Search NASA⌕ Search

SEARCH · Search NASA

Results for “SANITATION”

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.

190 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

3D Printed Materials Characterization for Rapid Prototyping and Plant Growth

Through KSC IRTD funding in 2022, this project brought a list of 18, 3D printed filaments into formal characterization testing to provide a reference for their behaviors under relevant applications. The project format set up a series of tests to expose 3D printed specimens. A total of 1,989 individual 3D printed test specimens were sent across KSC to be scrutinized by three laboratories to fulfill a multidisciplinary assessment of each material TRL. Testing started with 18 materials. Initially, seed germination assays in the PPA, sample materials were enclosed in petri dishes with lettuce seeds on damp germination paper. No significant impacts on lettuce seed germination were observed in this testing. Next, sample coupons were printed and sent for materials testing to the KSC Analysis/Mechanical and Environmental Testing Laboratory, where they were subjected to 14- and 30-day soak periods in solutions used to provide nutrients to plants or to sanitize hardware before and after use. Following a long soak typical of a 30-day plant growout in Hoagland’s solution, 14 materials gained more than 10% of their own mass. This indicated an increased potential for leaching or providing conditions that are not food safe. Materials that exceeded 15% absorption by mass were eliminated from further testing. Based off this result, the team continued with a core list of nine filaments to fulfill Tensile, Flexural, Biofilm formation, and plant growth testing. Those materials were PLA (Raise3D), ABS (Raise3D), PETG (PolyethyleneTerephthalate Glycol) (Raise3D), ASA (Acrylonitrile Styrene Acrylate) (Raise3D), PC (Polycarbonate) (Raise3D), TPU (Thermoplastic polyurethane)-95 (Raise3D), PLA Copper (Gizmodorks), PP (Polypropylene) (Braskem), and HIPS (High Impact Polystyrene) (Gizmodorks). Testing also quantified the spectral impact of using different color 3D printed surfaces in a growth chamber. The material used for spectral testing was PLA. Printing employed a standard surface texture representative of all materials. It was shown through Tensile Testing (ASTM D638-22) that the breaking force of a 3D printed part greatly varied depending on layer orientation. This is common through all materials, and demonstrates that the strength of a 3D printed component can be maximized by layering the material normal to the primary force on the part. Four-point flexural testing (ASTM D790) provided quantities of interest, Flexural modulus, Flexural strength, Flexural stress, and strain at break within a 5% strain limit from each of nine materials. Biofilm formation testing was conducted in the Molecular and Microbiological Laboratory. Testing completed on specimens from each material showed equal formation on the surface. Additional plant growth testing was conducted in the PPA beyond the initial germination testing. The final assessment documents that three materials (PLA, ABS, and PC) have reached TRL 6 through extensive testing, and ultimate end-to-end applied use in experimental or testing conditions (flight and ground). TRL 5 materials (ASA, TPU-95, PLA Copper, PP, PETG, and HIPS) have all been successfully applied in Research and Development for crop growth applications and are ready to be applied in formal testing. TRL 4 materials Nylon910, PLA Carbon Fiber, PPA CF, PPA Glass Fiber (GF), NinjaFlex, and P-filament 721 are materials that were able to be printed and tested, but have yet to show data meeting applied requirements. TRL 3 NylonX, Flex TPE-185, and Nylon were unable to be reliably printed to fulfill testing. These results provide researchers with reference for materials to use during plant growth experimentation, and also set a standard for future characterization work applying 3D printing and materials to testing, research, and experimentation.

Gioia Massa↗
DOE OSTI2021

Methods, apparatus and systems for generating and superheating vapor under sunlight

A solar vapor generator includes an absorber to absorb sunlight and an emitter, in thermal communication with the absorber, to radiatively evaporate a liquid under less than 1 sun illumination and without pressurization. The emitter is physically separated from the liquid, substantially reducing fouling of the emitter. The absorber and the emitter may also be heated to temperatures higher than the boiling point of the liquid and may thus may be used to further superheat the vapor. Solar vapor generation can provide the basis for many sustainable desalination, sanitization, and process heating technologies.

