Observation and Analysis of Settlements of Oil Tanks on High Compressive Saturated Soft Clay

This paper summarizes the experiences obtained in the design and construction of oil tank foundations on untreated high compressive saturated soft clay. Through the study and analysis of the various data collected from long-term observation, the author has proposed a number of suggestions on the designing of the foundation of oil tanks, the calculation of the deformation of tank floors, allowable differential settlement and the spacing of tanks. In addition, the paper also gives an account of the behaviour of the site and the deformation of tanks resulting from the Tangshan Earthquake

ATP-Dependent Mismatch Recognition in DNA Replication Mismatch Repair

Mismatch repair is a critical step in DNA replication that occurs after base selection and proofreading, significantly increasing fidelity. However, the mechanism of mismatch recognition has not been established for any repair enzyme. Speculations in this area mainly focus on exploiting thermodynamic equilibrium and free energy. Nevertheless, non-equilibrium processes may play a more significant role in enhancing mismatch recognition accuracy by utilizing adenosine triphosphate (ATP). This study aimed to investigate this possibility. Considering our limited knowledge of actual mismatch repair enzymes, we proposed a hypothetical enzyme that operates as a quantum system with three discrete energy levels. When the enzyme is raised to its highest energy level, a quantum transition occurs, leading to one of two low-energy levels representing potential recognition outcomes: a correct match or a mismatch. The probabilities of the two outcomes are exponentially different, determined by the energy gap between the two low energy levels. By flipping the energy gap, discrimination between mismatches and correct matches can be achieved. Within a framework that combines quantum mechanics with thermodynamics, we established a relationship between energy cost and the recognition error.Comment: 15 pages, 8 figure

Linear convergence of the Collatz method for computing the Perron eigenpair of primitive dual number matrix

Very recently, Qi and Cui extended the Perron-Frobenius theory to dual number matrices with primitive and irreducible nonnegative standard parts and proved that they have Perron eigenpair and Perron-Frobenius eigenpair. The Collatz method was also extended to find Perron eigenpair. Qi and Cui proposed two conjectures. One is the k-order power of a dual number matrix tends to zero if and only if the spectral radius of its standard part less than one, and another is the linear convergence of the Collatz method. In this paper, we confirm these conjectures and provide theoretical proof. The main contribution is to show that the Collatz method R-linearly converges with an explicit rate.Comment: arXiv admin note: text overlap with arXiv:2306.16140 by other author

Correlation of microstructure and thermo-mechanical properties of a novel hydrogen transport membrane

Thesis (Ph.D.) University of Alaska Fairbanks, 2014A key part of the FutureGen concept is to support the production of hydrogen to fuel a 'hydrogen economy,' with the use of clean burning hydrogen in power-producing fuel cells, as well as for use as a transportation fuel. One of the key technical barriers to FutureGen deployment is reliable and efficient hydrogen separation technology. Most Hydrogen Transport Membrane (HTM) research currently focuses on separation technology and hydrogen flux characterization. No significant work has been performed on thermo-mechanical properties of HTMs. The objective of the thesis is to understand the structure-property correlation of HTM and to characterize (1) thermo mechanical properties under different reducing environments and thermal cycles (thermal shock), and (2) evaluate the stability of the novel HTM material. A novel HTM cermet bulk sample was characterized for its physical and mechanical properties at both room temperature and at elevated temperature up to 1000°C. Microstructural properties and residual stresses were evaluated in order to understand the changing mechanism of the microstructure and its effects on the mechanical properties of materials. A correlation of the microstructural and thermo mechanical properties of the HTM system was established for both HTM and the substrate material. Mechanical properties of both selected structural ceramics and the novel HTM cermet bulk sample are affected mainly by porosity and microstructural features, such as grain size and pore size-distribution. The Young's Modulus (E-value) is positively correlated to the flexural strength for materials with similar crystallographic structure. However, for different crystallographic materials, physical properties are independent of mechanical properties. Microstructural properties, particularly, grain size and crystallographic structure, and thermodynamic properties are the main factors affecting the mechanical properties at both room and high temperatures. The HTM cermet behaves more like an elastic material at room temperature and as a ductile material at temperature above 850°C. The oxidation and the plasticity of Pd phase mainly affected the mechanical properties of HTM cermet at high temperature, also as a result of thermal cycling. Residual stress induced in the HTM by thermo cycles also plays a very critical role in defining the thermo-mechanical properties

LiDAR-Based Place Recognition For Autonomous Driving: A Survey

LiDAR-based place recognition (LPR) plays a pivotal role in autonomous driving, which assists Simultaneous Localization and Mapping (SLAM) systems in reducing accumulated errors and achieving reliable localization. However, existing reviews predominantly concentrate on visual place recognition (VPR) methods. Despite the recent remarkable progress in LPR, to the best of our knowledge, there is no dedicated systematic review in this area. This paper bridges the gap by providing a comprehensive review of place recognition methods employing LiDAR sensors, thus facilitating and encouraging further research. We commence by delving into the problem formulation of place recognition, exploring existing challenges, and describing relations to previous surveys. Subsequently, we conduct an in-depth review of related research, which offers detailed classifications, strengths and weaknesses, and architectures. Finally, we summarize existing datasets, commonly used evaluation metrics, and comprehensive evaluation results from various methods on public datasets. This paper can serve as a valuable tutorial for newcomers entering the field of place recognition and for researchers interested in long-term robot localization. We pledge to maintain an up-to-date project on our website https://github.com/ShiPC-AI/LPR-Survey.Comment: 26 pages,13 figures, 5 table