March 2026 Satellite Puzzler

March 2026 Satellite Puzzler

A satellite view shows green land with scattered light-brown formations containing concentric, uneven oval patterns. Blue water is visible at the top and top-left.

Every month, NASA Earth Observatory features a puzzling satellite image. The March 2026 puzzler appears above. 

Your Challenge
I
dentify the location shown in this satellite image. Share what clues you see, where you think it is, and what makes this place interesting or unique to you.

How to Answer
Submit your response using this form and select “Puzzler Answer” as the topic. Please include your preferred name or alias.

You can keep it simple and just guess the location. Want to impress us? Tell us which satellite and instrument captured the image, which spectral bands were used, or point out a subtle detail about the geology or history of the area. If something catches your eye, or if this is your home or means something to you, we’d love to hear about it.

The Prize
We can’t offer prize money or a trip to space to see Earth like satellites and astronauts do. But we can offer something almost as rewarding: puzzler bragging rights.

Within a week of the challenge, we’ll post the answer at the top of this page, along with a link to an Earth Observatory Image of the Day story that explains the image in more detail. We’ll give a shout-out to the first person who correctly guesses the location, and we may also highlight readers who share especially thoughtful or interesting answers on our blog.

Until then, zoom in, look closely, and enjoy the challenge. See you at the reveal!

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Computational Modeling of Failure at the Fabric Weave Level in Reentry Parachute Energy Modulators  

Computational Modeling of Failure at the Fabric Weave Level in Reentry Parachute Energy Modulators  

Download PDF: Computational Modeling of Failure at the Fabric Weave Level in Reentry Parachute Energy Modulators

Energy modulators (EM) are textile mechanical devices designed to dissipate snatch loads that occur when parachutes are deployed. Although critical for mitigating shock loads, recent flight testing has shown increasing variability in EM behavior, raising concerns about their performance predictability and potential failure under dynamic loading conditions. In response, a novel approach was implemented to create a computational model of an EM at the fabric weave level using the simulation software, LS-DYNA. This work was organized into two primary objectives: (1) development of a per-unit stitch model capturing the geometry and material behavior of the EM stitching pattern, and (2) implementation of a Python script to duplicate the unit model along the full length of an EM ear, simplifying the process of generating complex, patterned geometries in LS-DYNA. 

Depiction of EM extension during stroking from a tensile force applied at the blue arrows with (a) an unextended EM, (b) a partially extended EM, and (c) a fully extended EM
Depiction of EM extension during stroking from a tensile force applied at the blue arrows with (a) an unextended EM, (b) a partially extended EM, and (c) a fully extended EM.

EMs typically consist of a long strip of structural Kevlar webbing that is folded and stitched together with a nylon zigzag stitching pattern to form an EM “ear.” As an EM is pulled above a threshold load during deployment, the nylon stitching rips, unfolding the EM and dissipating shock forces. This process is illustrated in Figure 1, exemplifying stages of EM extension during stroking. In nominal cases, the EM cleanly tears with little damage to the Kevlar webbing. However, anomalous cases have been observed where the nylon stitches along the ear are skipped during loading, i.e., when a row of stitches do not tear in sequence. This results in failure of the surrounding Kevlar webbing, referred to as EM shredding. The inherent unpredictability of the fabric behavior and the high variability of flight loading conditions make a root cause challenging to identify through mechanical testing. 

In this study, development of a computational model of an EM in LS-DYNA was used to gain deeper insight into the cause of EM shredding. While similar studies of fabric webbing have modeled fabrics at a global level, this approach represents each thread of the Kevlar weave and nylon stitching as individually modeled 3D solid elements. Modeling each thread individually within the weave is essential not only for analyzing the failure mechanisms of the nylon stitching as it rips, but also for understanding the Kevlar weave failure during the EM shredding events. 

The first phase of this work focused on modeling individual Kevlar and nylon threads within a representative stitch geometry. A 3D model of the Kevlar weave was first generated using TexGen, an open-source software developed at the University of Nottingham. Using computer-aided design (CAD) software, nylon stitching passing through two layers of the Kevlar fabric weave was added. The nylon stitching pattern consisted of a bobbin thread and a needle thread that looped through the top and bottom layers, respectively, of the Kevlar weave pattern and twisted together at the end of every stitch between the two layers. The unit model was meshed in Hypermesh with 3D tetrahedral solid elements. 