Chen, Gang↗
DOE OSTI2022

E-Beam Irradiation Beamline at Jefferson Lab for Wastewater Treatment

Electron beam (e-beam) irradiation is an advanced method for removing the emerging organic contaminants in wastewater, such as 1,4-dioxane, and per- and polyfluoroalkyl sub?stances (PFAS), which have the potential to be regulated in the near future but are difficult to degrade by conventional treatment methods. This dissertation was based on a collabo?rating study between Jefferson Lab (Jlab) and Hampton Roads Sanitation District (HRSD) to evaluate the impacts of e-beam irradiation on the degradation of 1,4-dioxane and PFAS. It presents the detailed design of an e-beam irradiation beamline, the beamline simulation using general particle tracer (GPT), the installation, and the successful commissioning. The beamline is an extended section to the Upgraded Injector Test Facility (UITF) at Jlab, which is a continuous wave (CW), superconducting radio frequency (SRF) linear accelerator with an energy up to 10 MeV. To let the sample volume receive a significant and uniform dose distribution, the sample target was designed by investigating the dose distribution simulated with a Monte-Carlo code, FLUKA. The optimized beam energy was 8 MeV and the beam current for irradiation was ? 100 nA. With the use of a solenoid and a raster, the electron beam was expanded to the optimized size, 1? ? 15 mm, at the sample target. This dis?sertation also presents the irradiation experiments for 64 1,4-dioxane samples and 48 PFAS samples in different water matrices, including real wastewater, which were prepared and an?alyzed by HRSD. The absorbed doses of samples were obtained by designing a new method that combines the FLUKA simulation and dose mapping experiments. The irradiation re?sults showed that around 95% of 1,4-dioxane was removed at a low dose of ? 2 kGy, and PFAS was possibly removed at a lower dose compared to similar research. This work is a first implementation of SRF technology for wastewater irradiation. It pro?vides a valuable new research platform for wastewater remediation. This will be in support of future industrial applications of advanced SRF technologies and better understanding of the effect of e-beam irradiation on wastewater or water treatment.

Li, Xi↗
DOE OSTI2020

Investigation of Radiological Contamination at Parks in the Gateway National Recreation Area - 20350

In 2005, the National Park Service was notified that elevated radiation levels were detected at Great Kills Park during a baseline radiological mapping effort conducted by the Counter Terrorism Bureau of the New York City Police Department and the United States Department of Energy. Great Kills Park is in the Staten Island Unit of the Gateway National Recreation Area. A records search determined that approximately 280 acres of the park was established over an area in which the New York City Department of Sanitation placed approximately 15.1 million cubic yards of waste fill from 1944 to 1948. Since 2005, a series of response actions and investigations were conducted on behalf of the National Park Service to mitigate risk to human health and the environment and to determine the nature of radiological contamination at Great Kills Park. The findings support that radiological contamination is related to certain components of waste fill, including incinerator residue from both on and offsite incinerators, coal ash from the historical use of coal-fired boilers for heating, and incidental radiological artifacts in the waste fill due to their historical use and subsequent disposal. A majority of the radiological artifacts were determined to contain radium-226 and included radioluminescent markers, radium impregnated switch board buttons, radium paint containers, and brachytherapy devices. The National Park Service has several other Parks in the Gateway National Recreation Area that were established in areas with a similar history to Great Kills Park, and overlie waste fill historically placed during landfilling operations, including Spring Creek Park and Dead Horse Bay. Over the last year, the National Park Service has performed additional radiological investigations at Great Kills Park as part of the ongoing Remedial Investigation under the Comprehensive Environmental Response, Compensation, and Liability Act. In addition, preliminary radiological investigations were performed at Spring Creek Park and Dead Horse Bay Park in the Jamaica Bay Unit of Gateway National Recreation Area. These investigation activities identified gamma radiation levels above the ambient level, several of which were attributable to radiological artifacts similar in nature to those recovered at Great Kills Park. Ongoing investigations at Parks in the Gateway National Recreation Area support an association between radiological contamination and historical landfilling practices that were common prior to the regulation and control of radioactive materials. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Software engineering to sustain a high-performance computing scientific application: QMCPACK

