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This paper examines the positive and negative aspects of a range of interpretations of nearest-neighbours models. Measures-oriented and distributionoriented verification methods are applied to categorial, probabilistic and descriptive interpretations of nearest neighbours used operationally in avalanche forecasting in Scotland and Switzerland. The dependence of skill and accuracy measures on base rate is illustrated. The purpose of the forecast and the definition of events are important variables in determining the quality of the forecast. A discussion of the application of different interpretations in operational avalanche forecasting is presented.
Using results from an 8 m2 instrumented force plate we describe field measurements of normal and shear stresses, and fluid pore pressure for a debris flow. The flow depth increased from 0.1 to 1 m within the first 12 s of flow front arrival, remained relatively constant until 100 s, and then gradually decreased to 0.5 m by 600 s. Normal and shear stresses and pore fluid pressure varied in-phase with the flow depth. Calculated bulk densities are ρb = 2000–2250 kg m−3 for the bulk flow and ρf = 1600–1750 kg m−3 for the fluid phase. The ratio of effective normal stress to shear stress yields a Coulomb basal friction angle of ϕ = 26° at the flow front. We did not find a strong correlation between the degree of agitation in the flow, estimated using the signal from a geophone on the force plate, and an assumed dynamic pore fluid pressure. Our data support the idea that excess pore-fluid pressures are long lived in debris flows and therefore contribute to their unusual mobility.
The powerful avalanche simulation toolbox RAMMS (Rapid Mass Movements) is based on a depth-averaged
hydrodynamic system of equations with a Voellmy-Salm friction relation. The two empirical friction parameters
μ and correspond to a dry Coulomb friction and a viscous resistance, respectively. Although μ and lack a
proper physical explanation, 60 years of acquired avalanche data in the Swiss Alps made a systematic calibration
possible. RAMMS can therefore successfully model avalanche flow depth, velocities, impact pressure and run
out distances. Pudasaini and Hutter (2003) have proposed extended, rigorously derived model equations that
account for local curvature and twist. A coordinate transformation into a reference system, applied to the actual
mountain topography of the natural avalanche path, is performed. The local curvature and the twist of the
avalanche path induce an additional term in the overburden pressure. This leads to a modification of the Coulomb
friction, the free-surface pressure gradient, the pressure induced by the channel, and the gravity components
along and normal to the curved and twisted reference surface. This eventually guides the flow dynamics and
deposits of avalanches. In the present study, we investigate the influence of curvature on avalanche flow in
real mountain terrain. Simulations of real avalanche paths are performed and compared for the different models
approaches. An algorithm to calculate curvature in real terrain is introduced in RAMMS. This leads to a curvature
dependent friction relation in an extended version of the Voellmy-Salm model equations. Our analysis provides
yet another step in interpreting the physical meaning and significance of the friction parameters used in the
RAMMS computational environment.
Numerical avalanche dynamics models have become an essential part of snow engineering. Coupled with field observations and historical records, they are especially helpful in understanding avalanche flow in complex terrain. However, their application poses several new challenges to avalanche engineers. A detailed understanding of the avalanche phenomena is required to construct hazard scenarios which involve the careful specification of initial conditions (release zone location and dimensions) and definition of appropriate friction parameters. The interpretation of simulation results requires an understanding of the numerical solution schemes and easy to use visualization tools. We discuss these problems by presenting the computer model RAMMS, which was specially designed by the SLF as a practical tool for avalanche engineers. RAMMS solves the depth-averaged equations governing avalanche flow with accurate second-order numerical solution schemes. The model allows the specification of multiple release zones in three-dimensional terrain. Snow cover entrainment is considered. Furthermore, two different flow rheologies can be applied: the standard Voellmy–Salm (VS) approach or a random kinetic energy (RKE) model, which accounts for the random motion and inelastic interaction between snow granules. We present the governing differential equations, highlight some of the input and output features of RAMMS and then apply the models with entrainment to simulate two well-documented avalanche events recorded at the Vallée de la Sionne test site.
Two- and three-dimensional avalanche dynamics models are being increasingly used in hazard-mitigation studies. These models can provide improved and more accurate results for hazard mapping than the simple one-dimensional models presently used in practice. However, two- and three-dimensional models generate an extensive amount of output data, making the interpretation of simulation results more difficult. To perform a simulation in three-dimensional terrain, numerical models require a digital elevation model, specification of avalanche release areas (spatial extent and volume), selection of solution methods, finding an adequate calculation resolution and, finally, the choice of friction parameters. In this paper, the importance and difficulty of correctly setting up and analysing the results of a numerical avalanche dynamics simulation is discussed. We apply the two-dimensional simulation program RAMMS to the 1968 extreme avalanche event In den Arelen. We show the effect of model input variations on simulation results and the dangers and complexities in their interpretation.