Three‑panel graphic showing the workflow for modeling a woven composite: a 3D woven fabric CAD model in SOLIDWORKS, a meshed version of the weave in HyperMesh, and a color‑coded finite‑element simulation model in LS‑DYNA
A three‑step digital workflow showing how a woven composite structure moves from CAD modeling in SOLIDWORKS, to meshing in HyperMesh, to a color‑coded simulation‑ready model in LS‑DYNA

In LS-DYNA, the material properties, contact, failure conditions, and boundary conditions were defined to assess the dynamic response of a stitch during tensile loading. Material behavior for both fabric types was defined using *MAT_ELASTIC (*MAT_001), and two-way, surface-to-surface contact with erosion was implemented to capture progressive failure of the Kevlar weave and nylon threads. Boundary conditions were applied to replicate in-flight tensile loading scenarios. Additionally, several case studies were conducted to reduce computation time, including manual mass scaling, characteristic length analysis, and mesh quality optimization. 

Preliminary results from the EM per-unit model validated the use of solid elements to capture EM behavior, particularly the interaction between Kevlar and nylon threads. To streamline the construction of full-length EM models, the second phase of this work focused on developing a Python script to replicate the per-unit LS-DYNA model along the length of an EM ear. This eliminated the need for large CAD assemblies by generating the full model directly from duplicating the unit model. This model is applicable to both solid and shell 2D and 3D elements. Overall, these results will not only aid in identifying the root cause of EM shredding but also support the evaluation of new EM design variations. This modeling approach has broader implications for other work involving fabrics, enabling more accurate simulations and efficient design workflows in aerospace textile applications.  

For information, contact Annika M. Vaidyanathan, Alexander Chin, John Bell, and Rumaasha Maasha. 

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Meagan Chappell

Ice to Fuel: NASA Tests Technology for Refueling Landers 

Ice to Fuel: NASA Tests Technology for Refueling Landers 

3 min read

Preparations for Next Moonwalk Simulations Underway (and Underwater)

Two engineers wearing purple gloves peel away wrapping around metal and yellow hardware. The hardware is mounted inside a steel metal frame. This technology could help NASA fuel future missions,
NASA engineers Jonathan Davis, left, and Markus Perkins inspect a flight-like cryocooler developed by Creare LLC prior to its integration into the CryoFILL system NASA is testing. Engineers are working inside NASA Glenn Research Center’s Creek Road Cryogenics Complex on Sept. 24, 2025.
Credit: NASA/Jef Janis

The farther the destination, the more fuel a rocket needs. The more fuel the rocket carries, the heavier the spacecraft. The heavier the spacecraft, the more fuel it requires to launch. Experts at NASA’s Glenn Research Center in Cleveland are testing technology that could solve this problem. 

The CryoFILL (Cryogenic Fluid In-Situ Liquefaction for Landers) project could transform the way NASA fuels future space exploration missions, reducing costs and extending the duration of planetary surface operations.  

“If you think about how much fuel your spacecraft would need to go to Mars and come home, it’s quite a lot,” said Evan Racine, CryoFILL project manager at NASA Glenn. “If we can produce and liquefy oxygen on the Moon or Mars, we can fuel landers on the surface where they land, reducing the amount of propellant needed to launch from Earth.” 

Through the Artemis program, NASA will send astronauts on increasingly ambitious missions to explore more of the Moon for scientific discovery, economic benefits, and to build a foundation for the first crewed missions to Mars.  

To sustain a long-term presence on the lunar surface, NASA aims to use the Moon’s resources to make products like propellant. Oxygen, a key ingredient of rocket fuel, can be extracted from water ice found in permanently shadowed regions of the Moon. This oxygen would be mined in a gas form, but to be used as a propellant, it must be cooled and condensed into liquid form.   

NASA Glenn experts are using a flight-like cryocooler, developed by Creare LLC through NASA’s Small Business Innovation Research program, to remove heat from the system that extracts the oxygen. This allows the oxygen to condense and remain at extremely cold temperatures below minus 300 degrees Fahrenheit. 

“We’re testing with flight-like hardware to see how oxygen liquefies and how the system responds to different scenarios,” said Wesley Johnson, CryoFILL lead engineer. “These are critical steps toward scaling up and automating future in-situ refueling.” 

Over the course of the next three months, NASA engineers will study how oxygen condenses under various conditions, use the data to validate temperature computer models, and demonstrate how NASA can scale the technology for larger applications. Once the test is complete, the data will inform designs of these technologies for use on the Moon, Mars, or other planetary surfaces. 

