Configuration and Enablement of Vision Sensor Solutions Through a Combined Simulation Based Process Chain

Machine vision solutions can perform within a wide range of applications and are commonly used to verify the operation of production systems. They offer the potential to automatically record assembly states and derive information, but simultaneously require a high effort of planning, configuration and implementation. This generally leads to an iterative, expert based implementation with long process times and sets major barriers for many companies. Furthermore the implementation is task specific and needs to be repeated with every variation of product, environment or process. Therefore a novel concept of a simulation-based process chain for both—configuration and enablement—of machine vision systems is presented in this paper. It combines related work of sensor planning algorithms with new methods of training data generation and detailed task specific analysis for assembly applications.

Exploring Kv1.2 Channel Inactivation Through MD Simulations and Network Analysis

The KCNA2 gene encodes the Kv1.2 channel, a mammalian Shaker-like voltage-gated K+ channel, whose defections are linked to neuronal deficiency and childhood epilepsy. Despite the important role in the kinetic behavior of the channel, the inactivation remained hereby elusive. Here, we studied the Kv1.2 inactivation via a combined simulation/network theoretical approach that revealed two distinct pathways coupling the Voltage Sensor Domain and the Pore Domain to the Selectivity Filter. Additionally, we mutated some residues implicated in these paths and we explained microscopically their function in the inactivation mechanism by computing a contact map. Interestingly, some pathological residues shown to impair the inactivation lay on the paths. In summary, the presented results suggest two pathways as the possible molecular basis of the inactivation mechanism in the Kv1.2 channel. These pathways are consistent with earlier mutational studies and known mutations involved in neuronal channelopathies.

Analysis of Material Susceptibility in Silicon on Insulator Waveguides With Combined Simulation of Four-Wave Mixing and Linear Mode Coupling

We derive propagation equations modeling third-order susceptibility-induced nonlinear interaction and linear mode coupling in waveguides. We model material susceptibility with Raman and electronic response which include approximations suited for optical communications. We validate our model by comparing numerical integration of the propagation equations to continuous wave measurements of a silicon on insulator waveguide.

Multi-Source Coupling Based Analysis of the Acoustic Radiation Characteristics of the Wheel–Rail Region of High-Speed Railways

Based on elastic mechanics, the fluid–structure coupling theory and the finite element method, a high-speed railway wheel-rail rolling-aerodynamic noise model is established to realize the combined simulation and prediction of the vibrations, rolling noise and aerodynamic noise in wheel-rail systems. The field test data of the Beijing–Shenyang line are considered to verify the model reliability. In addition, the directivity of each sound source at different frequencies is analyzed. Based on this analysis, noise reduction measures are proposed. At a low frequency of 300 Hz, the wheel-rail area mainly contributes to the aerodynamic noise, and as the frequency increases, the wheel-rail rolling noise becomes dominant. When the frequency is less than 1000 Hz, the radiated noise fluctuates around the cylindrical surface, and the directivity of the sound is ambiguous. When the frequency is in the middle- and high-frequency bands, exceeding 1000 Hz, both the rolling and total noise exhibit a notable directivity in the directions of 20–30° and 70–90°, and thus, noise reduction measures can be implemented in these directions.

Designed ONE-FLOW System for the Synthesis of Rufinamide

A nano-compartmentalized one-solvent (ONE-FLOW) procedure was developed for the two-step synthesis of Rufinamide, employing a combined simulation and experimental approach. Computer-aided solvent selection was combined with reagent/catalyst compartmentalization in a continuous flow set-up. The synthetic route encompassed azidation of benzyl chloride, followed by a Cu-catalyzed azide alkyne cycloaddition (CuAAC) reaction. A functional solvent was chosen via a COSMO-RS based method, which allowed a one-phase reaction while facilitating a thermally induced final product separation from the reaction mixture. To perform azidation and CuAAC reactions in a microfluidic system, both azidation reagent and Cu(I) catalyst were immobilized, on a packed bed and in the hydrophobic membrane of polymer vesicles, respectively, as this allowed a higher reaction efficiency, facile regeneration of azidation reagent, and recovery of the metal catalyst. This ONE-FLOW process has great benefits for the pharmaceutical industry in their quest to scalable, efficient and safe synthetic processes with minimal waste generation.

