A framework for estimating difficulty and exclusion from tasks during inclusive design

Measuring capability variations within the population isanimportant process that can be used to support decision making regarding the inclusivity of design for all users, thus allowing the level of exclusion tobe defined veryearly and throughout the design process. Our hands often represent a central feature of the human-task interaction, and therefore, variations in the capabilities of the hands has the potential to exclude people from all or part of the tasks they perform. Data is presented from the performance of 15 people in one of three age groups (18-40, 41-64 and 65+). Using a classification system for defining hand actions the prevalence of different grips in response to a range of physical task demands was mapped in a way that allowed capability to be measured against other variables such as task quality. This was found toenhance thegranularity with which exclusion could be both measured and predicted.

Modelling of settlement induced building damage

This thesis focuses on the modelling of settlement induced damage to masonry buildings. In densely populated areas, the need for new space is nowadays producing a rapid increment of underground excavations. Due to the construction of new metro lines, tunnelling activity in urban areas is growing. One of the consequences is a greater attention to the risk of damage on existing structures. Thus, the assessment of potential damage of surface buildings has become an essential stage in the excavation projects in urban areas (Chapter 1). The current damage risk assessment procedure is based on strong simplifications, which not always lead to conservative results. Object of this thesis is the development of an improved damage classification system, which takes into account the parameters influencing the structural response to settlement, like the non-linear behaviour of masonry and the soil-structure interaction. The methodology used in this research is based on experimental and numerical modelling. The design and execution of an experimental benchmark test representative of the problem allows to identify the principal factors and mechanisms involved. The numerical simulations enable to generalize the results to a broader range of physical scenarios. The methodological choice is based on a critical review of the currently available procedures for the assessment of settlement-induced building damage (Chapter 2). A new experimental test on a 1/10th masonry façade with a rubber base interface is specifically designed to investigate the effect of soil-structure interaction on the tunnelling-induced damage (Chapter 3). The experimental results are used to validate a 2D semi-coupled finite element model for the simulation of the structural response (Chapter 4). The numerical approach, which includes a continuum cracking model for the masonry and a non-linear interface to simulate the soil-structure interaction, is then used to perform a sensitivity study on the effect of openings, material properties, initial damage, initial conditions, normal and shear behaviour of the base interface and applied settlement profile (Chapter 5). The results assess quantitatively the major role played by the normal stiffness of the soil-structure interaction and by the material parameters defining the quasi-brittle masonry behaviour. The limitation of the 2D modelling approach in simulating the progressive 3D displacement field induced by the excavation and the consequent torsional response of the building are overcome by the development of a 3D coupled model of building, foundation, soil and tunnel (Chapter 6). Following the same method applied to the 2D semi-coupled approach, the 3D model is validated through comparison with the monitoring data of a literature case study. The model is then used to carry out a series of parametric analyses on geometrical factors: the aspect ratio of horizontal building dimensions with respect to the tunnel axis direction, the presence of adjacent structures and the position and alignment of the building with respect to the excavation (Chapter 7). The results show the governing effect of the 3D building response, proving the relevance of 3D modelling. Finally, the results from the 2D and 3D parametric analyses are used to set the framework of an overall damage model which correlates the analysed structural features with the risk for the building of being damaged by a certain settlement (Chapter 8). This research therefore provides an increased experimental and numerical understanding of the building response to excavation-induced settlements, and sets the basis for an operational tool for the risk assessment of structural damage (Chapter 9).

Vulnerability assessment of buildings subject to tunnel-induced settlements: the influence of orientation and position of the building

The assessment of settlement induced damage on buildings during the preliminary phase of tunnel excavation projects, is nowadays receiving greater attention. Analyses at different levels of detail are performed on the surface building in proximity to the tunnel, to evaluate the risk of structural damage and the need of mitigation measures. In this paper, the possibility to define a correlation between the main parameters that influence the structural response to settlement and the potential damage is investigated through numerical analysis. The adopted 3D finite element model allows to take into account important features that are neglected in more simplified approaches, like the soil-structure interaction, the nonlinear behaviour of the building, the three dimensional effect of the tunnelling induced settlement trough and the influence of openings in the structure. Aim of this approach is the development of an improved classification system taking into account the intrinsic vulnerability of the structure, which could have a relevant effect on the final damage assessment. Parametric analyses are performed, focusing on the effect of the orientation and the position of the structure with respect to the tunnel. The obtained results in terms of damage are compared with the Building Risk Assessment (BRA) procedure. This method was developed by Geodata Engineering (GDE) on the basis of empirical observations and building monitoring and applied during the construction of different metro lines in urban environment. The comparison shows a substantial agreement between the two procedures on the influence of the analysed parameters. The finite element analyses suggest a refinement of the BRA procedure for pure sagging conditions.

