The five-parameter grain boundary character and energy distributions of a fully austenitic high-manganese steel using three dimensional data

The three-dimensional interfacial grain boundary network in a fully austenitic high-manganese steel was studied as a function of all five macroscopic crystallographic parameters (i.e. lattice misorientation and grain boundary plane normal) using electron backscattering diffraction mapping in conjunction with focused ion beam serial sectioning. The relative grain boundary area and energy distributions were strongly influenced by both the grain boundary plane orientation and the lattice misorientation. Grain boundaries terminated by (1 1 1) plane orientations revealed relatively higher populations and lower energies compared with other boundaries. The most frequently observed grain boundaries were {1 1 1} symmetric twist boundaries with the Σ3 misorientation, which also had the lowest energy. On average, the relative areas of different grain boundary types were inversely correlated to their energies. A comparison between the current result and previously reported observations (e.g. high-purity Ni) revealed that polycrystals with the same atomic structure (e.g. face-centered cubic) have very similar grain boundary character and energy distributions. © 2014 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

岷江上游景观边界网络格局研究及生态效应分析

景观边界是特定时空尺度下相对均质的景观之间所存在的异质性过渡带，作为景观的一个四维组分，边界动态直接反映景观变化，与基于斑块的研究相比，明确景观边界的生态意义是理解景观过程的一个新的切入点。边界效应是景观边界最显著特征之一，也是当前生态学领域的研究热点，但大部分研究集中在生态系统及其以下尺度，对大尺度上的研究涉及内容尚少。 本文以岷江上游地区为例，利用TM影像数据、林相图、土地利用图和野外实测数据，应用RS、GIS、SPSS、Fragstats等软件的数据处理、分析、运算功能，研究了景观边界网络格局的变化，并分析了与之相关的生态过程；研究了类型水平上森林景观的边界效应以及景观尺度上林农复合景观的边界网络效应。旨在揭示岷江上游景观格局的变化趋势及其驱动因子，以及林农复合景观格局的生态效应，从而为研究区土地利用提供科学参考。研究结果如下： （一）在岷江上游地区的13种景观边界类型中，建筑用地边界和农田边界是人工边界，同时也都是清晰边界；但林地、灌木林地、草地等自然景观之间的边界并不都是模糊边界。冰雪边界是典型的随季节变化的变动型边界，其它边界在年内的变化则相对稳定。 （二）在1974-2000年期间，由于人为干扰强度的加剧，岷江上游景观边界网络结构变得更加复杂，在早期以边界长度增加为主，网络连接度变大，在后期以边界数量和结点数量增加为主，网络连接度变小；森林景观与低坡位景观类型间的边界减少，森林下线上移；农田与林地的边界在早期增加，1986年后减少，而与灌木林地的边界持续增加；基于边界特征的格局分析表明，森林景观结构变得简单化，而农田、灌木林地、草地等景观类型的结构变得更加复杂。 在景观水平上，基于边界和结点特征的格局指数与对应的基于斑块特征的格局指数具有基本一致的变化趋势，但基于边界和结点特征的指数对格局的变化更灵敏，在类型水平上，基于结点的格局指数比基于边界的格局指数具有更大的灵敏性，而且前者能够反映出后者反映不出的格局信息。 （三）研究区的农田边界共有5种类型，分别是农田与林地、灌木林地、草地、水体、建筑用地之间的边界，总长6583.4km；其中林农边界长2473.7km，占37.6%，是除灌农边界（占农田边界总长度的44.9%）之外比例最大的农田边界类型，广泛分布在岷江干流及其支流的河谷中，海拔多在1000-3500m之间。 （1）多元线性回归分析结果表明，农田生物量的边界效应深度与海拔和坡度显著相关，与其它因子相关性不大；林地生物量的边界效应深度与海拔和坡向相关性较大，与其它因子相关性不大；林农边界对农田生物量产生正面效应，对林地生物量产生负面效应，且对农田的影响面积大于对林地的影响面积；根据回归方程计算边界效应的影响面积，2000年有14532hm2林地生物量受到林农边界网络的影响，占研究区林地面积的1.2%，有16659 hm2农田生物量受到林农边界网络的影响，占研究区农田面积的22.6%，由于边界位置、长度的变化，不同年间林农边界网络的生态效应也存在差异。 除了生物量，本文还研究了林农边界网络对林地和农田土壤水分和生物多样性的影响： （2）林农边界减少林地和农田边缘的土壤水分，岷江上游有2103 hm2农田和371 hm2林地其土壤水分受到林农边界效应的影响，分别占研究区农田面积的2.3%和林地面积的0.03%。生物多样性受林农边界网络影响的农田面积为4855 hm2，占研究区农田面积的5.37%；生物多样性受林农边界网络影响的林地面积为3401 hm2，占研究区林地面积的0.29%。 上述研究从景观边界网络的角度揭示了岷江上游近三十年的景观变化特征，在印证斑块类型所反映的景观变化特征的同时，还反映出传统格局研究方法反映不出的格局信息，为景观生态学中格局与过程研究提供了新思路，也丰富了边界效应的理论和案例研究，有关结论还可为高山峡谷区土地利用格局优化和实施退耕还林还草工程提供参考依据。

