Relation between the eigenfrequencies of Bogoliubov excitations of Bose-Einstein condensates and the eigenvalues of the Jacobian in a time-dependent variational approach

We study the relation between the eigenfrequencies of the Bogoliubov excitations of Bose-Einstein condensates, and the eigenvalues of the Jacobian stability matrix in a variational approach which maps the Gross-Pitaevskii equation to a system of equations of motion for the variational parameters. We do this for Bose-Einstein condensates with attractive contact interaction in an external trap, and for a simple model of a self-trapped Bose-Einstein condensate with attractive 1/r interaction. The stationary solutions of the Gross-Pitaevskii equation and Bogoliubov excitations are calculated using a finite-difference scheme. The Bogoliubov spectra of the ground and excited state of the self-trapped monopolar condensate exhibits a Rydberg-like structure, which can be explained by means of a quantum defect theory. On the variational side, we treat the problem using an ansatz of time-dependent coupled Gaussians combined with spherical harmonics. We first apply this ansatz to a condensate in an external trap without long-range interaction, and calculate the excitation spectrum with the help of the time-dependent variational principle. Comparing with the full-numerical results, we find a good agreement for the eigenfrequencies of the lowest excitation modes with arbitrary angular momenta. The variational method is then applied to calculate the excitations of the self-trapped monopolar condensates, and the eigenfrequencies of the excitation modes are compared.Comment: 15 pages, 12 figure

Flood loss reduction of private households due to building precautionary measures -- lessons learned from the Elbe flood in August 2002

Building houses in inundation areas is always a risk, since absolute flood protection is impossible. Where settlements already exist, flood damage must be kept as small as possible. Suitable means are precautionary measures such as elevated building configuration or flood adapted use. However, data about the effects of such measures are rare, and consequently, the efficiency of different precautionary measures is unclear. To improve the knowledge about efficient precautionary measures, approximately 1200 private households, which were affected by the 2002 flood at the river Elbe and its tributaries, were interviewed about the flood damage of their buildings and contents as well as about their precautionary measures. The affected households had little flood experience, i.e. only 15% had experienced a flood before. 59% of the households stated that they did not know, that they live in a flood prone area. Thus, people were not well prepared, e.g. just 11% had used and furnished their house in a flood adapted way and only 6% had a flood adapted building structure. Building precautionary measures are mainly effective in areas with frequent small floods. But also during the extreme flood event in 2002 building measures reduced the flood loss. From the six different building precautionary measures under study, flood adapted use and adapted interior fitting were the most effective ones. They reduced the damage ratio for buildings by 46% and 53%, respectively. The damage ratio for contents was reduced by 48% due to flood adapted use and by 53% due to flood adapted interior fitting. The 2002 flood motivated a relatively large number of people to implement private precautionary measures, but still much more could be done. Hence, to further reduce flood losses, people's motivation to invest in precaution should be improved. More information campaigns and financial incentives should be issued to encourage precautionary measures

Estimating parameter values of a socio-hydrological flood model

Socio-hydrological modelling studies that have been published so far show that dynamic coupled human-flood models are a promising tool to represent the phenomena and the feedbacks in human-flood systems. So far these models are mostly generic and have not been developed and calibrated to represent specific case studies. We believe that applying and calibrating these type of models to real world case studies can help us to further develop our understanding about the phenomena that occur in these systems. In this paper we propose a method to estimate the parameter values of a socio-hydrological model and we test it by applying it to an artificial case study. We postulate a model that describes the feedbacks between floods, awareness and preparedness. After simulating hypothetical time series with a given combination of parameters, we sample few data points for our variables and try to estimate the parameters given these data points using Bayesian Inference. The results show that, if we are able to collect data for our case study, we would, in theory, be able to estimate the parameter values for our socio-hydrological flood model

Flood-risk mapping: contributions towards an enhanced assessment of extreme events and associated risks

Currently, a shift from classical flood protection as engineering task towards integrated flood risk management concepts can be observed. In this context, a more consequent consideration of extreme events which exceed the design event of flood protection structures and failure scenarios such as dike breaches have to be investigated. Therefore, this study aims to enhance existing methods for hazard and risk assessment for extreme events and is divided into three parts. In the first part, a regionalization approach for flood peak discharges was further developed and substantiated, especially regarding recurrence intervals of 200 to 10 000 years and a large number of small ungauged catchments. Model comparisons show that more confidence in such flood estimates for ungauged areas and very long recurrence intervals may be given as implied by statistical analysis alone. The hydraulic simulation in the second part is oriented towards hazard mapping and risk analyses covering the whole spectrum of relevant flood events. As the hydrodynamic simulation is directly coupled with a GIS, the results can be easily processed as local inundation depths for spatial risk analyses. For this, a new GIS-based software tool was developed, being presented in the third part, which enables estimations of the direct flood damage to single buildings or areas based on different established stage-damage functions. Furthermore, a new multifactorial approach for damage estimation is presented, aiming at the improvement of damage estimation on local scale by considering factors like building quality, contamination and precautionary measures. The methods and results from this study form the base for comprehensive risk analyses and flood management strategies

Is flow velocity a significant parameter in flood damage modelling?

