Search NASA⌕ Search

SEARCH · Search NASA

Results for “Forward Osmosis”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

63 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

TOUGHREACT V4.12

TOUGHREACT V4.12 is a 3-D reactive transport code that handles to non-isothermal, multiphase/multicomponent fluid flow, heat transport, aqueous and gaseous species advection-diffusion, and equilibrium/kinetic water-gas-rock-biological reactions. TOUGHREACT V4.12 is based on TOUGHREACT V3.3, with several new features including: an option to compute activity coefficients using the Pitzer ion interaction model; implementation of ECO2N V2.0 for temperatures up to 300 C; options to simulate forward and reverse osmosis, including 2D Poiseuille flow; addition of EOS8 and revisions for EOS5 and EWASG with H2(g); addition of gas species decay, various new output formats and time step control options; many bug fixes.

Spycher, Nicolas↗
NASA NTRS2015

Results of the Alternative Water Processor Test, A Novel Technology for Exploration Wastewater Remediation

Biologically‐based water recovery systems are a regenerative, low energy alternative to physiochemical processes to reclaim water from wastewater. This paper summarizes the results of the Alternative Water Processor (AWP) test conducted over one year. The AWP recovered 90% of water from four crewmembers using (4) membrane aerated bioreactors (MABRs) to remove carbon and nitrogen from an exploration mission wastewater, including urine, hygiene, laundry and humidity condensate. Downstream, a coupled forward and reverse osmosis system removed large organics and inorganic salts from the biological system effluent. The system exceeded the overall objectives of the test by recovering 90% of the influent wastewater processed and a 29% reduction of consumables from the current state of the art water recovery system on the International Space Station (ISS). However the biological system fell short of its test goals, failing to remove 75% and 90% of the influent ammonium and organic carbon, respectively. Despite not meeting its test goals, the BWP demonstrated the feasibility of an attachedgrowth biological system for simultaneous nitrification and denitrification, an innovative, volume and consumable‐saving design that doesn't require toxic pretreatment. This paper will explain the reasons for this and will discuss steps to optimize each subsystem to increase effluent quality from the MABRs and the FOST to advance the system.

Leticia Vega↗
NASA NTRS2016

Results of the Alternative Water Processor Test, A Novel Technology for Exploration Wastewater Remediation

Biologically-based water recovery systems are a regenerative, low energy alternative to physiochemical processes to reclaim water from wastewater. This report summarizes the results of the Alternative Water Processor (AWP) Integrated Test, conducted from June 2013 until April 2014. The system was comprised of four (4) membrane aerated bioreactors (MABRs) to remove carbon and nitrogen from an exploration mission wastewater and a coupled forward and reverse osmosis system to remove large organic and inorganic salts from the biological system effluent. The system exceeded the overall objectives of the test by recovering 90% of the influent wastewater processed into a near potable state and a 64% reduction of consumables from the current state of the art water recovery system on the International Space Station (ISS). However, the biological system fell short of its test goals, failing to remove 75% and 90% of the influent ammonium and organic carbon, respectively. Despite not meeting its test goals, the BWP demonstrated the feasibility of an attached-growth biological system for simultaneous nitrification and denitrification, an innovative, volume- and consumable-saving design that does not require toxic pretreatment.

Meyer, Caitlin E.↗
NASA NTRS2016

Results of the Alternative Water Processor Test, A Novel Technology for Exploration Wastewater Remediation

Biologically-based water recovery systems are a regenerative, low energy alternative to physiochemical processes to reclaim water from wastewater. This paper summarizes the results of the Alternative Water Processor (AWP) test conducted over one year. The AWP recovered 90% of water from four crewmembers using (4) membrane aerated bioreactors (MABRs) to remove carbon and nitrogen from an exploration mission wastewater, including urine, hygiene, laundry and humidity condensate. Downstream, a coupled forward and reverse osmosis system removed large organics and inorganic salts from the biological system effluent. The system exceeded the overall objectives of the test by recovering 90% of the influent wastewater processed and a 29% reduction of consumables from the current state of the art water recovery system on the International Space Station (ISS). However the biological system fell short of its test goals, failing to remove 75% and 90% of the influent ammonium and organic carbon, respectively. Despite not meeting its test goals, the BWP demonstrated the feasibility of an attached-growth biological system for simultaneous nitrification and denitrification, an innovative, volume and consumable-saving design that doesn't require toxic pretreatment. This paper will explain the reasons for this and will discuss steps to optimize each subsystem to increase effluent quality from the MABRs and the FOST to advance the system.

Leticia Vega↗
DOE OSTI2022

Theoretical Pathway toward Improved Reverse Osmosis Membrane Selectivity for Neutral Solutes: Inspiration from Gas Separations

We report highly rigid membrane materials with tailored structures have exhibited permeabilities and selectivities that exceed the polymer upper bound in gaseous and organic solvent separations for challenging mixtures containing species that are similar in size and shape. One potential question is whether such membrane materials can maintain meaningful guest diffusivities in situations where the microporous spaces are essentially full of guest molecules. Here, we use a simplified transition state theory approach to estimate the diffusivity of water and small organics within a microporous membrane. The transition state theory model is parameterized using experimental values from zeolites and carbon molecular sieve materials found in the literature. We demonstrate the differences in transport and Maxwell–Stefan diffusivities based on guest species loading with different isotherm behaviors. These calculations theorize a path forward for highly selective reverse osmosis membranes for aqueous phase separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2005

Online fault adaptive control for efficient resource management in Advanced Life Support Systems

This article presents the design and implementation of a controller scheme for efficient resource management in Advanced Life Support Systems. In the proposed approach, a switching hybrid system model is used to represent the dynamics of the system components and their interactions. The operational specifications for the controller are represented by utility functions, and the corresponding resource management problem is formulated as a safety control problem. The controller is designed as a limited-horizon online supervisory controller that performs a limited forward search on the state-space of the system at each time step, and uses the utility functions to decide on the best action. The feasibility and accuracy of the online algorithm can be assessed at design time. We demonstrate the effectiveness of the scheme by running a set of experiments on the Reverse Osmosis (RO) subsystem of the Water Recovery System (WRS).