The Cryogenic Fluid Management Portfolio Project is a cross-agency team based at NASA Glenn and NASA’s Marshall Space Flight Center in Huntsville, Alabama. The cryogenic portfolio’s work is part of NASA’s Space Technology Mission Directorate and is comprised of more than 20 individual technology development activities. 

Two engineers stand beside a large stainless steel cylindrical chamber wrapped in reflective insulation, mounted inside a bright blue steel frame on wheels. One engineer points at the equipment while the other looks on. Pipe, valves, and metal structures are visible in the background.
Inside NASA Glenn Research Center’s Creek Road Cryogenics Complex, NASA engineers Jonathan Davis, left, and Wesley Johnson prepare to integrate a flight-like cryocooler developed by Creare LLC with the CryoFILL system on Sept. 24, 2025.
Credit: NASA/Jef Janis

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Heather Roe

Expanding the Human Factors Toolbox:  An Approach to Balancing Crew and Mission Design Parameters 

Expanding the Human Factors Toolbox:  An Approach to Balancing Crew and Mission Design Parameters 

This article is from the 2025 Technical Update.

The human factors TDT looks for and creates opportunities to influence design to leverage human strengths and to protect people and missions. The human factors team has experts with knowledge of human performance in all aspects of NASA missions as well as from other safety-critical industries. The goal is to ensure that science-based human factors knowledge and lessons learned are applied throughout the mission lifecycle. The strategy is to 1) modify existing and create new discipline tools that meet NASA’s needs and constraints, 2) build strategies to enhance the disciplines’ chances for success, 3) enhance simulation techniques to gain maximum information even when verification and validation  opportunities are limited, 4) develop new analysis methods for human performance in NASA mission contexts, and 5) reframe  understanding of human performance to emphasize the key role of human resilience in mission success. 

This article highlights a set of analytical models of crew workload, training, and expertise that can be used to aid decision makers in determining the size of a Mars crew adequate for crew safety and mission success. These tools are built on a Department of Defense (DoD) capability that has been used extensively to evaluate the success of specific designs. Unlike missions in low Earth orbit or even to the Moon, a crewed Mars mission will operate under extraordinary constraints, primarily a significant communication delay with Earth and prolonged communication blackout periods. This necessitates a radical rethinking of mission design, including the human elements of crew size, workload, expertise, and resilient performance.  

To address this gap, the NESC developed a systematic and quantitative methodology, along with an associated suite of modeling tools, to enable the development of an evidence-based trade space for guiding crew size decisions for human Mars missions. This work provides actionable analysis to programs and projects early in development, enabling simultaneous consideration of mission architecture, operational concepts, and the roles human will play throughout the mission. This analysis supports the development of mission designs that preserve and enable human resilient performance to ensure the success and safety of future Mars exploration. 

Historically, NASA’s human spaceflight programs have relied on real-time support from extensive ground control, composed of a collective intellect that acts as an extended crew to manage objectives and respond to anomalies. As depicted in Figure 1, the volume of ISS ground personnel highlights the vast support structure available for Earth-proximal missions. However, for Mars, communication delays of up to 22 minutes one-way and blackouts lasting up to three weeks during superior conjunctions will eliminate this real-time lifeline. This demands a new focus on the capabilities required of the onboard crew, who will face time-critical decisions and unforeseen failures with only their knowledge and onboard decision-support systems, often without pre-existing procedures. 

Current ground-support expertise for ISS missions
Current ground-support expertise for ISS missions

The NESC’s methodology fills a longstanding gap, as past Mars crew size determinations often lacked detailed quantitative analysis of crew tasking, workload, and expertise. Extending DoD methodologies for manpower determination, the NESC human factors trade space methodology offers a repeatable and data-driven means to assess whether a given crew complement possesses the capability to accomplish mission objectives and respond successfully to unforeseen failures that have potential loss of crew or loss of mission (LOC/LOM) consequences. The core process involves gathering Mars mission concepts and information, determining use cases to model, creating a trade space evaluation framework, conducting human performance modeling, and performing trade space analyses. This iterative approach, conceptually represented by the Mars Crew Size Decision Process (see Figure 2), allows for adaptation as technologies and mission assumptions evolve. 

Central to this methodology are four human performance models, each revealing critical insights into the human factors of Mars mission design. 

