影响水泥土波速的因素

从水泥掺入比、养护龄期、含水量和土质四个方面,结合实测结果和试验结果分别分析了这些因素对水泥土波速的影响,对于改进工程检测有一定意义。     

Data-driven estimation of building interior plans

This work investigates constructing plans of building interiors using learned building measurements. In particular, we address the problem of accurately estimating dimensions of rooms when measurements of the interior space have not been captured. Our approach focuses on learning the geometry, orientation and occurrence of rooms from a corpus of real-world building plan data to form a predictive model. The trained predictive model may then be queried to generate estimates of room dimensions and orientations. These estimates are then integrated with the overall building footprint and iteratively improved using a two-stage optimisation process to form complete interior plans.

The approach is presented as a semi-automatic method for constructing plans which can cope with a limited set of known information and constructs likely representations of building plans through modelling of soft and hard constraints. We evaluate the method in the context of estimating residential house plans and demonstrate that predictions can effectively be used for constructing plans given limited prior knowledge about the types of rooms and their topology.     

地基土-桩基础-核电站辅助厂房结构相互作用体系的地震响应分析

本文研究了地基土-桩-核岛辅助厂房结构相互作用体系在地震激励时的“平-扭”耦联动力响应,在分析中分别采用M.Novak的近似理论,M.Novak常数法,M法,常数法计算了桩基础的阻抗函数,并考虑了在同一基础上的安全壳和另一辅助厂房对所研究的辅助厂房动力响应的影响。     

Numerical investigation of pile installation effects in sand using material point method

The installation of displacement piles in sand leads to severe changes in the stress state, density and soil properties around the pile tip and shaft, and therefore has a significant influence on the pile bearing capacity. Most current numerical methods predicting pile capacity do not take installation effects into account, as large deformations can lead to mesh distortion and non-converging solutions. In this study, the material point method (MPM) is applied to simulate the pile installation process and subsequent static pile loading tests. MPM is an extension of the finite element method (FEM), which is capable of modelling large deformations and soil-structure interactions. This study utilizes the moving mesh algorithm where a redefined computational mesh is applied in the convective phase. This allows a fine mesh to be maintained around the pile tip during the installation process and improves the accuracy of the numerical scheme, especially for contact formulation. For the analyses a hypoplastic constitutive model for sand is used, which takes into account density and stress dependent behaviour. The model performs well in situations with significant stress level changes because it accounts for very high stresses at the pile tip. Numerical results agree with centrifuge experiments at a gravitational level of 40 g. This analysis confirms the importance of pile installation effects in numerical simulations, as well as the proposed numerical approach’s ability to simulate installation and static load tests of jacked displacement piles.     

An experimental,analytical and numerical study on the thermal efficiency of energy piles in unsaturated soils

Energy piles are bi-functional foundation elements used as structural support as well as ground heat exchangers for shallow geothermal energy systems. Because they are relatively short, energy piles may be partially embedded in unsaturated soils. Saturation conditions influence the thermal properties of the ground and therefore the heat exchange rate, which in turn affects the efficiency of energy piles. This paper combines analytical, experimental and numerical investigations to evaluate the heat exchange rate of energy piles partially or fully embedded in unsaturated soils. The proposed analytical solution is based on the cylindrical heat source theory that treats the soil as a semi-infinite, homogeneous, and isotropic medium. The solution from this theory is multiplied by a function developed analytically in this paper and the outcome is the heat exchange rate for energy piles in unsaturated soils. The proposed function depends on soil saturation, soil and pile thermal properties, and pile geometry. The analytical solution was compared against a finite element solution; which was in turn validated against results from laboratory experiments. Very satisfactory agreements between the analytical, numerical and experimental outputs were observed. The proposed method can be used for a quick and simple evaluation of the efficiency of energy piles in unsaturated conditions. The proposed analytical solution can also be a useful tool for the verification of numerical codes developed for the design of energy piles in unsaturated soils.     

Formulation of the axisymmetric CPDI with application to pile driving in sand

In foundation engineering practice, pile driving is often used as an efficient method to install piles. While large distortions take place along the pile shaft during the installation, the zone around the pile toe experiences compression. In an attempt to fully understand the build up of resistance when driving piles, it is desirable to model the driving process and the corresponding soil behaviour. The non-linear dynamic analysis of this problem is challenging, given the large deformation that develops together with the associated changes in soil properties. Some numerical methods offer the possibility of handling large material movements by utilising Lagrangian and Eulerian frames of references. However, few of these methods are capable of tracing the material displacement, such as the Material Point Method (MPM). Early implementation of MPM assumes that the mass is concentrated at the material points, which causes noise in the solution. Later implementations assign a spatial domain to the material points to mitigate the grid crossing error. The Convected Particle Domain Interpolation (CPDI) is one such implementation.This paper extends the two-dimensional CPDI formulation for an axisymmetric problem where a pile is driven into sand that is modelled as a hypoplastic model. The extended formulation is tested, validated and compared to that for the case of the two-dimensional plane-strain within the framework of the method of manufactured solution. The hammer blows on the pile are represented by a periodic forcing function. In contrast to earlier studies on pile installation using advanced models, deep penetration is achieved in the present analysis. A non-regular distribution for the particle domains is suggested to avoid unnecessary computation. A frictional contact algorithm is introduced to describe the pile–soil interaction.     

