Experimental comparison of dynamic tracking performance of iGPS and laser tracker

External metrology systems are increasingly being integrated with traditional industrial articulated robots, especially in the aerospace industries, to improve their absolute accuracy for precision operations such as drilling, machining and jigless assembly. While currently most of the metrology assisted robotics control systems are limited in their position update rate, such that the robot has to be stopped in order to receive a metrology coordinate update, some recent efforts are addressed toward controlling robots using real-time metrology data. The indoor GPS is one of the metrology systems that may be used to provide real-time 6DOF data to a robot controller. Even if there is a noteworthy literature dealing with the evaluation of iGPS performance, there is, however, a lack of literature on how well the iGPS performs under dynamic conditions. This paper presents an experimental evaluation of the dynamic measurement performance of the iGPS, tracking the trajectories of an industrial robot. The same experiment is also repeated using a laser tracker. Besides the experiment results presented, this paper also proposes a novel method for dynamic repeatability comparisons of tracking instruments.     

A neural network-based build time estimator for layer manufactured objects

A correct prediction of build time is essential to calculate the accurate cost of a layer manufactured object. The methods presented in literature are of two types: detailed?Canalysis- and parametric-based approaches. The former require that a lot of data, related to the kinematic and dynamic performance of the machine, should be known. Parametric models, on the other hand, are of general use and relatively simple to implement; however, the parametric methods presented in literature only provide a few of the components of the total build time. Therefore, their performances are not properly suited in any case. In order to overcome these limitations, this paper proposes a parametric approach which uses a more complete set of build-time driving factors. Furthermore, considering the complexity of the parametric build time function, an artificial neural network is used so as to improve the method flexibility. The analysis of the test cases shows that the proposed approach provides a quite accurate estimation of build time even in critical cases and when supports are required.     

Influence of uncertainty in selected aerodynamic and structural parameters on the buffeting response of long-span bridges

Multimode-analysis methods for the study and derivation of flutter instability and buffeting response are readily available from the literature and have been successfully applied to the assessment of the susceptibility of long-span bridges to wind loading. In both cases flutter critical velocity and buffeting oscillation are usually estimated from deterministic analyses. However, the probabilistic nature of the problem is latent since uncertainties, especially those associated with the definition of wind and aerodynamic characteristics, are intrinsically present. These quantities include, for example, wind-turbulence power spectral density, static coefficients and aerodynamic derivatives, usually derived from either site observations or experimental analysis. Their effects are often neglected or usually addressed through sensitivity analyses only.While in the past uncertainty in flutter estimates has been analyzed by researchers (for example through reliability analysis), little attention has been devoted to buffeting. In this paper the effects associated with the random nature of wind and structural characteristics are analyzed through the derivation of a closed-form solution associated with the single-mode buffeting problem with selected random parameters. A specific example is provided to clarify the role of wind power spectral density, damping and selected aeroelastic derivatives.     

呼吸房子——现代沙特房屋

项目地点:沙特阿拉伯利雅得项目类型:建筑(住宅)开工日期:未知该项目获2005年豪瑞可持续建筑大奖赛非洲中东地区提名奖     

Data generative machine learning model for the assessment of outdoor thermal and wind comfort in a northern urban environment

Predicting comfort levels in cities is challenging due to the many metric assessment. To overcome these challenges, much research is being done in the computing community to develop methods capable of generating outdoor comfort data. Machine Learning (ML) provides many opportunities to discover patterns in large datasets such as urban data. This paper proposes a data-driven approach to build a predictive and data-generative model to assess outdoor thermal comfort. The model benefits from the results of a study, which analyses Computational Fluid Dynamics (CFD) urban simulation to determine the thermal and wind comfort in Tallinn, Estonia. The ML model was built based on classification, and it uses an opaque ML model. The results were evaluated by applying different metrics and show us that the approach allows the implementation of a data-generative ML model to generate reliable data on outdoor comfort that can be used by urban stakeholders, planners, and researchers.     

