Use of Monitoring Approaches to Verify the Predictive Accuracy of the Modeling of Particle-Bound Solid Inputs to Surface Waters

For particle-bound substances such as phosphorus, erosion is an important input pathway to surface waters. Therefore, knowledge of soil erosion by water and sediment inputs to water bodies at high spatial resolution is essential to derive mitigation measures at the regional scale. Models are used to calculate soil erosion and associated sediment inputs to estimate the resulting loads. However, validation of these models is often not sufficiently possible. In this study, sediment input was modeled on a 10 × 10 m grid for a subcatchment of the Kraichbach river in Baden-Wuerttemberg (Germany). In parallel, large-volume samplers (LVS) were operated at the catchment outlet, which allowed a plausibility check of the modeled sediment inputs. The LVS produced long-term composite samples (2 to 4 weeks) over a period of 4 years. The comparison shows a very good agreement between the modeled and measured sediment loads. In addition, the monitoring concept of the LVS offers the possibility to identify the sources of the sediment inputs to the water body. In the case of the Kraichbach river, it was found that around 67% of the annual sediment load in the water body is contributed by rainfall events and up to 33% represents dry-weather load. This study shows that the modeling approaches for calculating the sediment input provide good results for the test area Kraichbach and the transfer for a German wide modeling will produce plausible values.

Automated vessel centerline extraction and diameter measurement in OCT Angiography

Optical Coherence Tomography Angiography (OCTA) is a non-invasive imaging technique that enables the visualization of perfused vasculature in vivo. In ophthalmology, it allows the physician to monitor diseases affecting the vascular networks of the retina such as agerelated macular degeneration or diabetic retinopathy. Due to the complexity of the vasculature in the retina, it is of interest to automatically extract vascular parameters which describe the condition of the vessels. Suitable parameters could improve the diagnosis and the treatment during the course of therapy. We present an automated algorithm to compute the diameters of the vessels in en face OCTA images. After segmenting the images, the vessel centerline was computed using a thinning algorithm. The centerline was refined by detecting invalid pixels such as spurs and by continuing the centerline until the ends of the vessels. Lastly, the diameter was computed by dilating a discrete circle at the position of the centerline or by measuring the distance between both borders of the vessels. The developed algorithms were applied to in vivo images of human eyes. Certainly, no ground truth was available. Hence, a plausibility check was performed by comparing the measured diameters of two different layers of the retina (Superficial Vascular Complex (SVC) and Deep Vascular Complex (DVC)). Each layer exhibits a different characteristic vasculature. The algorithm clearly reflected the differences from both retinal layers. The measured diameters demonstrate that the DVC consists of more capillaries and considerably smaller vessels compared to the SVC. The presented method enables automated analysis of the retinal vasculature and forms thereby the basis for monitoring diseases influencing the vasculature of the retina. The validation of the method using an artificial ground truth is still needed.

Risk Management in Seaports: A Community Analysis at the Port of Hamburg

The aim of this work is to detect communities of stakeholders at the port of Hamburg regarding their communication intensity in activities related to risk management. An exploratory mixed-method design is chosen as a methodology based on a compact survey and semi-structured interviews, as well as secondary data. A compact survey at the port of Hamburg is utilized to address the communication intensity values among stakeholders. Based on 28 full responses, the data is extracted, cleansed, and prepared for the network analysis using the software “Gephi”. Thereafter, the Louvain community detection algorithm is used to extract the communities from the network. A plausibility check is carried out using 15 semi-structured interviews and secondary data to verify and refine the results of the community analysis. The results have revealed different communities for the following risk categories: (a) natural disasters and (b) operational and safety risks. The focus of cooperation is on the reactive process and emergency plans. For instance, emergency plans play an important role in the handling of natural disasters such as floods or extreme winds.

Approach and application to transfer heterogeneous simulation data from finite element analysis to neural networks

The simulation of product behavior is a vital part of current virtual product development. It can be expected that soon there will be more product simulations due to the availability of easy-to-use finite element analysis software and computational power. Consequently, the amount of accessible new simulation data adds up to the already existing amount. However, even when using easy-to-use finite element software tools, errors can occur during the setup of finite element simulations, and users should be warned about certain mistakes by automatic algorithms. To use the vast amount of available finite element simulations for a data-driven finite element support tool, in this paper, a methodology will be presented to transform different finite element simulations to unified matrices. The procedure is based on the projection of nodes onto a detector sphere, which is converted into a matrix in the next step. The generated matrices represent the simulation and can be described as the DNA of a finite element simulation. They can be used as an input for any machine learning model, such as convolutional neural networks. The essential steps of preprocessing the data and an application with a large dataset are part of this contribution. The trained network can then be used for an automatic plausibility check for new simulations, based on the previous simulation data from the past. This can result in a tool for automatic plausibility checks and can be the backbone for a feedback system for less experienced users.