NASA Discipline Life Support Systems↗
DOE OSTI2024

Machine learning models of intermittent operation of RO wellhead water treatment for salinity reduction and nitrate removal

Machine learning models were developed for intermittent multi-mode operation of a wellhead reverse osmosis water purification and desalination system to predict salt passage, nitrate passage, and permeate flux. The models, based on long short-term memory (LSTM) recurrent neural network (RNN) architecture, included an attention mechanism to increase model performance in proximity of the regulatory limit for nitrate. Training and testing of the models for the Startup, Production, Shutdown and Flushing operational modes were based on operational data (consisting of 22 process variables per data sample) acquired every 2–5 s over a six-month period. The significant sets of model input attributes for the different operational modes were assessed via Spearman ranking correlation, Self-Organizing Map (SOM) analysis and feed forward feature selection (FFFS). Although the variability of nitrate passage, salt passage and permeate flux was significant over the four operational modes, prediction performance for the three outcomes were with R2 and Average Absolute Relative Error (AARE) of 0.78–0.95 and 2.96–6.16 %, respectively. Model updates post membrane elements replacement demonstrated similar levels of prediction accuracy. The study results suggest that there is merit in exploring the utility of multi-mode models for sensor fault detection, data imputation, and for potential use in model-predictive control.

Intermittent RO operation↗
DOE OSTI2025

Predicting Initial Trans-Membrane Pressure for Optimized Operations in UF Unit Using Random Forest

With the growing scarcity of freshwater, innovative process design mechanisms like Reverse Osmosis (RO) are increasingly gaining attention among water treatment utilities to address the rising demand. Ensuring reliable water production necessitates efficient resource utilization, minimizing downtime in (ultra-filtration) UF systems. Recent advancements in machine learning (ML) have enabled the development of accurate data-driven models for Model Predictive Control (MPC), often requiring minimal prior knowledge of underlying physical processes. In this study, we present predictive regression models based on Random Forest (RF) and Auto-Regressive (AR) approaches to forecast the initial Trans-Membrane Pressure (TMP) for each filtration cycle in data generated by Direct Potable Reuse (DPR) systems. The proposed RF-based model demonstrates superior performance compared to baseline methods, including historical mean, Last Observation Carried Forward (LOCF), and naïve AR models, across various forecasting horizons in terms of root mean square error (RMSE) metric. To evaluate how different classes of process variables contribute to TMP dynamics over time, we examine the feature importance of independent covariates across multiple forecast horizons. This analysis provides insight into the temporal relevance of operational and sensor-derived features, guiding control and monitoring strategies. Additionally, the impact of hyperparameter tuning on TMP prediction performance is studied for both direct and recursive RF modelling approaches across increasing forecast horizons. Accurate prediction of initial TMP is critical for optimizing RO operations, as it enables the development of robust modelling frameworks by accurately estimating membrane fouling trends, thereby enhancing process efficiency and long-term reliability. The demonstrated efficacy of the RF-based approach highlights its potential as a tool for real-time decision-making in water treatment systems, paving the way for advanced process optimization and sustainable water resource management.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗
DOE OSTI2020

Measuring Neutrino Oscillations in the NOvA and CHIPS Detectors.

NOvA is a long baseline neutrino experiment which uses muon neutrinos produced by the NuMI beam at the Fermi National Accelerator Laboratory to measure muon neutrino disappearance and electron neutrino appearance, among other analyses. The Far/Near Extrapolation analysis framework (FNEX) was used to measure muon neutrino disappearance using the events observed by NOvA while the NuMI beam was in Forward Horn Current configuration (i.e. this analysis uses neutrino data, not antineutrino data). The values of the parameters measured in this analysis are sin 2 θ 23 - 0.499$^{+0.098}_{-0.069}$ and Δm$^2_{32}$ - 2.454$^{+0.108}_{0.119}$ × 10 -3 eV, which is consistent with the results of NOvA’s main muon neutrino disappearance analysis using the experiment’s usual framework, known as CAF. The CHIPS detector is a water Cherenkov detector currently in construction. It will also use the NuMI beam to perform muon neutrino disappearance and electron neutrino appearance analyses. The necessary water clarity for a detector with a diameter of 25 m and a height of 6 m is discussed, as well as the results of testing water filtration systems. The filtration that will be used for the detector is a 10 µm carbon block filter and a 0.5 µm filter in series, with no reverse osmosis or ultraviolet sterilisation being used. This provides an attenuation length of 16.63 ± 0.25 m for light of 532 nm wavelength (green), so light with a wavelength of 405 nm (violet) would have an attenuation length of 133±2 m. The greatest possible distance between a PMT and any point in the detector’s volume is approximately 26 m, so 133 m is sufficient for the detector to measure Cherenkov light produced anywhere in the detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