Search

The Arctic is warming at a faster rate compared to the globe on average, commonly referred to as Arctic amplification. Sea ice has been linked to Arctic amplification and gathered attention recently due to the decline in summer sea ice extent. Data assimilation (DA) is the act of combining observations with prior forecasts to obtain a more accurate model state. Sea ice poses a unique challenge for DA because sea ice variables have bounded distributions, leading to non-Gaussian distributions. The non-Gaussian nature violates Gaussian assumptions built into DA algorithms. This study configures different observing system simulated experiments (OSSEs) to find the optimal sea ice and snow observation subset for assimilation to produce the most accurate analyses and forecasts. Findings indicate that not assimilating sea ice concentration observations while assimilating snow depth observation produced the best sea ice and snow forecasts. A simplified DA experiment helped demonstrate that the DA solution is biased when assimilating sea ice concentration observations. The biased DA solution is related to the observation error distribution being a truncated normal distribution and the assumed observation likelihood is normal for the DA method. Additional OSSEs show that using a non-parametric DA method does not alleviate the non-Gaussian effects of the sea ice concentration observations, and assimilating sea ice surface temperatures have a positive impact on snow updates. Lastly, it is shown that perturbed sea ice model parameters, used to create additional ensemble spread in the free forecasts, lead to a year-long negative snow volume bias.

Effective exploration techniques during mechanized tunneling are of high importance in order to prevent severe surface settlements as well as a damage of the tunnel boring machine, which in turn would lead to additional costs and a standstill in the construction process. A seismic methodology called full waveform inversion can bring a considerable improvement compared to state-of-the-art seismic methods in terms of precision. Another method of exploration during mechanized tunneling is to continuously monitor subsurface behavior and then use this data to identify disturbances through pattern recognition and machine learning techniques. Various probabilistic methods for conducting system identification and proposing an appropriate monitoring plan are developed in this regard. Furthermore, ground conditions can be determined by studying boring machine data collected during the excavation. The active and passive obtained data during performance of a shield driven machine were used to estimate soil parameters. The monitoring campaign can be extended to include above-ground structural surveillance as well as terrestrial and satellite data to track displacements of existing infrastructure caused by tunneling. The available radar data for the Wehrhahn-line project are displayed and were utilized to precisely monitor the process of anticipated uplift by injections and any subsequent ground building settlements.

Waveform inversion is an approach used to find an optimal model for the velocity field of a ground structure such that the dynamic response is close enough to the given seismic data. First, a suitable numerical approach is employed to establish a realistic forward computer model. The forward problem is solved in the frequency domain using higher-order finite elements. The velocity field is inverted over a specific number of discrete frequencies; thereby, reducing the computational cost of the forward calculation and the nonlinearity of the inverse problem. The results are presented for different frequency sets and with different source and receiver locations for a two-dimensional model. The influence of attenuation effects is also investigated. The results of two blind tests are presented where only the seismic records of an unknown synthetic model with an inhomogeneous material parameter distribution are provided to mimic a more realistic case. Finally, the result of the inversion in a three-dimensional space is illustrated.

The excavation process in mechanized tunneling can be improved by reconnaissance of the geology ahead. A nondestructive exploration can be achieved in means of seismic imaging. A full waveform inversion approach, which works in the frequency domain, is investigated for the application in tunneling. The approach tries to minimize the difference of seismic records from field observations and from a discretized ground model by changing the ground properties. The final ground model might be a representation of the geology. The used elastic wave modeling approach is described as well as the application of convolutional perfectly matched layers. The proposed inversion scheme uses the discrete adjoint gradient method, a multi-scale approach as well as the L-BFGS method. Numerical parameters are identified as well as a validation of the forward wave modeling approach is performed in advance to the inversion of every example. Two-dimensional blind tests with two different ground scenarios and with two different source and receiver station configurations are performed and analyzed, where only the seismic records, the source functions and the ambient ground properties are provided. Finally, an inversion for a three-dimensional tunnel model is performed and analyzed for three different source and receiver station configurations.