Optimal spatial allocation of irrigation water under uncertainty using the bilayer nested optimisation algorithm and geospatial technology

The optimal spatial allocation of irrigation water under uncertainty has become a serious concern because of irrigation water shortage and uncertain factors that affect irrigation water allocation. In this study, an optimal multi-objective model for irrigation water allocation under uncertainty is developed to maximise the economic benefit of crops and minimise the operation cost and water deficit of crop irrigation. The original and optimal plantation structure, irrigation mode and soil water content are acquired through geospatial technology. A bilayer nested optimisation (BLNO) algorithm is designed to produce multiple individuals of design vectors using an ant colony neural network algorithm for an outer optimisation. Meanwhile, a continuous adaptive ant colony (CAAC) algorithm is used for inner optimisation to calculate the interval values of the uncertain model. The crop distribution and irrigation mode are obtained to parameterise the planting area and the water demand of each crop and each block in the multi-objective model. This model is then solved and analysed. Compared to the optimal schemes obtained from an inexact two-stage fuzzy-stochastic programming and the CAAC, respectively, BLNO can effectively and efficiently solve the optimal spatial allocation of irrigation water under uncertainty. This method can spatially maximise the economic benefit of crops and minimise the operation cost and water deficit of crop irrigation using lower and upper bound maps whilst visually obtaining the exact crop type, reasonable irrigation method and precise water demand for each block and for the entire irrigated area.     

Measuring segregation as a spatial optimisation problem,revisited: a case study of London, 1991–2011

There has been long and wide-ranging debate in the social science literature about how best to conceptualise and to measure segregation. A popular measure is the dissimilarity index, usually attributed to Duncan and Duncan who were aware of its geographical limitations – that it, like most indices, is invariant to the precise spatial patterning of the segregation measured. Whilst one response to this shortcoming has been to develop a spatial adjustment, a number of papers from the 1980s and 1990s took the approach of treating the measurement as a (spatial) optimisation problem. This paper revisits that optimisation literature, arguing that what was computationally prohibitive in the past is now possible in the open-source software, R, and emblematic of the sorts of problem that might be more routinely solved in a cyberinfrastructure tailored to geographical analysis. Applying this method to UK Census data for London, and comparing the optimisation measure with the standard and adjusted dissimilarity indices, claims of ethnic desegregation are considered.     

液化地基中桩的破坏机理研究进展

地震诱发的地基液化对桩基础的破坏极大,液化地基中桩的破坏机理是岩土地震工程中的一个重要研究课题。目前地基液化时桩土结构系统的地震性态尚没有认识充分,已有的研究内容较多局限于桩身材料的强度破坏方面,难以考虑液化土体侧向流动、基桩屈曲失稳、以及土与结构动力相互作用等复杂因素的影响。本文重点加强以下3个方面的深入探讨和研究:(1)液化地基中桩的屈曲失稳;(2)液化地基中桩基破坏的数值模拟新方法;(3)液化地基中桩-土-结构的动力相互作用分析。     

Modelling uncertainties in short-term reservoir operation using fuzzy sets and a genetic algorithm / Modélisation d’incertitudes dans la gestion de barrage à court terme grâce à des ensembles flous et à un algorithme génétique

Abstract

Abstract Various uncertainties are inherent in modelling any reservoir operation problem. Two of these are addressed in this study: uncertainty involved in the expression of reservoir penalty functions, and uncertainty in determining the target release value. Fuzzy set theory was used to model these uncertainties where the preferences of the decision maker for the fuzzified parameters are expressed as membership functions. Nonlinear penalty functions are used to determine the penalties due to deviations from targets. The optimization was performed using a genetic algorithm with the objectives to minimize the total penalty and to maximize the level of satisfaction of the decision maker with fuzzified input parameters. The proposed formulation was applied to the problem of finding the optimal release and storage values, taking Green reservoir in Kentucky, USA as a case study. The approach offers more flexibility to reservoir decision-making by demonstrating an efficient way to represent subjective uncertainties, and to deal with non-commensurate objectives under a fuzzy multi-objective environment.