Engineering Papers⌕ Search
Home/Archive/NASA NTRS

NASA NTRS · 20260005978

Logistics Materials for Reuse

Annie Meier·Jackson Smith·Malay Shah·Ray Pitts·Ella Caudill·Tesia Irwin·Thomas Lipscomb·Tracy Gibson·Jason Fischer·Carolina Franco·Ajchariya Harrison·Arin Crow
View original source ↗Read source document ↗Export metadata ↓

Abstract

The source did not provide an abstract. Follow the original record for more information.

Explore related subjects

trash to gasWaste managementlogisticsbiodegradable materialscompostingsustainabilitytrashReusabilitymaterials

Keep this discovery

BibTeXRIS

Annie Meier, Jackson Smith, Malay Shah, Ray Pitts, Ella Caudill, Tesia Irwin, Thomas Lipscomb, Tracy Gibson, Jason Fischer, Carolina Franco, Ajchariya Harrison, Arin Crow. Logistics Materials for Reuse. https://ntrs.nasa.gov/citations/20260005978

Cite the original work for its findings. Save a collection to share your selection of sources.

Discover connections

MATERIALS subjectReusability subjectTrash subjectWASTE MANAGEMENT subjectbiodegradable materials subjectcomposting subjectsustainability subjecttrash to gas subject

Connections use source metadata and explicit phrase matches, not verified experimental comparisons.

KEEP EXPLORING

Related reports

NASA NTRS2026

The Trash Compaction Processing Systems (TCPS) Ground Unit Control Sample Testing

The Trash Compaction Processing System (TCPS) is being developed by NASA and Sierra Space to process crew trash for long-duration missions. The system compacts and thermally processes mixed spacecraft waste to reduce volume and stabilize the material while managing gas and liquid effluents. A Ground Unit (GU) located at Sierra Space in Madison, Wisconsin was used to run a series of tests using standardized control samples representing different trash conditions, including nominal, high liquid, high cloth, benign, and foam. Gas grab samples were collected during processing and analyzed to identify the compounds present in the effluent stream and compare the concentrations to the NASA spacecraft maximum allowable concentrations (SMACs). Additional testing included odor testing at White Sands Test Facility, aerosol measurements, microbiology, and tile characterization. Overall, the compounds detected in the gas samples were well below the SMAC limits for all trash models tested. The results from this testing are being used to help guide the verification approach and test planning for the TCPS Flight Unit that is planned for on-orbit testing on the International Space Station.

Control Samples↗
NASA NTRSDate not supplied

Design of an AI Trash Sorting Machine for Use on the Moon and Mars

As NASA prepares for Mars colonization, resource conservation will be critical for survival. Artificial Intelligence (AI) powered waste sorting technologies, already emerging on Earth, offer promising solutions for recycling and material recovery. These systems use advanced sensors and machine learning algorithms to identify and separate materials with remarkable accuracy. On Mars, where every item has significant value, efficient recycling will be essential to reduce resupply needs and support closed-loop life support systems. This paper explores how terrestrial AI-based trash sorting technologies can be adapted for Martian conditions, focusing on challenges such as the harsh surface environment, minimizing system mass, power, volume, and estimating waste composition. Addressing these issues will be key to enabling sustainable operations on the Red Planet.

Sorting↗
NASA NTRSDate not supplied

Design of an AI Trash Sorting Machine for Use on the Moon and Mars

As NASA prepares for Mars colonization, resource conservation will be critical for survival. Artificial Intelligence (AI) powered waste sorting technologies, already emerging on Earth, offer promising solutions for recycling and material recovery. These systems use advanced sensors and machine learning algorithms to identify and separate materials with remarkable accuracy. On Mars, where every item has significant value, efficient recycling will be essential to reduce resupply needs and support closed-loop life support systems. This paper explores how terrestrial AI-based trash sorting technologies can be adapted for Martian conditions, focusing on challenges such as the harsh surface environment, minimizing system mass, power, volume, and estimating waste composition. Addressing these issues will be key to enabling sustainable operations on the Red Planet.

AI↗