating the inner features and predicting the variation of long-term water quality due to the lack of related monitoring data and the complexity of urban water systems. Fortunately, multi-remote sensing data, such as nighttime light and evapotranspiration (ET), provide scientific data support and reasonably reveal the variation mechanisms. Here, we develop an integrated decomposition-reclassification-prediction method for water quality by integrating the CEEMDN method, the RF method mothed, and the genetic algorithm-support vector machine model (GA-SVM). The degression of the long-term water quality was decomposed and reclassified into three different frequency terms, i.e., high-frequency, low-frequency, and trend terms, to reveal the inner mechanism and dynamics in the CEEMDAN method. The RF method was then used to identify the teleconnection and the significance of the selected driving factors. More importantly, the GA-SVM model was designed with two types of model schemes, which were the data-driven model (GA-SVMd) and the integrated CEEMDAN-GA-SVM model (defined as GA-SVMc model), in order to predict urban water quality. Results revealed that the high-frequency terms for NH3-N and TN had a major contribution to the water quality and were mainly dominated by hydrometeorological factors such as ET, rainfall, and the dynamics of the lake water table. The trend terms revealed that the water quality continuously deteriorated during the study period; the terms were mainly regulated by the land use and land cover (LULC), land metrics, population, and yearly rainfall. The predicting results confirmed that the integrated GA-SVMc model had better performance than single data-driven models (such as the GA-SVM model). Our study supports that the integrated method reveals variation rules in water quality and provides early warning and guidance for reducing the water pollutant concentration

Inner Dynamic Detection and Prediction of Water Quality Based on CEEMDAN and GA-SVM Models

Urban water quality is facing strongly adverse degradation in rapidly developing areas. However, there exists a huge challenge to estimating the inner features and predicting the variation of long-term water quality due to the lack of related monitoring data and the complexity of urban water systems. Fortunately, multi-remote sensing data, such as nighttime light and evapotranspiration (ET), provide scientific data support and reasonably reveal the variation mechanisms. Here, we develop an integrated decomposition-reclassification-prediction method for water quality by integrating the CEEMDN method, the RF method mothed, and the genetic algorithm-support vector machine model (GA-SVM). The degression of the long-term water quality was decomposed and reclassified into three different frequency terms, i.e., high-frequency, low-frequency, and trend terms, to reveal the inner mechanism and dynamics in the CEEMDAN method. The RF method was then used to identify the teleconnection and the significance of the selected driving factors. More importantly, the GA-SVM model was designed with two types of model schemes, which were the data-driven model (GA-SVMd) and the integrated CEEMDAN-GA-SVM model (defined as GA-SVMc model), in order to predict urban water quality. Results revealed that the high-frequency terms for NH3-N and TN had a major contribution to the water quality and were mainly dominated by hydrometeorological factors such as ET, rainfall, and the dynamics of the lake water table. The trend terms revealed that the water quality continuously deteriorated during the study period; the terms were mainly regulated by the land use and land cover (LULC), land metrics, population, and yearly rainfall. The predicting results confirmed that the integrated GA-SVMc model had better performance than single data-driven models (such as the GA-SVM model). Our study supports that the integrated method reveals variation rules in water quality and provides early warning and guidance for reducing the water pollutant concentration

Experimental Study on Stress and Strain Characteristics of Solidified Clay under Seawater Condition

This paper presents the results of a laboratory study on the stress-strain relationship of solidified clay formed in seawater corrosion condition. An automatic triaxial apparatus was used and the axial stress and strain was monitored continuously. The dry density was 1.0g/cm3, the cement contents were 4, 6, 8 and 10% by weight of dry soil particles, and the curing time was 28, 60 and 90 days respectively. Test results indicate that the stress strain relationship of cemented clay was affected by soil density, cement content and curing period. A behaviour of strain hardening to strain softening occurred with the increase of cement content. Strong structure will form in cemented clay when the admixture content is 10% or more. The increase in strength of the solidified foundation is resulted from the increase in internal friction angle and cohesive force. The cohesive force increases obviously with the increase of the cement content and the curing age, but the change of internal friction angle is not pronounced after reaching a certain value

Clustering Method of Large-Scale Battlefield Airspace Based on Multi A * in Airspace Grid System

Aiming at the problem of the wide range and great difficulty in the future of battlefield airspace control, based on the unique advantages of an airspace grid system in an airspace grid representation and time–space binary computing, this paper designs a pre-clustering method for mission airspace based on airspace location correlation under the condition of future large-scale air combat missions in order to realize the block control of battlefield airspace. This method reduces the whole 3D battlefield space projection to a 2D plane and regards the task airspace projection as “obstacles” in the task area; Multi-A * algorithm is used to generate the airspace clustering line surrounding the task airspace, and the airspace association clustering problem is transformed into a multiple “start point-end point” path planning problem with autonomous optimization. Through the experiment, it was found that clustering the airspace can effectively improve the management and control efficiency of large-scale battlefield airspace

Clustering Method of Large-Scale Battlefield Airspace Based on Multi A * in Airspace Grid System

Aiming at the problem of the wide range and great difficulty in the future of battlefield airspace control, based on the unique advantages of an airspace grid system in an airspace grid representation and time–space binary computing, this paper designs a pre-clustering method for mission airspace based on airspace location correlation under the condition of future large-scale air combat missions in order to realize the block control of battlefield airspace. This method reduces the whole 3D battlefield space projection to a 2D plane and regards the task airspace projection as “obstacles” in the task area; Multi-A * algorithm is used to generate the airspace clustering line surrounding the task airspace, and the airspace association clustering problem is transformed into a multiple “start point-end point” path planning problem with autonomous optimization. Through the experiment, it was found that clustering the airspace can effectively improve the management and control efficiency of large-scale battlefield airspace

Dual-Band MIMO Antenna for 5G/WLAN Mobile Terminals

This paper presents a dual-band four-element multiple-input-multiple-output (MIMO) array for the fifth generation (5G) mobile communication. The proposed antenna is composed of an open-loop ring resonator feeding element and a T-shaped radiating element. The utilization of the open-loop ring resonator not only reduces the size of the antenna element, but also provides positive cross-coupling. The dimension of a single antenna element is 14.9 mm × 7 mm (0.27λ × 0.13λ, where λ is the wavelength of 5.5 GHz). The MIMO antenna exhibits a dual-band feature from 3.3 to 3.84 GHz and 4.61 to 5.91 GHz, which can cover 5G New Radio N78 (3.3–3.8 GHz), 5G China Band N79 (4.8–5 GHz), and IEEE 802.11 ac (5.15–5.35 GHz, 5.725–5.85 GHz). The measured total efficiency and isolation are better than 70% and 15 dB, respectively. The calculated envelope correlation coefficient (ECC) is less than 0.02. The measured results are in good agreement with the simulated results