Micro-Range Actuation by Pressure-Induced Elastic Deformation of 316L Steel Membranes Produced by Laser Powder Bed Fusion

In this paper, fundamental research is performed on membrane type actuators made out of 316L stainless steel, manufactured with Laser powder bed fusion (LPBF). A total of six membranes with membrane thicknesses ranging from 0.6 mm up to 1.2 mm were scanned using a high precision metrology system to measure the membrane for displacement at different actuating pressures. The membranes were furthermore investigated for roughness, porosity and thickness. This showed that the thinnest membranes skewed in the print direction when actuated. The remaining membranes achieved higher specific displacements than finite element simulations (FES) predicted, due to surface roughness and porosity. Membrane type actuators can be used for precise actuation within the micrometre range. LPBF allows the creation of internal pockets and membranes in a single metal piece. In opposition to the more commonly used polymers for membrane-type actuators, LPBF steel printed parts offer high stiffness and actuation force. However, due to limitations of the LPBF process on thin walls, large deviations from FES occur. In this paper, a CAD and FES compensation strategy is suggested, which makes future, more complex and effective, designs possible

Spike-Based Sensing and Communication for Highly Energy-Efficient Sensor Edge Nodes

Highly energy-efficient wireless sensor nodes are a prerequisite for a sustainable operation of the Internet of things. Therefore, classical approaches for system design based on digital signal processing are not a viable solution, but system design has to follow entirely new paradigms. In this regard, we present a sensory system with analog spike-based signal processing for sensing and communication, encoding the sensory information in the pulse repetition frequency (PRF), getting rid of energy hungry A/D and D/A conversion. Our spiking sensory system can generate spikes from any conventional analog output sensor using a compact, highly tunable voltage-controlled oscillator based on vanadium dioxide, and an analog differentiator circuit performing the transmit pulse shaping. The sole conversion from analog to digital takes place at the base station followed by the estimation of the PRF, for which we compare a conventional receiver design consisting of an analog-to-digital converter (ADC) with the use of an integrate-and-fire time encoding machine (IFTEM). Results show the successful communication of sensory information from the edge node over an additive white Gaussian noise channel to the base station, with the IF-TEM outperforming the conventional ADC for a signal-to-noise ratio above 0 dB

GrSMBMIP: Intercomparison of the modelled 1980-2012 surface mass balance over the Greenland Ice Sheet

Observations and models agree that the Greenland Ice Sheet (GrIS) surface mass balance (SMB) has decreased since the end of the 1990s due to an increase in meltwater runoff and that this trend will accelerate in the future. However, large uncertainties remain, partly due to different approaches for modelling the GrIS SMB, which have to weigh physical complexity or low computing time, different spatial and temporal resolutions, different forcing fields, and different ice sheet topographies and extents, which collectively make an inter-comparison difficult. Our GrIS SMB model intercomparison project (GrSMBMIP) aims to refine these uncertainties by intercomparing 13 models of four types which were forced with the same ERA-Interim reanalysis forcing fields, except for two global models. We interpolate all modelled SMB fields onto a common ice sheet mask at 1 km horizontal resolution for the period 1980-2012 and score the outputs against (1) SMB estimates from a combination of gravimetric remote sensing data from GRACE and measured ice discharge; (2) ice cores, snow pits and in situ SMB observations; and (3) remotely sensed bare ice extent from MODerate-resolution Imaging Spectroradiometer (MODIS). Spatially, the largest spread among models can be found around the margins of the ice sheet, highlighting model deficiencies in an accurate representation of the GrIS ablation zone extent and processes related to surface melt and runoff. Overall, polar regional climate models (RCMs) perform the best compared to observations, in particular for simulating precipitation patterns. However, other simpler and faster models have biases of the same order as RCMs compared with observations and therefore remain useful tools for long-term simulations or coupling with ice sheet models. Finally, it is interesting to note that the ensemble mean of the 13 models produces the best estimate of the present-day SMB relative to observations, suggesting that biases are not systematic among models and that this ensemble estimate can be used as a reference for current climate when carrying out future model developments. However, a higher density of in situ SMB observations is required, especially in the south-east accumulation zone, where the model spread can reach 2 m w.e. yr-1 due to large discrepancies in modelled snowfall accumulation

GrSMBMIP: intercomparison of the modelled 1980–2012 surface mass balance over the Greenland Ice Sheet

Observations and models agree that the Greenland Ice Sheet (GrIS) surface mass balance (SMB) has decreased since the end of the 1990s due to an increase in meltwater runoff and that this trend will accelerate in the future. However, large uncertainties remain, partly due to different approaches for modelling the GrIS SMB, which have to weigh physical complexity or low computing time, different spatial and temporal resolutions, different forcing fields, and different ice sheet topographies and extents, which collectively make an inter-comparison difficult. Our GrIS SMB model intercomparison project (GrSMBMIP) aims to refine these uncertainties by intercomparing 13 models of four types which were forced with the same ERA-Interim reanalysis forcing fields, except for two global models. We interpolate all modelled SMB fields onto a common ice sheet mask at 1 km horizontal resolution for the period 1980–2012 and score the outputs against (1) SMB estimates from a combination of gravimetric remote sensing data from GRACE and measured ice discharge; (2) ice cores, snow pits and in situ SMB observations; and (3) remotely sensed bare ice extent from MODerate-resolution Imaging Spectroradiometer (MODIS). Spatially, the largest spread among models can be found around the margins of the ice sheet, highlighting model deficiencies in an accurate representation of the GrIS ablation zone extent and processes related to surface melt and runoff. Overall, polar regional climate models (RCMs) perform the best compared to observations, in particular for simulating precipitation patterns. However, other simpler and faster models have biases of the same order as RCMs compared with observations and therefore remain useful tools for long-term simulations or coupling with ice sheet models. Finally, it is interesting to note that the ensemble mean of the 13 models produces the best estimate of the present-day SMB relative to observations, suggesting that biases are not systematic among models and that this ensemble estimate can be used as a reference for current climate when carrying out future model developments. However, a higher density of in situ SMB observations is required, especially in the south-east accumulation zone, where the model spread can reach 2 m w.e. yr−1 due to large discrepancies in modelled snowfall accumulation.Project H2020 PROTECT https://protect-slr.eu