Cleavage initiation in the intercritically reheated coarse-grained heat-affected zone:Part I. Fractographic evidence

Tensile, crack opening displacement (COD), blunt notch, and Charpy impact tests were used to investigate cleavage initiation in the intercritically reheated coarse-grained heat-affected zone (IC CG HAZ) of three steels. The steels were chosen to provide different distributions and morphologies of MA (high-carbon martensite with some retained austenite) particles within the IC CG HAZ structure. Observation of minimum impact toughness values for the IC CG HAZ was found to be associated with a particular microstructure containing a near-connected grain boundary network of blocky MA particles, the MA particles being significantly harder than the internal grain microstructure. The initiation mechanism for this structure was determined to be from a combination of an overlap of residual transformational induced stress fields, due to the formation of the MA particles, between two closely spaced particles and stress concentration effects resulting from debonding of the particles. © 1994 The Minerals, Metals and Materials Society, and ASM International.

Effect of cooling rate on intercritically reheated microstructure and toughness in high strength low alloy steel

High strength low alloy steels have been shown to be adversely affected by the existence of regions of poor impact toughness within the heat affected zone (HAZ) produced during multipass welding. One of these regions is the intercritically reheated coarse grained HAZ or intercritical zone. Since this region is generally narrow and discontinuous, of the order of 0.5 mm in width, weld simulators are often employed to produce a larger volume of uniform microstructure suitable for toughness assessment. The steel usedfor this study was a commercial quenched and tempered steel of 450 MN m -2 yield strength. Specimen blanks were subjected to a simulated welding cycle to produce a coarse grained structure of upper bainite during the first thermal cycle, followed by a second thermal cycle where the peak temperature T p2 was controlled. Charpy tests carried out for T p2 values in the range 650-850°C showed low toughness for T p2 values between 760 and 790°C, in the intercritical regime. Microstructural investigation of the development of grain boundary martensite-retained austenite (MA) phase has been coupled with image analysis to measure the volume fraction of MAformed. Most of the MA constituent appears at the prior austenite grain boundaries during intercritical heating, resulting in a 'necklace' appearance. For values of T p2 greater than 790°C the necklace appearance is lost and the second phase areas are observed throughout the structure. Concurrent with this is the development of the fine grained, predominantly ferritic structure that is associated with the improvement in toughness. At this stage the microstructure is transforming from the intercritical regime structure to the supercritically reheated coarse grained HAZ structure. The toughness improvement occurs even though the MA phase is still present, suggesting that the embrittlement is associated with the presence of a connected grain boundary network of the MA phase. The nature of the second phase particles can be controlled by the cooling rate during the second cycle and variesfrom MA phase at high cooling rates to a pearlitic structure at low cooling rates. The lowest toughness of the intercritical zone is observed only when MA phase is present. The reason suggested for this is that only the MA particles debond readily, a number of debonded particles in close proximity providing sufficient stress concentration to initiate local cleavage. © 1993 The Institute of Materials.

