HyGear (Netherlands)

Grass cover erosion by wave overtopping is a major failure mechanism for earthen dikes. Grass cover erosion resistance (represented by the critical velocity, Uc) can be assessed using full-scale, destructive tests with the wave overtopping simulator (WOS) in combination with the erosion model ‘cumulative overload method’ (COM). Although these tests provide valuable information, they are relatively expensive and time consuming. Therefore, a small-scale grass pullout test (GPT), which translates the vertical pullout force of a grass sod to a Uc, may be an attractive alternative. In this paper, based on comparative testing with the WOS and GPT on three species-rich grass covers on dikes in the Netherlands, we assess the correspondence between the Uc obtained with the WOS and GPT for species-rich grass covers. Ultimately, by also including historical tests, we aim to get more insight into the suitability of the GPT for quantitative erodibility assessment of grass covers in general. During testing with the WOS, no failure was observed for the tested grass cover sections. Therefore only a lower bound of the Uc could be derived. Results indicate that the estimated Uc with the GPT is around the lower bound values obtained with the WOS. This is in line with previous tests on conventional grass covers, for which the GPT provides a more conservative estimate of the Uc than the WOS. Adaptations in the translation from pullout force to Uc may correct for the negative bias and hence improve the reliability of the GPT for quantitative erodibility assessment. Several suggestions to adapt the GPT in future work are provided in this paper. These adaptations should be tested and validated for conventional as well as species-rich grass covers to guarantee the general applicability of the method.

Operation of the SOFC power system can be improved by upgrading the low-level controllers with a supervisory controller (see Figure 1). In this work a simple, model-free supervisory optimizer that adjusts references for the low level controllers is proposed. The optimization problem for the SOFC power system is formulated with the cost function depending on the electrical efficiency of the system and deviations of the system temperatures from their limits. Electrical efficiency is calculated as the ratio of the net electrical power to the total power obtained by burning the fuel. The dominant parasitic losses of the system are assumed to be mainly related to the air blower consumption. Based on efficiency analysis, which demands a number of simulations on SOFC power system model, the references for the burner lambda and stack outlet and inlet air temperatures are selected as optimization variables. The optimization problem is solved by using the extremum-seeking approach where optimum is sought directly on the process. An advantage of this approach is that it does not need a model of the system and exceeds the weakness of model-based optimizers, which assume nominal process condition all the time and do not take into account the degradation processes in fuel cells. Its disadvantage is it needs to probe the system at all time by imposing small variations on manipulated variables and delivers a convergence speed which is somewhat slower compared to the model based approach. A simple algorithm is designed to perform the model-free optimization. The algorithm is additionally augmented to incorporate changes in the current load in order to increase the convergence speed of the optimization at large load changes. The efficiency of the optimizer is governed by properly tuned parameters of the optimization algorithm. Proposed supervisory optimizer is assessed on a simulated detailed physical model of a 2.5 kW SOFC power system by applying large step current load changes. Simulation results indicate that the optimizer improves efficiency of the system by approximately 10 % compared to the low-level controllers and keeps the system temperatures within the safe ranges (see Figure 2). Due to its simplicity the optimizer appears appropriate for practical applications. Figure 1

A PV powered inflatable tent has been developed using flexible PV modules which have been integrated in the tent's roof leading to a light-weight and easily usable product. This this paper presents energy balance studies, the modular reinforced flexible PV system design and other design features of this product-integrated PV application. The nominal power of the PV powered tent is at present 544 Wp (at η=8%). It contains a battery of 300 Ah, which is sufficient for power supply to basic functions such as the use of mobile phones and light.