Digital elevation models (DEMs), represent the three-dimensional terrain and are the basic input for numerical snow avalanche dynamics simulations. DEMs can be acquired using topographic maps or remote-sensing technologies, such as photogrammetry or lidar. Depending on the acquisition technique, different spatial resolutions and qualities are achieved. However, there is a lack of studies that investigate the sensitivity of snow avalanche simulation algorithms to the quality and resolution of DEMs. Here, we perform calculations using the numerical avalance dynamics model RAMMS, varying the quality and spatial resolution of the underlying DEMs, while holding the simulation parameters constant. We study both channelized and open-terrain avalanche tracks with variable roughness. To quantify the variance of these simulations, we use well-documented large-scale avalanche events from Davos, Switzerland (winter 2007/08), and from our large-scale avalanche test site, Valĺee de la Sionne (winter 2005/06). We find that the DEM resolution and quality is critical for modeled flow paths, run-out distances, deposits, velocities and impact pressures. Although a spatial resolution of ~25 m is sufficient for large-scale avalanche modeling, the DEM datasets must be checked carefully for anomalies and artifacts before using them for dynamics calculations.
This paper describes the implementation of topographic curvature effects within the RApid Mass MovementS (RAMMS) snow avalanche simulation toolbox. RAMMS is based on a model similar to shallow water equations with a Coulomb friction relation and the velocity dependent Voellmy drag. It is used for snow avalanche risk assessment in Switzerland. The snow avalanche simulation relies on back calculation of observed avalanches. The calibration of the friction parameters depends on characteristics of the avalanche track. The topographic curvature terms are not yet included in the above mentioned classical model. Here, we fundamentally improve this model by mathematically and physically including the topographic curvature effects. By decomposing the velocity dependent friction into a topography dependent term that accounts for a curvature enhancement in the Coulomb friction, and a topography independent contribution similar to the classical Voellmy drag, we construct a general curvature dependent frictional resistance, and thus propose new extended model equations. With three site-specific examples, we compare the apparent frictional resistance of the new approach, which includes topographic curvature effects, to the classical one. Our simulation results demonstrate substantial effects of the curvature on the flow dynamics e.g., the dynamic pressure distribution along the slope. The comparison of resistance coefficients between the two models demonstrates that the physically based extension presents an improvement to the classical approach. Furthermore a practical example highlights its influence on the pressure outline in the run out zone of the avalanche. Snow avalanche dynamics modeling natural terrain curvature centrifugal force friction coefficients.
In the present work, a novel method for monitoring sterilisation processes with gaseous H2O2 in combination with heat activation by means of a specially designed calorimetric gas sensor was evaluated. Therefore, the sterilisation process was extensively studied by using test specimens inoculated with Bacillus atrophaeus spores in order to identify the most influencing process factors on its microbicidal effectiveness. Besides the contact time of the test specimens with gaseous H2O2 varied between 0.2 and 0.5 s, the present H2O2 concentration in a range from 0 to 8% v/v (volume percent) had a strong influence on the microbicidal effectiveness, whereas the change of the vaporiser temperature, gas flow and humidity were almost negligible. Furthermore, a calorimetric H2O2 gas sensor was characterised in the sterilisation process with gaseous H2O2 in a wide range of parameter settings, wherein the measurement signal has shown a linear response against the H2O2 concentration with a sensitivity of 4.75 °C/(% v/v). In a final step, a correlation model by matching the measurement signal of the gas sensor with the microbial inactivation kinetics was established that demonstrates its suitability as an efficient method for validating the microbicidal effectiveness of sterilisation processes with gaseous H2O2.
In this paper we consider low Péclet number flow in bead packs. A series of relaxation exchange experiments has been conducted and evaluated by ILT analysis. In the resulting correlation maps, we observed a collapse of the signal and a translation towards smaller relaxation times with increasing flow rates, as well as a signal tilt with respect to the diagonal. In the discussion of the phenomena we present a mathematical theory for relaxation exchange experiments that considers both diffusive and advective transport. We perform simulations based on this theory and discuss them with respect to the conducted experiments.