We provide an overview of the software engineering efforts and their impact in QMCPACK, a production-level ab-initio Quantum MonteCarlo open-source code targeting high-performance computing (HPC) systems. Aspects included are: (i) strategic expansion ofcontinuous integration (CI) targeting CPU, using GitHub Actions runners, and graphics processing units (GPU) in pre-exascalesystems, using self-hosted hardware; (ii) incremental reduction of memory leaks using sanitizers, (iii) incorporation of Dockercontainers for CI and reproducibility, and (iv) refactoring efforts to improve maintainability, testing coverage, and memory lifetime management. We quantify the value of these improvements by providing metrics to illustrate the shift towards a predictive, rather than reactive, sustainable maintenance approach. Our goal, in documenting the impact of these efforts on QMCPACK, is to contribute to the body of knowledge on the importance of research software engineering (RSE) for the sustainability of community HPC codes and scientific discovery at scale.

Godoy, William↗
DOE OSTI2026

Feedforward-feedback ammonia control at a water resource recovery facility based on a digital twin with hybrid model

Ammonia-based aeration control (ABAC) at full-scale Water Resource Recovery Facilities (WRRFs) can be challenged by diurnal loading and transport delays. This work addressed these challenges using a hybrid feedforward–feedback controller built on Activated Sludge Model 1 (ASM1), marking the first full-scale deployment to pair a mechanistic feedforward core with data-driven corrections. The objectives were to improve ammonia setpoint tracking, assess performance of the mechanistic model when enhanced with data-driven corrections, and document full-scale operation. The hybrid model incorporates two data-driven components: (1) a Mechanistic Error Forecasting Engine (MEFE), consisting of a multivariate linear regressor and a long short-term memory (LSTM) ensemble. Defying expectations, low-parameter models outperformed more complex alternatives, reducing the mechanistic error by 71%. (2) A Residual Oscillation Forecasting Engine (ROFE), based on Fast Fourier Transform, reduced the remaining error by another 35%. Two proportional–integral (PI) feedback loops further (i) trim the feedforward output and (ii) eliminate residual controller error in the final aerobic zone. In full-scale operation, the controller reduced mean-squared error (MSE) by 94% over the baseline and produced more stable dissolved oxygen (DO) setpoints. Overall, it was proven that layering multi-timescale data-driven models on a mechanistic core can yield reliable ABAC performance at WRRFs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Design considerations for a Digital Twin built to improve nitrification performance at a water resource recovery facility

A Digital Twin built around Activated Sludge Model No. 1 was deployed at a full-scale water resource recovery facility. Its design included a waste rate recommender system based on automatic scenario analyses, where influent loads and waste rates are varied to determine their impact on nitrification. At the same frequency as these scenario analyses, scheduled auto-calibrations allow for nitrifier maximum specific growth rate (μmax-NITO) soft sensing, the only kinetic parameter shown to require adjustment if the objective is aeration tank effluent ammonia forecasting accuracy. By integrating temperature forecasting over the next three sludge ages, this Digital Twin approach creates opportunities for advancing waste rate decisions in anticipation of seasonal temperature changes, optimizing ammonia control authority under varying influent loads, and furnishing valuable insights for future capital projects requiring nitrifier kinetic understanding and modelling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Data about data – when, why and how metadata can support the digital plant

A structured approach for recording data quality and contextual information about how and why a signal exists – i.e. metadata – is central to interpret and use sensor data correctly. This is becoming increasingly important with the global trend with data-driven applications such as digital twins and AI-models. But a structured metadata collection and organization of sensor data is not routine in most plants, which can result in lost information and missed opportunities to make use of the investments made in the data collection. Therefore, the IWA task group on Metadata Collection and Organization in wastewater resource recovery systems (MetaCO) was initiated in 2020 and recently delivered the IWA scientific and technical report number 31. The report gives and in-depth description about metadata in water resources recovery facilities (WRRFs) and is available as open access at IWA publishing. The report is the outcome of the collaboration between more than 80 water professionals with the intention to serve WRRF data users with a guide on how to structure and make use of metadata throughout the data pipeline in order to maximize the value of sensor data.

Alferes, Janelcy [VITO, Belgium]↗