A Combined Simulation Approach to Evaluate Overtaking Behaviour on Two-Lane Two-Way Rural Roads

A significant percentage of road fatalities and injuries occur in the nonmotorway rural road network. One of the main causes of accidents on these roads is represented by overtaking, as, by its nature, it involves a risk of a head-on collision with oncoming traffic. The paper describes a combined simulation approach (driving simulator and traffic microsimulation) designed to examine the influence of different traffic conditions on passing manoeuvres on two-lane two-way rural roads. The main focus was the evaluation of the end of the passing manoeuvre because it reflects the risk of a head-on collision. In addition, the study aimed to assess the usefulness of the proposed combined approach in the ability to proactively and quickly diagnose traffic safety problems and consequently to evaluate appropriate solutions. The data collected with an interactive driving simulator on a sample of 54 participants have been used to adjust some input data of the traffic microsimulation software. A specific situation consisting of a stationary heavy vehicle obstructing the entire lane was repeated in both experiments. The analyses focused on time-to-collision (TTC), defined as the remaining gap between the passing vehicle and the oncoming vehicle at the end of the passing manoeuvre. The results showed that the type of manoeuvre performed is significantly influenced by the traffic condition. Furthermore, the manoeuvre is influenced by the gap between two successive vehicles in the opposite lanes. Focusing on the end of the manoeuvre, it was found how a traffic increase leads to a significant reduction of the TTC values. Furthermore, the comparative analysis conducted between the data recorded following the combined approach and those obtained using exclusively the input data of the microsimulation software supports the usefulness of the proposed methodology for conducting road safety analyses, especially in complex traffic environments where drivers’ behaviour plays a decisive role.

Optimal ANC System Arrangement Based on Complete System Analyses Applying COSMOL Multiphysics and Matlab

In real active noise control system implementation, the arrangement of secondary sources and error microphones have significant effect on the performance of the system. Analytical and experimental ways are usually combined to determine the best system layout. In this paper, we use COSMOL Multiphysics to accurately model the acoustic environment in enclosures with the real measured dimensions and parameters. Matlab is adopted to simulate the basic active noise control algorithms. The combined simulation results are used to decide the optimal system layout of the real ANC system. Experiments are conducted on a real ANC system with EVAL-21489-EZLITE from ADI to validate the analyzed and simulation results.

Combined simulation and optimization framework for irrigation scheduling in agriculture fields

In the context of growing evidence of climate change and the fact that agriculture uses about 70% of all the water available for irrigation in semi-arid areas, there is an increasing probability of water scarcity scenarios. Water irrigation optimization is, therefore, one of the main goals of researchers and stakeholders involved in irrigated agriculture. Irrigation scheduling is often conducted based on simple water requirement calculations without accounting for the strong link between water movement in the root zone, soil–water–crop productivity and irrigation expenses. In this work, we present a combined simulation and optimization framework aimed at estimating irrigation parameters that maximize the crop net margin. The simulation component couples the movement of water in a variably saturated porous media driven by irrigation with crop water uptake and crop yields. The optimization component assures maximum gain with minimum cost of crop production during a growing season. An application of the method demonstrates that an optimal solution exists and substantially differs from traditional methods. In contrast to traditional methods, results show that the optimal irrigation scheduling solution prevents water logging and provides a more constant value of water content during the entire growing season within the root zone. As a result, in this case, the crop net margin cost exhibits a substantial increase with respect to the traditional method. The optimal irrigation scheduling solution is also shown to strongly depend on the particular soil hydraulic properties of the given field site.