Indoor air quality in schools of a highly polluted south Mediterranean area

This study aimed at surveying lower secondary schools in southern Italy, in a highly polluted area. A community close to an industrial area and three villages in rural areas was investigated. Indoor temperature, relative humidity (RH), gaseous pollutants (CO₂ and NO₂), selected biological pollutants in indoor dust, and the indoor/outdoor mass concentration and elemental composition of PM_2.5 were ascertained. Temperature and RH were within, or close to, the comfort range, while CO₂ frequently exceeded the threshold of 1000 ppm, indicating inadequate air exchange rate. In all the classrooms, median NO₂ levels were above the WHO threshold value. Dermatophagoides p. allergen concentration was below the sensitizing threshold, while high endotoxin levels were detected in the classrooms, suggesting schools may produce significant risks of endotoxin exposure. Concentration and solubility of PM_2.5 elements were used to identify the sources of indoor particles. Indoor concentration of most elements was higher than outdoors. Resuspension was responsible for the indoor increase in soil components. For elements from industrial emission (Cd, Co, Ni, Pb, Sb, Tl, V), the indoor concentration depended on penetration from the outside. For these elements, differences in rural vs industrial concentrations were found, suggesting industrial sources may influence indoor air quality nearby schools.     

How to Overcome the Dichotomous Nature of Smart City Research: Proposed Methodology and Results of a Pilot Study

ABSTRACT

Overcoming the dichotomous nature of smart city research is fundamental to providing cities with a clear understanding of how smart city development should be approached. This paper introduces a research methodology for conducting the multiple-case study analyses necessary to meet this challenge. After presenting the methodology, we test the practical feasibility, effectiveness, and logistics of such a methodology by examining the activities that Vienna has implemented in building its smart city development strategy. The results of this pilot study show how the application of the proposed methodology can help smart city researchers codify the knowledge produced from multiple smart city experiences, using a common protocol. This in turn allows them to: (1) coordinate efforts when investigating the strategic principles that drive smart city development and test the divergent hypotheses emerging from the scientific literature; (2) share the results of this investigation and hypothesis testing by conducting extensive cross-case analyses among multiple studies able to capture the generic qualities of the findings; (3) gain consensus on the way to think about, conceptualize, and standardize the analysis of smart city developments; and (4) develop innovative monitoring and evaluation systems for smart city development strategies by reflecting upon the lessons learned from current practices.     

Correlation of Burning Rate with Spread Rate for Downward Flame Spread Over PMMA

Burning rate of solid fuel and laminar flame spread rate are both well studied topics for flame spread in downward configuration. Yet, despite well-developed theories, not much experimental data is available to correlate the two. In this work, experiments are performed under ambient conditions in downward spread configuration for a wide range of thicknesses (2 mm to 24 mm) for flat samples of Poly-Methyl Methacrylate (PMMA). The samples are held by two ceramic plates in order to obtain a two-dimensional propagation that is independent on the sample width. By analyzing videos of the experiments, the instantaneous spread rate is obtained using a recently developed MATLAB based tool. The shape of the pyrolyzing fuel is carefully measured after extinguishing the flame during a steady propagation. The spread rate and the burn angle, which is defined as the angle subtended by the pyrolyzing surface with respect of the fuel surface, are correlated, producing an expression for the burning rate in terms of the burn angle and flame spread rate. As the fuel thickness is increased, the burn angle and burning rate decrease and reach asymptotic limits for thermally thick fuels, in analogy with the spread rate limit. The comparison with data from literature suggests that in the thick limit the value of mass flux for PMMA (about 10 g/m² s) tends to the one of non-spreading flames. The presented geometrical approach to study the downward spread problem avoids the use of the B number and local gradients in order to calculate the mass burning rate of the fuel.     

Peri-urban agriculture in Barcelona: outlining landscape dynamics vis à vis socio-environmental functions

Dispersed urbanisation promotes complex relationships between rural areas and the urban fringe, with emerging new functions for peri-urban agriculture (PUA). Although PUA is a type of productive farming of interest for urban planning due to its recognised functions, comparative analyses are needed to relate farm dynamics to fringe landscape modifications in different socio-economic contexts. Given the current limitation of specific methodologies to analyse PUA dynamics, a quantitative approach profiling farm types and the related landscape structure in an expanding urban region, the Metropolitan Area of Barcelona, is proposed. Results indicate that PUA is based on five typologies with different territorial values, as a consequence of diverse economic relevance, socio-environmental weight and landscape prominence. Based on these results, a conservation strategy aimed at preserving the residual PUA landscape is proposed through the promotion of a polycentric functional network of farming with natural vegetation.