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AbstractA common control strategy for the production of recombinant proteins in Pichia pastoris using the alcohol oxidase 1 (AOX1) promotor is to separate the bioprocess into two main phases: biomass generation on glycerol and protein production via methanol induction. This study reports the establishment of a soft sensor for the prediction of biomass concentration that adapts automatically to these distinct phases. A hybrid approach combining mechanistic (carbon balance) and data‐driven modeling (multiple linear regression) is used for this purpose. The model parameters are dynamically adapted according to the current process phase using a multilevel phase detection algorithm. This algorithm is based on the online data of CO2 in the off‐gas (absolute value and first derivative) and cumulative base feed. The evaluation of the model resulted in a mean relative prediction error of 5.52% and R² of .96 for the entire process. The resulting model was implemented as a soft sensor for the online monitoring of the P. pastoris bioprocess. The soft sensor can be used for quality control and as input to process control systems, for example, for methanol control.

AbstractSmart Grids are electrical grids that require a decentralised way of controlling electric power conditioning and thereby control the production and distribution of energy. Yet, the integration of Distributed Renewable Energy Sources (DRESs) in the Smart Grid introduces new challenges with regards to electrical grid balancing and storing of electrical energy, as well as additional monetary costs. Furthermore, the future smart grid also has to take over the provision of Ancillary Services (ASs). In this paper, a distributed ICT infrastructure to solve such challenges, specifically related to ASs in future Smart Grids, is described. The proposed infrastructure is developed on the basis of the Smart Grid Architecture Model (SGAM) framework, which is defined by the European Commission in Smart Grid Mandate M/490. A testbed that provides a flexible, secure, and low-cost version of this architecture, illustrating the separation of systems and responsibilities, and supporting both emulated DRESs and real hardware has been developed. The resulting system supports the integration of a variety of DRESs with a secure two-way communication channel between the monitoring and controlling components. It assists in the analysis of various inter-operabilities and in the verification of eventual system designs. To validate the system design, the mapping of the proposed architecture to the testbed is presented. Further work will help improve the architecture in two directions; first, by investigating specific-purpose use cases, instantiated using this more generic framework; and second, by investigating the effects a realistic number and variety of connected devices within different grid configurations has on the testbed infrastructure.

Abstract The need to increase energy system flexibility, alongside the need to lower fossil fuel use in the food sector, and the importance of refrigeration infrastructure presents an opportunity for Liquid Air Energy Storage (LAES) integrated with refrigerated warehouses. To quantify this opportunity in Europe we analyse energy scenarios and existing refrigeration infrastructure for four countries with diverse energy systems (UK, Spain, Bulgaria and Germany). We find that with growing levels of electricity generation from variable renewable sources and numerous refrigerated warehouses, LAES has the potential to provide value in many areas of the EU through the 2020s. However, LAES is still pre-commercial, and with the proportion of electricity from variable renewable sources still low in many countries it is likely that LAES will not be deployed widely alongside refrigerated warehouses under current market conditions. Countries such as the UK and Spain, which have the greatest need for additional energy system flexibility and the most refrigerated warehouses are likely to gain the most value initially.

Computational fluid dynamics (CFD) studies are carried out on a two-bladed vertical axis wind turbine operating at a wind speed of 8 m/s for tip speed ratios (λ) of 0.50–3.0. The blade is the NACA0021 airfoil with chord length 0.265 m and rotor radius 1 m. Basic sensitivity studies for various time step sizes are carried out. The results are validated against available measurement data from the literature. Excellent agreement is obtained for small λ up to optimum condition. For the higher tip speed ratios, the two-dimensional CFD computations predict higher results than the wind tunnel experiment, but they are very similar to the field measurement data. Wake characteristics are presented, showing that the wake becomes Gaussian at 5 times radius downstream of the rotor. It is shown that complex flow phenomena occur owing to dynamic stall onset, especially for the smaller tip speed ratio.

AbstractEnhancing the efficiency of the electric vehicle’s powertrain becomes a crucial focus, wherein the control system for the traction motor plays a significant role. This paper presents a novel electric vehicle traction motor control system based on a robust predictive direct torque control approach, an improved version of the conventional DTC, where the traditional switching table and the hysteresis regulators are substituted with a predictive block based on an optimization algorithm. Additionally, a robust predictive speed loop regulator is employed instead of the proportional-integral regulator, which integrates a new cost function with a finite horizon, incorporating integral action into the control law based on a Taylor series expansion. This technique’s primary benefit is its independence from the necessity to measure and observe external disturbances, as well as uncertainties related to parameters. The effectiveness of the suggested system was confirmed through simulation and experimental results under the OPAL-RT platform. The findings indicate that the proposed approach outperforms the conventional method in terms of rejecting disturbances, exhibiting robustness to variations in parameters, and minimizing torque ripple.

The basic requirements for materials of modern fortifications are established and substantiated. It is established that concrete of such structures should have high strength under the influence of static loads and low modulus of deformations. To ensure the required deformability, you must use dampers. A quantitative characteristic of reinforcing steel at dynamic dynamic loads is the dynamic strengthening coefficient, which shows the growth of dynamic strength in comparison with static.

A reduction of the inactive components can increase the energy density and reduce production cost of Li‐ion batteries. But an effective reduction of the binder amount also negatively affects the adhesion of the electrode. Herein, slot‐die coating of a primer layer for Li‐ion anodes is investigated. It is shown that the use of a primer layer with only 0.3 g m−2 can increase the adhesive force by the factor of 5 as well as the cell performance for anodes with low binder content. The process limits for a stable, defect‐free primer coating are investigated at coating speeds of up to 550 m min−1. The limits coincide both for a setup without vacuum box and with vacuum box with theory‐based equations. By using a vacuum box, the minimum wet film thickness can be reduced by half.