A new RBF neural network with boundary value constraints

We present a novel topology of the radial basis function (RBF) neural network, referred to as the boundary value constraints (BVC)-RBF, which is able to automatically satisfy a set of BVC. Unlike most existing neural networks whereby the model is identified via learning from observational data only, the proposed BVC-RBF offers a generic framework by taking into account both the deterministic prior knowledge and the stochastic data in an intelligent manner. Like a conventional RBF, the proposed BVC-RBF has a linear-in-the-parameter structure, such that it is advantageous that many of the existing algorithms for linear-in-the-parameters models are directly applicable. The BVC satisfaction properties of the proposed BVC-RBF are discussed. Finally, numerical examples based on the combined D-optimality-based orthogonal least squares algorithm are utilized to illustrate the performance of the proposed BVC-RBF for completeness.

An overview on the urban boundary-layer atmosphere network in Helsinki

The Helsinki Urban Boundary-Layer Atmosphere Network (UrBAN: http://urban.fmi.fi) is a dedicated research-grade observational network where the physical processes in the atmosphere above the city are studied. Helsinki UrBAN is the most poleward intensive urban research observation network in the world and thus will allow studying some unique features such as strong seasonality. The network's key purpose is for the understanding of the physical processes in the urban boundary layer and associated fluxes of heat, momentum, moisture, and other gases. A further purpose is to secure a research-grade database, which can be used internationally to validate and develop numerical models of air quality and weather prediction. Scintillometers, a scanning Doppler lidar, ceilometers, a sodar, eddy-covariance stations, and radiometers are used. This equipment is supplemented by auxiliary measurements, which were primarily set up for general weather and/or air-quality mandatory purposes, such as vertical soundings and the operational Doppler radar network. Examples are presented as a testimony to the potential of the network for urban studies, such as (i) evidence of a stable boundary layer possibly coupled to an urban surface, (ii) the comparison of scintillometer data with sonic anemometry above an urban surface, (iii) the application of scanning lidar over a city, and (iv) combination of sodar and lidar to give a fuller range of sampling heights for boundary layer profiling.

A complex network-based approach for boundary shape analysis

This paper introduces a novel methodology to shape boundary characterization, where a shape is modeled into a small-world complex network. It uses degree and joint degree measurements in a dynamic evolution network to compose a set of shape descriptors. The proposed shape characterization method has all efficient power of shape characterization, it is robust, noise tolerant, scale invariant and rotation invariant. A leaf plant classification experiment is presented on three image databases in order to evaluate the method and compare it with other descriptors in the literature (Fourier descriptors, Curvature, Zernike moments and multiscale fractal dimension). (C) 2008 Elsevier Ltd. All rights reserved.

Decision boundary for discrete Bayesian network classifiers

Bayesian network classifiers are a powerful machine learning tool. In order to evaluate the expressive power of these models, we compute families of polynomials that sign-represent decision functions induced by Bayesian network classifiers. We prove that those families are linear combinations of products of Lagrange basis polynomials. In absence of V-structures in the predictor sub-graph, we are also able to prove that this family of polynomials does in- deed characterize the specific classifier considered. We then use this representation to bound the number of decision functions representable by Bayesian network classifiers with a given structure and we compare these bounds to the ones obtained using Vapnik-Chervonenkis dimension.

Decision boundary for discrete Bayesian network classifiers

Bayesian network classifiers are a powerful machine learning tool. In order to evaluate the expressive power of these models, we compute families of polynomials that sign-represent decision functions induced by Bayesian network classifiers. We prove that those families are linear combinations of products of Lagrange basis polynomials. In absence of V-structures in the predictor sub-graph, we are also able to prove that this family of polynomials does in- deed characterize the specific classifier considered. We then use this representation to bound the number of decision functions representable by Bayesian network classifiers with a given structure and we compare these bounds to the ones obtained using Vapnik-Chervonenkis dimension.

Decision boundary for discrete Bayesian network classifiers

Bayesian network classifiers are a powerful machine learning tool. In order to evaluate the expressive power of these models, we compute families of polynomials that sign-represent decision functions induced by Bayesian network classifiers. We prove that those families are linear combinations of products of Lagrange basis polynomials. In absence of V -structures in the predictor sub-graph, we are also able to prove that this family of polynomials does indeed characterize the specific classifier considered. We then use this representation to bound the number of decision functions representable by Bayesian network classifiers with a given structure.

