Ground failure in Adapazari, Turkey during the 1999 Kocaeli earthquake was severe. Hundreds of structures settled, slid, tilted, and collapsed due in part to liquefaction and ground softening. Ground failure was more severe adjacent to and under buildings. The soils that led to severe building damage were generally low plasticity silts. In this paper, the results of a comprehensive investigation of the soils of Adapazari, which included cone penetration test (CPT) profiles followed by borings with standard penetration tests (SPTs) and soil index tests, are presented. The effects of subsurface conditions on the occurrence of ground failure and its resulting effect on building performance are explored through representative case histories. CPT- and SPT-based liquefaction triggering procedures adequately identified soils that liquefied if the clay-size criterion of the Chinese criteria was disregarded. The CPT was able to identify thin seams of loose liquefiable silt, and the SPT (with retrieved samples) allowed for reliable evaluation of the liquefaction susceptibility of fine-grained soils. A well-documented database of in situ and index testing is now available for incorporating in future CPT- and SPT-based liquefaction triggering correlations. 相似文献
The influencing mechanisms of elements Ti and Ce and their interactions on fracture behaviors of casting alloys Al-4.5Cu-0.6Mn were studied by observing tensile fracture behavior in quasi-solid zone under SEM and EDX instruments.The results indicate that the resistance stress against hot cracking can be improved obviously by addition of Ti, because of its grain refining function. It is also found that, when Ce is added into the alloys, besides its effect in refining crystalline, the mechanical behavior of lower melting point eutectic phase in quasi-solid zone can be improved efficiently by some compounds with Ce formed and deposited between dendrites. Therefore, a coiligating effect of Ti and Ce on improving resistance stress against hot cracking is more efficient than that only single alloy element is applied. When hot cracking occurs, grains yield at first, and then crack spreads. Both inter-grain and trans-grain fractures are observed, but the major fracture manner is brittleness. 相似文献
Unmanned aerial vehicles have been widely used in many areas of life. They communicate with each other or infrastructure to provide ubiquitous coverage or assist cellular and sensor networks. They construct flying ad hoc networks. One of the most significant problems in such networks is communication among them over a shared medium. Using random channel access techniques is a useful solution. Another important problem is that the variations in the density of these networks impact the quality of service and introduce many challenges. This paper presents a novel density-aware technique for flying ad hoc networks. We propose Density-aware Slotted ALOHA Protocol that utilizes slotted ALOHA with a dynamic random access probability determined using network density in a distributed fashion. Compared to the literature, this paper concentrates on proposing a three-dimensional, easily traceable model and stabilize the channel utilization performance of slotted ALOHA with an optimized channel access probability to its maximum theoretical level, 1/e, where e is the Euler’s number. Monte-Carlo simulation results validate the proposed approach leveraging aggregate interference density estimator under the simple path-loss model. We compare our protocol with two existing protocols, which are Slotted ALOHA and Stabilized Slotted ALOHA. Comparison results show that the proposed protocol has 36.78% channel utilization performance; on the other hand, the other protocols have 24.74% and 30.32% channel utilization performances, respectively. Considering the stable results and accuracy, this model is practicable in highly dynamic networks even if the network is sparse or dense under higher mobility and reasonable non-uniform deployments.
While malicious samples are widely found in many application fields of machine learning, suitable countermeasures have been investigated in the field of adversarial machine learning. Due to the importance and popularity of Support Vector Machines (SVMs), we first describe the evasion attack against SVM classification and then propose a defense strategy in this paper. The evasion attack utilizes the classification surface of SVM to iteratively find the minimal perturbations that mislead the nonlinear classifier. Specially, we propose what is called a vulnerability function to measure the vulnerability of the SVM classifiers. Utilizing this vulnerability function, we put forward an effective defense strategy based on the kernel optimization of SVMs with Gaussian kernel against the evasion attack. Our defense method is verified to be very effective on the benchmark datasets, and the SVM classifier becomes more robust after using our kernel optimization scheme. 相似文献
Engineering design has great importance in the cost and safety of engineering structures. Rock mass rating (RMR) system has
become a reliable and widespread pre-design system for its ease of use and variety in engineering applications such as tunnels,
foundations, and slopes. In RMR system, six parameters are employed in classifying a rock mass: uniaxial compressive strength
of intact rock material (UCS), rock quality designation (RQD), spacing of discontinuities (SD), condition of discontinuities
(CD), condition of groundwater (CG), and orientation of discontinuities (OD). The ratings of the first three parameters UCS,
RQD, and SD are determined via graphic readings where the last three parameters CD, CG, and OD are estimated by the tables
that are composed of interval valued linguistic expressions. Because of these linguistic expresions, the estimated rating
values of the last three become fuzzy especially when the related conditions are close to border of any two classes. In such
cases, these fuzzy situations could lead up incorrect rock class estimations. In this study, an empirical database based on
the linguistic expressions for CD, CG, and OD is developed for training Artificial Neural Network (ANN) classifiers. The results
obtained from graphical readings and ANN classifiers are unified in a simulation model (USM). The data obtained from five
different tunnels, which were excavated for derivation purpose, are used to evaluate classification results of conventional
method and proposed model. Finally, it is noted that more accurate and realistic ratings are reached by means of proposed
model. 相似文献
Polymer-encapsulated phthalocyanine blue pigment dispersion was prepared with a polymerizable dispersant by emulsion polymerization method, and the effect of preparation conditions on the particle size of dispersion was investigated. Dynamic light scattering measurement demonstrated that allyloxy nonyl-phenoxypropanolpolyoxyethyleneetherammonium sulfonate (ANPS) was suitable for phthalocyanine blue pigment modification. The polymer-encapsulated phthalocyanine blue pigment dispersion with the small particles was obtained when the mass ratio of ANPS to phthalocyanine blue pigment, styrene (St) to phthalocyanine blue pigment, and ammonium persulfate (APS) to St was about 0.2, 0.2, and 0.01, respectively. Transmission electron microscopy (TEM), Fourier transforms infrared spectra (FTIR) and thermogravimetric analyses (TGA) provided supporting evidences for the encapsulation of phthalocyanine blue pigment with the formed copolymer. The polymer-encapsulated phthalocyanine blue pigment dispersion showed excellent stabilities to freeze–thaw treatment and centrifugal force. 相似文献