Computational modelling of building damage due to tunnelling

Underground constructions in soft ground may lead to settlement damage to existing buildings. In The Netherlands the situation is particularly complex, because of the combination of soft soil, fragile pile foundations and brittle, unreinforced masonry façades. The tunnelling design process in urban areas requires a reliable risk damage assessment. In the engineering practice the current preliminary damage assessment is based on the limiting tensile strain method (LTSM). Essentially this is an uncoupled analysis, in which the building is modelled as an elastic beam subject to imposed Greenfield settlements and the induced tensile strains are compared with a limit value for the material. The soil-structure interaction is included only as a ratio between the soil and the building stiffness. In this paper, a coupled approach is evaluated. The soil-structure interaction in terms of normal and shear behaviour is represented by interface elements and a cracking model for masonry is included. This project aims to improve the existing damage classification system for masonry buildings subjected to tunnel-induced settlement, in order to evaluate the necessity of strengthening techniques or mitigation measures.

Numerical analyses of tunnel-induced settlement damage to a masonry wall

Settlements due to underground construction represent a risk for the architectural heritage, especially in The Netherlands, because of the combination of soft soil, fragile pile foundation and brittle, un-reinforced masonry façade. Modelling of soil-structure interaction is fundamental to assess the risk of building damage due to tunnelling. This paper presents results of finite element analyses carried out with different models for a simple masonry wall. Focus is paid on the comparison between coupled, uncoupled and semi-coupled analyses, in which the soil-structure interaction is represented in different ways. In particular, the implementation of a soil-structure interface model in the numerical analyses is analysed, in order to asses its validity. The aim of the research project is the development of a damage classification system for different building typologies.

Cross-Lingual spoken language understanding from unaligned data using discriminative classification models and machine translation

This paper investigates several approaches to bootstrapping a new spoken language understanding (SLU) component in a target language given a large dataset of semantically-annotated utterances in some other source language. The aim is to reduce the cost associated with porting a spoken dialogue system from one language to another by minimising the amount of data required in the target language. Since word-level semantic annotations are costly, Semantic Tuple Classifiers (STCs) are used in conjunction with statistical machine translation models both of which are trained from unaligned data to further reduce development time. The paper presents experiments in which a French SLU component in the tourist information domain is bootstrapped from English data. Results show that training STCs on automatically translated data produced the best performance for predicting the utterance's dialogue act type, however individual slot/value pairs are best predicted by training STCs on the source language and using them to decode translated utterances. © 2010 ISCA.

Encoding of mixtures in a simple olfactory system.

Natural odors are usually mixtures; yet, humans and animals can experience them as unitary percepts. Olfaction also enables stimulus categorization and generalization. We studied how these computations are performed with the responses of 168 locust antennal lobe projection neurons (PNs) to varying mixtures of two monomolecular odors, and of 174 PNs and 209 mushroom body Kenyon cells (KCs) to mixtures of up to eight monomolecular odors. Single-PN responses showed strong hypoadditivity and population trajectories clustered by odor concentration and mixture similarity. KC responses were much sparser on average than those of PNs and often signaled the presence of single components in mixtures. Linear classifiers could read out the responses of both populations in single time bins to perform odor identification, categorization, and generalization. Our results suggest that odor representations in the mushroom body may result from competing optimization constraints to facilitate memorization (sparseness) while enabling identification, classification, and generalization.

Encoding of mixtures in a simple olfactory system

Natural odors are usually mixtures; yet, humans and animals can experience them as unitary percepts. Olfaction also enables stimulus categorization and generalization. We studied how these computations are performed with the responses of 168 locust antennal lobe projection neurons (PNs) to varying mixtures of two monomolecular odors, and of 174 PNs and 209 mushroom body Kenyon cells (KCs) to mixtures of up to eight monomolecular odors. Single-PN responses showed strong hypoadditivity and population trajectories clustered by odor concentration and mixture similarity. KC responses were much sparser on average than those of PNs and often signaled the presence of single components in mixtures. Linear classifiers could read out the responses of both populations in single time bins to perform odor identification, categorization, and generalization. Our results suggest that odor representations in the mushroom body may result from competing optimization constraints to facilitate memorization (sparseness) while enabling identification, classification, and generalization