Assimilation of GOSAT Methane in the Hemispheric CMAQ; Part II: Results Using Optimal Error Statistics

We applied the parametric variance Kalman filter (PvKF) data assimilation designed in Part I of this two-part paper to GOSAT methane observations with the hemispheric version of CMAQ to obtain the methane field (i.e., optimized analysis) with its error variance. Although the Kalman filter computes error covariances, the optimality depends on how these covariances reflect the true error statistics. To achieve more accurate representation, we optimize the global variance parameters, including correlation length scales and observation errors, based on a cross-validation cost function. The model and the initial error are then estimated according to the normalized variance matching diagnostic, also to maintain a stable analysis error variance over time. The assimilation results in April 2010 are validated against independent surface and aircraft observations. The statistics of the comparison of the model and analysis show a meaningful improvement against all four types of available observations. Having the advantage of continuous assimilation, we showed that the analysis also aims at pursuing the temporal variation of independent measurements, as opposed to the model. Finally, the performance of the PvKF assimilation in capturing the spatial structure of bias and uncertainty reduction across the Northern Hemisphere is examined, indicating the capability of analysis in addressing those biases originated, whether from inaccurate emissions or modelling error.

High-Temperature Behavior of Metals

The design of new alloys as well as the optimization of processes involving whichever form of high-temperature deformation cannot disregard the characterization and/or modelling of the high-temperature structural response of the material [...]

Multiple Approaches to Problem Posing: Theoretical Considerations Regarding its Definition, Conceptualisation, and Implementation

The importance of mathematical problem posing has been acknowledged by many researchers. In this theoretical paper, we want to capture different meanings and aspects of problem posing by approaching it from three different levels: (1) by comparing definitions, (2) by relating it to other constructs, and (3) by referring to research and teaching settings. The first level is an attempt to organise existing definitions of problem posing. The result of this analysis are five categories, which shows that there is no consensus regarding the conceptualisations of problem posing. In the second level, we examine how problem posing is conceived by the research community compared to other mathematical constructs, such as problem solving, mathematical creativity, or modelling. Finally, in the third level, we summarise possible ways of implementing problem posing in research and teaching settings as they are depicted in the relevant literature. Given this broad variance regarding the conceptualisations of problem posing, we attempt to provide some arguments as to whether there is a need for consensus on a commonly accepted concept of problem posing.

Estimation of surface roughness and cutting speed in CNC WEDM by artificial neural network that employed trainable activation function

Activation functions are the most significant properties of artificial neural networks (ANN) because these functions are directly related with the ability of ANN in learning or modelling a system or a function. Furthermore, another reason for the significance of the fact that determination of optimal activation function in ANN is its relationship with success level. In this experimental study, the effects of different types of wire electrodes, cooling techniques and workpiece materials on surface roughness (Ra) and cutting speed (Vc) in wire electrical discharge machining (WEDM) were investigated by using trainable activation functions (AFt) and modelling them in ANNs. So far, a number of methods have been performed according to the data set in order to optimally predict Ra and Vc results. Among these methods, randomized ANN with AFt was found to be the best one for robust prediction according to RMSE values. While the value was 0.280 for Vc, it was 0.2104 for Ra. Optimum activation functions in Ra and Vc were found at first and third degree trainable functions, respectively.

Automated framework for optimized path-planning for pile foundation drilling machines based on 4D BIM modelling

<p>While the Building Information Modeling (BIM) method allows accurate information modelling and thus more robust predictions, it often needs to be combined with tasks beyond the model or modelling phase, especially if the goal is a model-based construction phase. This study proposes an optimization workflow for the construction of pile foundations, since they are part of a varying range of building and infrastructure projects. Pile foundation drilling is an extensive construction process, which can be optimized significantly by reducing the execution length through an effective drilling path plan and automated data transfer. This was achieved through the combination of optimization algorithms, which were linked to the 3D BIM model and selected the shortest distance between piles using Ant Colony Optimization (ACO) algorithm, based on the Travelling Salesperson Problem (TSP). Subsequently the script created separate security distance-compliant tours for drilling machines, calculated construction times and converted the resulting paths into schedules, which in turn could be updated to the 3D BIM model to generate a 4D animation of the construction process. The developed optimization framework and script were tested with a construction company focused on special foundations based in Germany.</p>

Mechanical properties of the most common European woods: a literature review

Wood is an orthotropic material used since ancient time. A literature research about the mechanical properties of density, fracture toughness, modulus of elasticity, and Poisson’s ratio has been done to have a broader view on the subject. The publications relating to the topic were found through the two search engines Scopus and Google Scholar that have yielded several papers, including articles and book sections. In general, there is no standardization on the method of analysis carried out on wood, underlining the great difficulty in studying this complex material. The parameter of density has a great variability and needs a deeper investigation; fracture toughness is not always available in literature, not even in the different directions of the wood sample. Interesting is the modulus of elasticity, which provides a correlation with density, especially in longitudinal section but, again, it needs to be studied in detail. The parameter of Poisson’s ratio is provided as single values in three different directions, but mainly for softwood. All the parameters require a more in-depth study for both softwood and hardwood. Furthermore, the type of analysis, whether experimental or modelling, needs to be standardized to have more comparable results.

A quantitative assessment of rockfall influence on forest structure in the Swiss Alps

Forests below rocky cliffs often play a very important role in protecting settlements against rockfall. The structure and development of these forests are expected to be substantially affected by the disturbance of the falling rocks. Knowing about this effect is important to predict the development of protection forests and consider potential effects of the falling blocks in management strategies. The goal of this study is to quantify differences in forest structure depending on rockfall activity in four different sites in the Swiss Alps. For this, we collected data on forest structure in zones of different rockfall activity and derived rockfall impact probabilities based on rockfall simulations. We assessed whether differences in forest structure and signs of rockfall disturbance could be observed between the rockfall zones. We additionally built mixed-effects models to identify the key variables explaining the forest characteristics described by diameter (DBH) and basal area (bA). The forest structure differs between the rockfall zones, however, with varying effects amongst the sites. DBH tends to decrease with increasing rockfall activity, whereas tree density appears to be little impacted by rockfall. For most sites, the number of deposited blocks and the simulated tree impact probability have a significant effect in the models along with the species, whereas for one site, hardly any effect of rockfall was found. Our results, obtained either from direct measurements or modelling, show that rockfall can locally influence the structure of forests, whereas the influence depends on the frequency and intensity of the rockfall disturbance. Impact probabilities obtained by simulations can serve as a good proxy for rockfall disturbances.