Determination of the frictional coefficient of the implant-antler interface : experimental approach
(2012)
The similar bone structure of reindeer antler to human bone permits studying the osseointegration of dental implants in the jawbone. As the friction is one of the major factors that have a significant influence on the initial stability of immediately loaded dental implants, it is essential to define the frictional coefficient of the implant-antler interface. In this study, the kinetic frictional forces at the implant-antler interface were measured experimentally using an optomechanical setup and a stepping motor controller under different axial loads and sliding velocities. The corresponding mean values of the static and kinetic frictional coefficients were within the range of 0.5–0.7 and 0.3–0.5, respectively. An increase in the frictional forces with increasing applied axial loads was registered. The measurements showed an evidence of a decrease in the magnitude of the frictional coefficient with increasing sliding velocity. The results of this study provide a considerable assessment to clarify the suitable frictional coefficient to be used in the finite element contact analysis of antler specimens.
Although Selective Laser Melting (SLM) process is an innovative manufacturing method, there are challenges such as inferior mechanical properties of fabricated objects. Regarding this, buckling deformation which is caused by thermal stress is one of the undesired mechanical properties which must be alleviated. As buckling deformation is more observable in hard to process materials, silver is selected to be studied theoretically and experimentally for this paper. Different scanning strategies are utilized and a Finite Element Method (FEM) is applied to calculate the temperature gradient in order to determine its effect on the buckling deformation of the objects from experiments.
Semiconductor-based chemical imaging sensors, like the light-addressable potentiometric sensor (LAPS) or the pH-imaging sensor based on a charge-coupled device (CCD), are becoming a powerful tool for label-free imaging of biological phenomena. We have proposed a polyion-based enzymatic membrane to develop an acetylcholine (ACh) imaging sensor for neural cell-activity observations. In this study, a CCD-type ACh-imaging sensor and a LAPS-type ACh-imaging sensor were fabricated and the prospect of both sensors was clarified by making a comparison of their basic characteristics.
Often, detailed simulations of heat conduction in complicated, porous media have large runtimes. Then homogenization is a powerful tool to speed up the calculations by preserving accurate solutions at the same time. Unfortunately real structures are generally non-periodic, which requires unpractical, complicated homogenization techniques. We demonstrate in this paper, that the application of simple, periodic techniques to realistic media, that are just close to periodic, gives accurate, approximative solutions. In order to obtain effective parameters for the homogenized heat equation, we have to solve a so called “cell problem”. In contrast to periodic structures it is not trivial to determine a suitable unit cell, which represents a non-periodic media. To overcome this problem, we give a rule of thumb on how to choose a good cell. Finally we demonstrate the efficiency of our method for virtually generated foams as well as real foams and compare these results to periodic structures.
Numerical solution of the heat equation with non-linear, time derivative-dependent source term
(2010)
The mathematical modeling of heat conduction with adsorption effects in coated metal structures yields the heat equation with piecewise smooth coefficients and a new kind of source term. This term is special, because it is non-linear and furthermore depends on a time derivative. In our approach we reformulated this as a new problem for the usual heat equation, without source term but with a new non-linear coefficient. We gave an existence and uniqueness proof for the weak solution of the reformulated problem. To obtain a numerical solution, we developed a semi-implicit and a fully implicit finite volume method. We compared these two methods theoretically as well as numerically. Finally, as practical application, we simulated the heat conduction in coated aluminum fibers with adsorption in the zeolite coating. Copyright © 2010 John Wiley & Sons, Ltd.
Field-effect capacitive electrolyte-insulator-semiconductor (EIS) sensors functionalised with citrate-capped gold nanoparticles (AuNP) have been used for the electrostatic detection of macromolecules by their intrinsic molecular charge. The EIS sensor detects the charge changes in the AuNP/macromolecule hybrids induced by the adsorption or binding events. A feasibility of the proposed detection scheme has been exemplary demonstrated by realising EIS sensors for the detection of poly-D-lysine molecules.
The chemical imaging sensor is a chemical sensor which is capable of visualizing the spatial distribution of chemical species in sample solution. In this study, a novel measurement system based on the chemical imaging sensor was developed to observe the inside of a Y-shaped microfluidic channel while injecting two sample solutions from two branches. From the collected chemical images, it was clearly observed that the injected solutions formed laminar flows in the microfluidic channel. In addition, ion diffusion across the laminar flows was observed. This label-free method can acquire quantitative data of ion distribution and diffusion in microfluidic devices, which can be used to determine the diffusion coefficients, and therefore, the molecular weights of chemical species in the sample solution.
This work describes the novel combination of the light-addressable electrode (LAE) and the light-addressable potentiometric sensor (LAPS) into a microsystem set-up. Both the LAE as well as the LAPS shares the principle of addressing the active spot by means of a light beam. This enables both systems to manipulate resp. to detect an analyte with a high spatial resolution. Hence, combining both principles into a single set-up enables the active stimulation e.g., by means of electrolysis and a simultaneous observation e.g., the response of an entrapped biological cell by detection of extracellular pH changes. The work will describe the principles of both technologies and the necessary steps to integrate them into a single set-up. Furthermore, examples of application and operation of such systems will be presented.