A Design Tool for Supercritical CO2 Radial Compressors Based on the Two-Zone Model

In supercritical Carbon Dioxide (sCO2) cycles, the compressor inlet conditions are selected near the critical point where compressibility factor reaches values as low as 0.2. Consequently, conventional compressor design approaches formulated for fluids obeying the ideal gas law are not verified. Therefore, this paper proposes a design approach for sCO2 radial compressors that consists of a performance prediction model in addition to a set of geometry parameters suitable for radial compressors. The compressor model is based on the two-zone modeling approach, in which the Span and Wagner equation of state for CO2 is integrated. At first, the compressor model is presented in addition to the required correlations. Afterwards, a sensitivity analysis is performed on the model main parameters. Thereafter, a plausibility check is performed against experimentally obtained data. Finally, an overall design approach is proposed and its capability to deliver new geometries is assessed by comparing the tool predictions against the results from a verified CFD code for several test cases. The Comparison shows a maximum deviation of less than 2 percent for the pressure ratio and less than 3.5 percentage points for the efficiency. The results indicate the ability of the proposed approach to predict the performance of sCO2 compressor from correlations that originate from experience with conventional fluids. Additionally, the adopted geometric relations proved its applicability to sCO2 compressors.

Robust Polymer Planar Bragg Grating Sensors Embedded in Commercial-Grade Composites

This contribution demonstrates the functionality of polymer planar Bragg grating (PPBG) sensors integrated into commercial-grade carbon fiber reinforced polymer (CFRP) components. Multiple CFRP specimens are generated by curing a stack of pre-impregnated fibers inside of a heated mechanical press, exposing the polymer sensor to a pressure of 7 bar and a temperature of 120 °C for 2 h. After integration, the sensor still exhibits a strong and evaluable signal. Subsequent flexural experiments reveal a linear response of the integrated sensor’s Bragg wavelength to the CFRP specimen’s maximum deflection. Additional findings demonstrate that the embedded PPBG can be used to detect plastic deformations of a CFRP workpiece, whereas a linear correlation of plastic deformation to the resulting Bragg signal offset is determined. A plausibility check of the obtained results is delivered by a comparison of three-point flexural experiments on bulk CFRP workpieces, without integrated sensors and additional specimens featuring external optical sensors affixed to their surface. It is found that PPBGs based on cyclic olefin copolymers are able to overcome the temperature-related limitations of traditional polymer-based optical sensors and can thus be directly integrated into commercial-grade composites during production.

Vehicle-to-Vehicle (V2V) Message Content Plausibility Check for Platoons through Low-Power Beaconing

Although the IEEE Wireless Access in Vehicular Environment (WAVE) and 3GPP Cellular V2X deployments are imminent, their standards do not yet cover an important security aspect; the message content plausibility check. In safety-critical driving situations, vehicles cannot blindly trust the content of received safety messages, because an attacker may have forged false values in it in order to cause unsafe response from the receiving vehicles. In particular, the attacks mounted from remote, well-hidden positions around roads are considered the most apparent danger. So far, there have been three approaches to validating V2X message content: checking based on sensor fusion, behavior analysis, and communication constraints. This paper discusses the three existing approaches. In addition, it discusses a communication-based checking scheme that supplements the existing approaches. It uses low-power transmission of vehicle identifiers to identify remote attackers. We demonstrate its potential address in the case of an autonomous vehicle platooning application.

Novel Closed-Form Equation for Critical Pressure and Optimum Pressure Ratio for Turbojet Engines

Advanced mathematical model has been developed for design and analysis of turbojet engines. It includes closed form algebraic equation for critical pressure and optimum pressure ratio at maximum thrust. The model and the algebraic equations consider efficiencies, pressure recovery rates meanwhile the gas parameters are the function of the fuel to air ratio and the temperature. РД-9Б and АЛ-21Ф3 engines are applied for demonstrating the capabilities of the calculation process. The unknown parameters as efficiencies, pressure recovery rates, power reduction rate of the auxiliary systems, bleed air ratio, air income ratio due to blade cooling and total temperature in the afterburner were identified by constrained optimization. The effect of i. T04/T02 ratio for the thrust and TSFC in the function of compressor pressure ratio, ii. the real (viscous) flow conditions and iii. the temperature and fuel to air ratio on gas parameters were also investigated for verification and plausibility check.