Search for: All records

Wave-Powered Reverse Osmosis (WPRO) represents a promising convergence of ocean energy harvesting and advanced Reverse Osmosis (RO) desalination techniques. The significant fluctuations in pressures and flow rates within the integrated WPRO system present a critical challenge, necessitating an accurate transient model for effective performance estimation. This study presents a two-dimensional transient model based on pressure-correction algorithm to simulate channel flow with membrane boundary conditions under varying inlet conditions. The coupled dynamics of pressure, velocity, and salt concentration are addressed iteratively by decoupling and updating each term separately. The model investigates the performance of RO systems under different input conditions, including constant, sinusoidal, and irregular flow. The results indicate that constant input with higher pressure and lower flow rate achieves a better Recovery Ratio (RR). It is emphasized that for WPRO systems, a fair comparison requires choosing the same average power or pressure when evaluating different inputs. Under equivalent input power, sinusoidal waves result in a lower RR compared to constant inputs due to reduced average pressure. Conversely, under equivalent inlet pressure and flow rate, sinusoidal waves achieve a higher RR than constant inputs due to the phase difference between pressuredriven permeate velocity and diffusion-driven Concentration Polarization (CP). Specifically, sinusoidal inputs with higher frequency and higher amplitude display a higher RR. Additionally, irregular input yields a higher RR than constant inputs, as mean pressure and power can be maintained at levels comparable to those of constant input. The model’s adaptability to diverse flow regimes — from steady to sinusoidal and irregular fluctuations — highlights its potential as a critical tool for optimizing RO desalination processes powered by renewable ocean energy. 

Abstract Ocean wave-powered reverse osmosis (RO) desalination is an emerging field of study that combines the utilization of ocean energy and RO desalination techniques. However, due to the significant fluctuations in pressure and flow rate within the hydraulic system, an accurate transient model is necessary to estimate its performance accurately and effectively. This paper presents a two-dimensional transient model based on the pressure-correction algorithm to simulate the channel flow with porous walls and time-dependent inlet conditions. The coupled pressure, velocity, and salt concentration problem is solved iteratively by decoupling each term and updating them separately. The model is validated by comparing the results with analytical film theory which estimates the formation of the concentration polarization layer under constant inlet conditions. The performance of the RO systems, especially the concentration polarization phenomenon at the member surface, is investigated using different input conditions, including constant flow condition and sinusoidal flow condition. The salt concentration and permeate flux at the membrane boundary are studied to understand the effect of the dynamic inputs. Results show that the system can reach a higher maximum wall concentration and higher average recovery ratio in sinusoidal signal compared with the constant input. The model’s adaptability to different flow regimes, from steady to sinusoidal, underscores its potential as a valuable tool in optimizing RO desalination powered by ocean wave energy. 

The dynamics of a liquid droplet impacting a liquid film of different compositions is critical for many industrial processes, including additive manufacturing and bio-printing. In this work we present an exposition of droplet impact on liquid films investigating the effects of mismatch in their properties on bouncing-to-merging transitions. Experiments are conducted for two sets of liquid combinations, namely, alkanes and silicon oils. The regime maps for impact outcomes (bouncing vs merging) are created from detailed experiments with various single- and two-liquid systems. The results highlight that the two-liquid systems exhibit an additional merging regime, which is not observed for single-liquid systems. Subsequently, the scaling analyses for transitional boundaries between various regimes are revisited, and new scaling laws are proposed to include the effects of asymmetry in the droplet and film properties. Finally, the experimental results are used to assess the performance of the proposed scaling laws. 

Abstract. Future changes in the El Niño–Southern Oscillation (ENSO) are uncertain, both because future projections differ between climate models and because the large internal variability of ENSO clouds the diagnosis of forced changes in observations and individual climate model simulations. By leveraging 14 single model initial-condition large ensembles (SMILEs), we robustly isolate the time-evolving response of ENSO sea surface temperature (SST) variability to anthropogenic forcing from internal variability in each SMILE. We find nonlinear changes in time in many models and considerable inter-model differences in projected changes in ENSO and the mean-state tropical Pacific zonal SST gradient. We demonstrate a linear relationship between the change in ENSO SST variability and the tropical Pacific zonal SST gradient, although forced changes in the tropical Pacific SST gradient often occur later in the 21st century than changes in ENSO SST variability, which can lead to departures from the linear relationship. Single-forcing SMILEs show a potential contribution of anthropogenic forcing (aerosols and greenhouse gases) to historical changes in ENSO SST variability, while the observed historical strengthening of the tropical Pacific SST gradient sits on the edge of the model spread for those models for which single-forcing SMILEs are available. Our results highlight the value of SMILEs for investigating time-dependent forced responses and inter-model differences in ENSO projections. The nonlinear changes in ENSO SST variability found in many models demonstrate the importance of characterizing this time-dependent behavior, as it implies that ENSO impacts may vary dramatically throughout the 21st century.