Search

The acquisition of landslide inventory represents a pivotal challenge in landslide susceptibility mapping. Existing landslide susceptibility maps(LSMs) predominantly rely on manually obtained landslide inventories, leading to an overdependence on expert insights and susceptibilities to topographic and geomorphic influences. In regions characterized by steep terrain, obtaining a landslide inventory can be arduous or even unattainable, subsequently constraining the utility of LSMs. Addressing the limitations of conventional LSMs, this study introduces an innovative method for landslide inventory compilation and LSM creation, utilizing Small Baselines Subset Interferometry Synthetic Aperture Radar(SBAS-InSAR) technology. The study area selected for illustration is the Dongchuan district, notorious for frequent landslide occurrences. The application of SBAS-InSAR facilitated the extraction of surface deformation data, subsequently enabling the selection of landslide deformation points as samples. These samples underwent analysis through a particle swarm optimization-backpropagation neural network(PSO-BPNN) guided by deformation thresholds and the landslide developmental environment. This produced the LSM for the Dongchuan district. Subsequent validation of the LSM employed both qualitative and quantitative measures. Results elucidate that the LSM, as derived from the presented approach, primarily highlights high to very high susceptibility zones in landslide-prone areas, mirroring the spatial distribution of historical landslides. The method also achieved a commendable accuracy(ACC) of 79.59% and an area under the curve(AUC) value of 0.88. Notably, the landslide density exhibited a direct correlation with increasing susceptibility class. Such findings align with previous studies, endorsing the feasibility and reliability of the proposed approach.

Among non-destructive testing (NDT) techniques, fast neutron radiography with a higher penetration capability has achieved rapid advancements. However, the application of the radiography detector in many fast neutron imaging systems is limited by unfavorable detection efficiency and imaging spatial resolution. In this paper, a fast neutron radiography detector was designed, which was composed of a pixelated EJ200 scintillator array, a 16 × 16 silicon photomultiplier (SiPM) array, and capacitive multiplexing network readout electronics. The main parameters of the detector were optimized using Monte Carlo simulations. In addition, the prototype of the detector was fabricated and tested under a 14 MeV D-T neutron source. The preliminary test results demonstrated that the spatial resolution of the prototype reached 1.2 mm. Moreover, the conflict between spatial resolution and detection efficiency could be mitigated by using a pixelated scintillator structure. Overall, SiPMs enabled the extensive application of the imaging system because of their excellent photon detection performance, relatively low price, and joint possibility for large areas.

Currently, the high-purity single crystal diamond preparation is still a challenging task, which restricts the application of diamond in electronics. In this paper, the chemical vapor deposition (CVD) IIa type single crystal diamond was prepared on the IIa type high pressure high temperature (HPHT) substrate by combining the chamber design with the plasma purifying technology, and the performance of diamond detectors using both IIa type single crystal diamonds were compared based on the defect analysis. The dislocations in diamonds were directly observed by synchrotron radiation X-ray white-beam topography. The CVD diamond shows the comparatively low dislocation density resulting from the high-quality HPHT diamond substrate. No observable NV impurity could be found in photoluminescence (PL) spectrum. The trace impurity of substitutional nitrogen (Ns) was characterized by electron paramagnetic resonance (EPR). It shows the very low concentration in the CVD diamond (2.1 ppb) compared with the several tens ppb in HPHT diamond. This value is comparable with the electronic-grade diamond reported by Element Six. Furthermore, both of the HPHT and CVD single crystal diamonds were packaged as the α-particle radiation detectors with the typical sandwich structure and used Ni/Al (50 nm/500 nm) as metal electrodes. The energy resolution of HPHT and CVD diamond detectors were 2.04% and 0.86%, respectively. Based on Schottky contact and defect regulation, at 0 voltage, the CVD diamond detector achieved response of α-particle radiation and the charge collection efficiency (CCE) was 10.76%. Under positive voltage, the CCE of HPHT and CVD diamond detectors were 38.11% and 86.65%, respectively. The deep level trapping effect of Ns impurities on charge carriers resulted in low CCE of HPHT diamond detector. The spatial polarization effect caused by defects leaded to the formation of an internal electric field, which was the main reason affecting the transport of charge carriers in CVD diamond.

Landslide susceptibility maps (LSM) are often used by government departments to carry out land use management and planning, which supports decision makers in urban and infrastructure planning. The accuracy of conventional landslide susceptibility maps is often affected by classification errors. Consequently, they become less reliable, which makes it difficult to meet the needs of decision-makers. Therefore, it is proposed in this paper to reduce classification errors and improve LSM reliability by integrating the Small Baseline Subsets-Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique and LSM. By using the logistic regression model (LR) and the support vector machine model (SVM), experiments were conducted to generate LSM in the Dongchuan district. It was classified into five classes: very high susceptibility, high susceptibility, medium susceptibility, low susceptibility, and very low susceptibility. Then, the surface deformation rate of the Dongchuan area was obtained through the ascending and descending orbit sentinel-1A data from January 2018 to January 2021. To correct the classification errors, the SBAS-InSAR technique was integrated into LSM under the optimal model by constructing the contingency matrix. Finally, the LSMs obtained before and after correction were compared. Moreover, the correction results were validated and analyzed by combining remote sensing images, InSAR deformation results, and field surveys. According to the research results, the susceptibility class of 66,094 classification error cells (59.48 km2) was significantly improved in the LSM after the integration of the SBAS-InSAR correction. The enhanced susceptibility classes and the spectral characteristics of remote sensing images are highly consistent with the trends of InSAR cumulative deformation and the results of field investigation. It is suggested that integrating SBAS-InSAR and LSM is effective in correcting classification errors and further improving the reliability of LSM for landslide prediction. The LSM obtained by using this method plays an important role in guiding local government departments on disaster prevention and mitigation, which is conducive to eliminating the risk of landslides.

Influence of alternating current (AC) on pitting corrosion and stress corrosion cracking (SCC) behavior of X70 pipeline steel in the near-neutral pH environment under cathodic protection (CP) was investigated. Both corrosion and SCC are inhibited by −0.775 VSCE CP without AC interference. With the superimposition of AC current (1–10 mA/cm2), the direct current (DC) potential shifts negatively under the CP of −0.775 VSCE and the cathodic DC current decreases and shifts to the anodic direction. Under the CP potential of −0.95 VSCE and −1.2 VSCE, the applied AC current promotes the cathodic reaction and leads to the positive shift of DC potential and increase of cathodic current. Local anodic dissolution occurs attributing to the generated anodic current transients in the positive half-cycle of the AC current, resulting in the initiation of corrosion pits (0.6–2 μm in diameter). AC enhances the SCC susceptibility of X70 steel under −0.775 VSCE CP, attributing to the promotion of anodic dissolution and hydrogen evolution. Even an AC current as low as 1 mA/cm2 can enhance the SCC susceptibility.