A variety of transition metals, e.g., copper, zinc, cadmium, lead, etc. are widely used in industry as components for wires, coatings, alloys, batteries, paints and so on. The inevitable presence of transition metals in industrial processes implies the ambition of developing a proper analytical technique for their adequate monitoring. Most of these elements, especially lead and cadmium, are acutely toxic for biological organisms. Quantitative determination of these metals at low activity levels in different environmental and industrial samples is therefore a vital task. A promising approach to achieve an at-side or on-line monitoring on a miniaturized and cost efficient way is the combination of a common potentiometric sensor array with heavy metal-sensitive thin-film materials, like chalcogenide glasses and polymeric materials, respectively.
The construction of a statistical test is investigated which is based only on “reliability” and “precision” as quality criteria. The reliability of a statistical test is quantifiedin a straightforward way by the probability that the decision of the test is correct. However, the quantification of the precision of a statistical test is not at all evident. Thereforethe paper presents and discusses several approaches. Moreover the distinction of “nullhypothesis” and “alternative hypothesis” is not necessary any longer.
Real-time and reliable monitoring of the biogas process is crucial for a stable and efficient operation of biogas production in order to avoid digester breakdowns. The concentration of dissolved hydrogen (H₂) represents one of the key parameters for biogas process control. In this work, a one-chip integrated combined amperometric/field-effect sensor for monitoring the dissolved H₂ concentration has been developed for biogas applications. The combination of two different transducer principles might allow a more accurate and reliable measurement of dissolved H₂ as an early warning indicator of digester failures. The feasibility of the approach has been demonstrated by simultaneous amperometric/field-effect measurements of dissolved H₂ concentrations in electrolyte solutions. Both, the amperometric and the field-effect transducer show a linear response behaviour in the H₂ concentration range from 0.1 to 3% (v/v) with a slope of 198.4 ± 13.7 nA/% (v/v) and 14.9 ± 0.5 mV/% (v/v), respectively.
Deoxyribonucleic acid (DNA) and protein recognition are now standard tools in biology. In addition, the special optical properties of microsphere resonators expressed by the high quality factor (Q-factor) of whispering gallery modes (WGMs) or morphology dependent resonances (MDRs) have attracted the attention of the biophotonic community. Microsphere-based biosensors are considered as powerful candidates to achieve label-free recognition of single molecules due to the high sensitivity of their WGMs. When the microsphere surface is modified with biomolecules, the effective refractive index and the effective size of the microsphere change resulting in a resonant wavelength shift. The transverse electric (TE) and the transverse magnetic (TM) elastic light scattering intensity of electromagnetic waves at 600 and 1400 nm are numerically calculated for DNA and unspecific binding of proteins to the microsphere surface. The effect of changing the optical properties was studied for diamond (refractive index 2.34), glass (refractive index 1.50), and sapphire (refractive index 1.75) microspheres with a 50 µm radius. The mode spacing, the linewidth of WGMs, and the shift of resonant wavelength due to the change in radius and refractive index, were analyzed by numerical simulations. Preliminary results of unspecific binding of biomolecules are presented. The calculated shift in WGMs can be used for biomolecules detection.
In this paper we present CAESAR, an intelligent domestic service robot. In domestic settings for service robots complex tasks have to be accomplished. Those tasks benefit from deliberation, from robust action execution and from flexible methods for human–robot interaction that account for qualitative notions used in natural language as well as human fallibility. Our robot CAESAR deploys AI techniques on several levels of its system architecture. On the low-level side, system modules for localization or navigation make, for instance, use of path-planning methods, heuristic search, and Bayesian filters. For face recognition and human–machine interaction, random trees and well-known methods from natural language processing are deployed. For deliberation, we use the robot programming and plan language READYLOG, which was developed for the high-level control of agents and robots; it allows combining programming the behaviour using planning to find a course of action. READYLOG is a variant of the robot programming language Golog. We extended READYLOG to be able to cope with qualitative notions of space frequently used by humans, such as “near” and “far”. This facilitates human–robot interaction by bridging the gap between human natural language and the numerical values needed by the robot. Further, we use READYLOG to increase the flexible interpretation of human commands with decision-theoretic planning. We give an overview of the different methods deployed in CAESAR and show the applicability of a system equipped with these AI techniques in domestic service robotics