1. IV Operations for Planetary Surface EVA Model: This model examined the mental workload of intravehicular (IV) Mars crewmembers supporting a planetary surface extravehicular activity (EVA), simulating activities currently performed by Mission Control Center personnel for ISS EVAs. It predicted that during a Mars surface technical EVA conducted at the pace of an ISS EVA, the workload for an IV crewmember performing combined essential flight controller duties would be unacceptably high, indicating a severe negative impact on task performance. This finding underscores the necessity of reconsidering EVA pacing, task automation, or increasing IV support crew complement to ensure mission-critical EVAs are safely conducted independently of Earth-based support. 

2. Robotic Arm Assisted EVA Operator Model: This model assessed the mental workload of a crewmember operating a robotic arm (see Figure 3) in both manual and automated control modes on a Mars transit vehicle. The model results indicate that two crewmembers may be necessary to mitigate unacceptably high workload during manual robotic arm operations. Furthermore, consistent with the scientific literature, the model predicted that stressors like sleep debt increase mental workload and degrade performance, extending task completion times. This highlights the importance of accounting for crew well-being in crew-size determinations. 

3. Mars Transit Crew Model: This analysis focused on crew utilization and staffing requirements during a 9-month Mars transit mission, reallocating planned and unplanned tasks from ground control to the crew. The modeling, using ISS-equivalent task assumptions, predicted that more than six crewmembers (given average rates for unplanned events) would be needed to achieve the same number of work hours as a four-person ISS mission. This substantial increase emphasizes the critical impact of Earth-independence on daily crew workload and the imperative for adequate crew complement to manage ongoing responsibilities. 

4. Personnel, Expertise, and Training Model: Given the communication delay/blackout with Mars, paired with no rapid return-to-Earth options, NASA will need to rely on the expertise of the crew to respond to unforeseen failures. A custom model was developed to quantify the crew expertise required to meet mission objectives and respond to unforeseen events with LOC/LOM potential and short time-to-effect. Based on analysis of ISS historical data, the probability of at least one occurrence of such a failure during Mars transit is greater than 99%. A sensitivity analysis of the relationship between a successful crew response and LOC/LOM outcome was conducted for cases in which the crew gave a successful response 90%, 95%, 98%, and 99.985% of the time. The estimated likelihood of a LOC/LOM consequence for all but the most conservative of these cases is greater than 1%, which is considered in the “very high” (red) range, per the Human System Risk Board risk matrix. The likelihood of LOC/LOM consequences only drops below 0.1% (yellow) for a successful response rate of 99.985%. When unforeseen failures occur on a mission to Mars, it will be critical that the crew have the necessary level of expertise to accurately diagnose problems and restore critical functionality. The Personnel, Expertise, and Training model is designed to provide the agency with the capability to consider the trade space

The NESC’s proposed methodology to aid crew-size determinations.
Trade-space parameters are input into any of four models, whose output
characterizes the risk level associated with a given crew size.
Astronaut Anne McClain using the
Space Station Remote Manipulator System on ISS.

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Meagan Chappell

Webinar 3/25: NASA CSDA Vendor Focus – Satellogic

Webinar 3/25: NASA CSDA Vendor Focus – Satellogic

2 min read

Webinar 3/25: NASA CSDA Vendor Focus – Satellogic

Satellite image of coastal Louisiana showing sediment plumes entering the Gulf of Mexico near river outlets, with surrounding wetlands and agricultural land patterns along the coastline.
Satellogic satellite imagery of coastal Louisiana shows sediment plumes entering the Gulf of Mexico, illustrating how Earth observation data can monitor coastal and environmental dynamics.
Image courtesy of Satellogic

Join us on Wednesday, March 25 at 2:00 p.m. EDT (-04:00 UTC) to learn more about NASA Commercial Satellite Data Acquisition (CSDA) program vendor Satellogic and how to discover, access, and work with their high-resolution commercial datasets.

NASA’s Earth Science Division (ESD) established the Commercial Satellite Data Acquisition (CSDA) program to explore the potential of commercial satellite data in advancing the agency’s Earth science research and application objectives. The program aims to identify, assess, and acquire data from commercial providers, which may offer a cost-effective means of supplementing Earth observations collected by NASA, other U.S. Government agencies, and international collaborators.

Satellogic delivers high-resolution Earth observation imagery at scale through its vertically integrated satellite constellation. During this NASA CSDA program webinar, speakers will introduce Satellogic and its constellation of commercial Earth Observation satellites. Representatives will highlight current and future capabilities, including service-level monitoring at scale, and plans for global daily remapping. They will also discuss how these data products complement NASA Earth science data holdings for research and applications. In addition, presenters will address the services and tools available to data users, including how they can get expert assistance when using Satellogic datasets.  

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Last Updated
Mar 10, 2026

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