Stability boundary analysis of the dynamic voltage restorer in weak systems with dynamic loads

In this contribution, a stability analysis for a dynamic voltage restorer (DVR) connected to a weak ac system containing a dynamic load is presented using continuation techniques and bifurcation theory. The system dynamics are explored through the continuation of periodic solutions of the associated dynamic equations. The switching process in the DVR converter is taken into account to trace the stability regions through a suitable mathematical representation of the DVR converter. The stability regions in the Thevenin equivalent plane are computed. In addition, the stability regions in the control gains space, as well as the contour lines for different Floquet multipliers, are computed. Besides, the DVR converter model employed in this contribution avoids the necessity of developing very complicated iterative map approaches as in the conventional bifurcation analysis of converters. The continuation method and the DVR model can take into account dynamics and nonlinear loads and any network topology since the analysis is carried out directly from the state space equations. The bifurcation approach is shown to be both computationally efficient and robust, since it eliminates the need for numerically critical and long-lasting transient simulations.

Breaching the standardised assessment boundary : assessment for learning as a field of exchange

The introduction of the Australian curriculum, the use of standardised testing (e.g. NAPLAN) and the My School website are couched in a context of accountability. This circumstance has stimulated and in some cases renewed a range of boundaries in Australian Education. The consequences that arise from standardised testing have accentuated the boundaries produced by social reproduction in education which has led to an increase in the numbers of students disengaging from mainstream education and applying for enrolment at the Edmund Rice Education Australia Flexible Learning Centre Network (EREAFLCN). Boundaries are created for many young people who are denied access to credentials and certification as a result of being excluded from or in some way disengaging from standardised education and testing. Young people who participate at the EREAFLCN arrive with a variety of forms of cultural capital that are not valued in current education and employment fields. This is not to say that these young people’s different forms of cultural capital have no value, but rather that such funds of knowledge, repertoires and cultural capital are not valued by the majority of powerful agents in educational and employment fields. How then can the qualitative value of traditionally unorthodox - yet often intricate, ingenious, and astute - versions of cultural capital evident in the habitus of many young people be made to count, be recognised, be valuated? Can a process of educational assessment be a field of capital exchange and a space which breaches boundaries through a valuating process? This paper reports on the development of an innovative approach to assessment in an alternative education institution designed for the re-engagement of ‘at risk’ youth who have left formal schooling. A case study approach has been used to document the engagement of six young people, with an educational approach described as assessment for learning as a field of exchange across two sites in the EREAFLCN. In order to capture the broad range of students’ cultural and social capital, an electronic portfolio system (EPS) is under trial. The model draws on categories from sociological models of capital and reconceptualises the eportfolio as a sociocultural zone of learning and development. Results from the trial show a general tendency towards engagement with the EPS and potential for the attainment of socially valued cultural capital in the form of school credentials. In this way restrictive boundaries can be breached and a more equitable outcome achieved for many young Australians.

Compaction control of topography and fault network structure along strike-slip faults in sedimentary basins

Strike-slip faults commonly display structurally complex areas of positive or negative topography. Understanding the development of such areas has important implications for earthquake studies and hydrocarbon exploration. Previous workers identified the key factors controlling the occurrence of both topographic modes and the related structural styles. Kinematic and stress boundary conditions are of first-order relevance. Surface mass transport and material properties affect fault network structure. Experiments demonstrate that dilatancy can generate positive topography even under simple-shear boundary conditions. Here, we use physical models with sand to show that the degree of compaction of the deformed rocks alone can determine the type of topography and related surface fault network structure in simple-shear settings. In our experiments, volume changes of ∼5% are sufficient to generate localized uplift or subsidence. We discuss scalability of model volume changes and fault network structure and show that our model fault zones satisfy geometrical similarity with natural flower structures. Our results imply that compaction may be an important factor in the development of topography and fault network structure along strike-slip faults in sedimentary basins.