Computationally efficient approaches to topology optimization usually include heuristic update and/or filtering schemes to overcome numerical problems such as the well-known checkerboarding phenomenon, local minima, and the associated mesh dependency. In a series of papers, Hamilton’s principle, which originates from thermodynamic material modeling, was applied to derive a model for topology optimization based on a novel conceptual structure: utilization of this thermodynamic approach resulted in an evolution equation for the local mass distribution as the update scheme during the iterative optimization process. Although this resulted in topologies comparable to those from classical optimization schemes, no direct linkage between these different approaches has yet been drawn. In this contribution, we present a detailed comparison of the new approach to the well-established SIMP approach. To this end, minor modifications of the original thermodynamic approach yield an optimization process with a numerical efficiency that is comparable to that of SIMP approaches. However, a great advantage of the new approach arises from results that are parameter- and mesh-independent, although neither filtering techniques nor gradient constraints are applied. Several 2D and 3D examples are discussed and serve as a profound basis for an extensive comparison, which also helps to reveal similarities and differences between the individual approaches.

Rapid Layer Technology (RLT) uses computer-aided design/computer-aided manufacturing (CAD/CAM) to manufacture a veneer layer that is adhesively bonded to the zirconia framework, avoiding firing steps during the fabrication process and thus preventing build-up of residual stresses. This work studied, using sliding contact fatigue, the in vitro lifetime of restorations produced using RLT compared with restorations produced using conventional veneering techniques. Zirconia copings were veneered with a conventional hand-layering method (VM9) using a fast (n = 16) or a slow (n = 16) cooling protocol, or with RLT. For the latter, the veneers were CAD/CAM fabricated using a feldspathic reinforced-glass (Vitablocs Mark II; n = 16) or a polymer-infiltrated reinforced-glass network (Enamic; n = 16) and adhesively bonded to the zirconia frameworks. Crowns thus obtained were submitted to sliding contact fatigue against a steatite indenter in a chewing simulator until failure. A Kaplan-Meier survival analysis was conducted. None of the hand-layered restorations survived after a 2 × 106 -cycle interval, whereas no fractures in the RLT groups were observed. Vitablocs Mark II veneers survived for a longer testing period (3.5 × 106 cycles) than their Enamic counterparts (2.5 × 106 cycles) owing to their superior wear behavior. The RLT represents an efficient method to veneer zirconia frameworks by reducing processing steps and, more importantly, increasing the lifetime of the restorations.

The author examines the Translation and Miracles of St. Swithun by the tenth-century monk Lantfred as a way of gauging the relationship of the laity to the reformist bishop AEthelwold and the monks of the Old Minster Cathedral in Winchester during the first generation of the Benedictine Reform in tenth-century Anglo-Saxon England.

Forecasters and research meteorologists tested a real-time three-dimensional variational data assimilation (3DVAR) system in the Hazardous Weather Testbed during the springs of 2010–12 to determine its capabilities to assist in the warning process for severe storms. This storm-scale system updates a dynamically consistent three-dimensional wind field every 5 min, with horizontal and average vertical grid spacings of 1 km and 400 m, respectively. The system analyzed the life cycles of 218 supercell thunderstorms on 27 event days during these experiments, producing multiple products such as vertical velocity, vertical vorticity, and updraft helicity. These data are compared to multiradar–multisensor data from the Warning Decision Support System–Integrated Information to document the performance characteristics of the system, such as how vertical vorticity values compare to azimuthal shear fields calculated directly from Doppler radial velocity. Data are stratified by range from the nearest radar, as well as by the number of radars entering into the analysis of a particular storm. The 3DVAR system shows physically realistic trends of updraft speed and vertical vorticity for a majority of cases. Improvements are needed to better estimate the near-surface winds when no radar is nearby and to improve the timeliness of the input data. However, the 3DVAR wind field information provides an integrated look at storm structure that may be of more use to forecasters than traditional radar-based proxies used to infer severe weather potential.