Flow velocity is generally presumed to influence flood damage. However, this influence is hardly quantified and virtually no damage models take it into account. Therefore, the influences of flow velocity, water depth and combinations of these two impact parameters on various types of flood damage were investigated in five communities affected by the Elbe catchment flood in Germany in 2002. 2-D hydraulic models with high to medium spatial resolutions were used to calculate the impact parameters at the sites in which damage occurred. A significant influence of flow velocity on structural damage, particularly on roads, could be shown in contrast to a minor influence on monetary losses and business interruption. Forecasts of structural damage to road infrastructure should be based on flow velocity alone. The energy head is suggested as a suitable flood impact parameter for reliable forecasting of structural damage to residential buildings above a critical impact level of 2 m of energy head or water depth. However, general consideration of flow velocity in flood damage modelling, particularly for estimating monetary loss, cannot be recommended

Review article "Assessment of economic flood damage"

Damage assessments of natural hazards supply crucial information to decision support and policy development in the fields of natural hazard management and adaptation planning to climate change. Specifically, the estimation of economic flood damage is gaining greater importance as flood risk management is becoming the dominant approach of flood control policies throughout Europe. This paper reviews the state-of-the-art and identifies research directions of economic flood damage assessment. Despite the fact that considerable research effort has been spent and progress has been made on damage data collection, data analysis and model development in recent years, there still seems to be a mismatch between the relevance of damage assessments and the quality of the available models and datasets. Often, simple approaches are used, mainly due to limitations in available data and knowledge on damage mechanisms. The results of damage assessments depend on many assumptions, e.g. the selection of spatial and temporal boundaries, and there are many pitfalls in economic evaluation, e.g. the choice between replacement costs or depreciated values. Much larger efforts are required for empirical and synthetic data collection and for providing consistent, reliable data to scientists and practitioners. A major shortcoming of damage modelling is that model validation is scarcely performed. Uncertainty analyses and thorough scrutiny of model inputs and assumptions should be mandatory for each damage model development and application, respectively. In our view, flood risk assessments are often not well balanced. Much more attention is given to the hazard assessment part, whereas damage assessment is treated as some kind of appendix within the risk analysis. Advances in flood damage assessment could trigger subsequent methodological improvements in other natural hazard areas with comparable time-space properties

Flood damage model bias caused by aggregation

Flood risk models provide important information for disaster planning through estimating flood damage to exposed assets, such as houses. At large scales, computational constraints or data coarseness leads to the common practice of aggregating asset data using a single statistic (e.g., the mean) prior to applying non-linear damage functions. While this simplification has been shown to bias model results in other fields, the influence of aggregation on flood risk models has received little attention. This study provides a first order approximation of such errors in 344 damage functions using synthetically generated depths. We show that errors can be as high as 40 % of the total asset value under the most extreme example considered, but this is highly sensitive to the level of aggregation and the variance of the depth values. These findings identify a potentially significant source of error in large-scale flood risk assessments introduced, not by data quality or model transfers, but by modelling approach.</p

Improving effectiveness of honeypots: predicting targeted destination port numbers during attacks using J48 algorithm

During recent years, there has been an increase in cyber-crime and cybercriminal activities around the world and as countermeasures, effective attack prevention and detection mechanisms are needed. A popular tool to augment existing attack detection mechanisms is the Honeypot. It serves as a decoy for luring attackers, with the purpose to accumulate essential details about the intruder and techniques used to compromise systems. In this endeavor, such tools need to effectively listen and keep track of ports on hosts such as servers and computers within networks. This paper investigates, analyzes and predicts destination port numbers targeted by attackers in order to improve the effectiveness of honeypots. To achieve the purpose of this paper, the J48 decision tree classifier was applied on a database containing information on cyber-attacks. Results revealed insightful information on key destination port numbers targeted by attackers, in addition to how these targeted ports vary within different regions around the world

Is flow velocity a significant parameter in flood damage modelling?

Flow velocity is generally presumed to influence flood damage. However, this influence is hardly quantified and virtually no damage models take it into account. Therefore, the influences of flow velocity, water depth and combinations of these two impact parameters on various types of flood damage were investigated in five communities affected by the Elbe catchment flood in Germany in 2002. 2-D hydraulic models with high to medium spatial resolutions were used to calculate the impact parameters at the sites in which damage occurred. A significant influence of flow velocity on structural damage, particularly on roads, could be shown in contrast to a minor influence on monetary losses and business interruption. Forecasts of structural damage to road infrastructure should be based on flow velocity alone. The energy head is suggested as a suitable flood impact parameter for reliable forecasting of structural damage to residential buildings above a critical impact level of 2m of energy head or water depth. However, general consideration of flow velocity in flood damage modelling, particularly for estimating monetary loss, cannot be recommended