WIRED38%

The SpaceX Falcon Lunar Crash Is a Warning for Moon Bases 31%

By Javier Carbajal28%

8/3/2026, 12:58:23 PM

BS Summary: This article contains 25 faulty reasoning types, including Optimism Bias, Pessimism Bias, and Negativity Bias, with Confirmation Bias as the most egregious example at 12.2% saturation with 75 hits. Analysis detected 1,034 faulty-reasoning hits from 615 analyzed words, generating a BS Score of 33.3% and a BS Rank of 31% (20,962 of 30,190 articles). This article is better (less manipulative) than 69.40% of the article peer group.

The rocket set for moon impact is the upper stage of a Falcon 9 that transported a pair of lunar landers. 
While the landers successfully reached the surface, the rocket was left adrift since it did not have enough fuel to return to Earth or enter a stable orbit. 
Weighing 4 metric tons, the rocket is expected to strike the lunar surface at a speed of approximately 5,400 mph—about seven times the speed of sound. 
Without an atmosphere to slow the projectile down, the impact will cause an explosion equivalent to 3 metric tons of TNT, leaving a crater that’s projected to be up to 27 meters in diameter and 5 meters deep. 
The upper stage is expected to hit the surface around 6:34 am UTC on Wednesday, likely making impact near Einstein Crater on the western edge of the moon’s near side. 
The Americas will have the best view of this impact. 
While it won’t be visible to the naked eye, viewers should be able to spot the debris plume through a good telescope for a few minutes. 
A lunar crash landing visible from Earth will be a spectacle, one that raises concerns about the future of the moon. 
Multiple countries are planning uncrewed lunar missions, which could clutter the area around the moon. 
This SpaceX rocket won’t be the first to accidentally crash into the moon. 
In March 2022, a Chinese Long March 3C rocket also struck the lunar surface and left a crater that’s 29 meters wide. 
China and the US are also pushing to build bases on the surface in the coming decades. 
Bill Gray, the creator of the Project Pluto initiative to develop software and tools to track the orbits of asteroids, comets, and artificial satellites, was the first to calculate the trajectory of the impending Falcon 9 crash. 
He was also part of a team that worked on a preprint study released last month detailing the collision. 
The crash landing is ”an opportunity to test pipelines for measuring flash properties to locate impact events seismically, and to better understand the multi-modal hazards posed to future lunar infrastructure and astronauts from space debris impacting the Moon,” the study states. 
Although building a moon research center capable of supporting a sustained human presence will take at least a decade, NASA’s missions to construct the first facilities are expected to launch in the coming years as part of the Artemis program. 
"These sorts of things are going to happen more and more often. 
And as we have more astronauts on the lunar surface, more lunar bases habitats, for example, we need to understand how much of a risk these impact events actually pose," Benjamin Fernando, a researcher at Los Alamos National Laboratory in New Mexico and coauthor of the preprint study, tells ABC News. 
The risk posed by space debris is part of a growing list of hazards that cast doubt on the safety of any long-term project on the moon. 
In addition to the potential for space junk to wreak havoc on the lunar surface, natural events such as meteorite strikes also threaten any future activities. 
But with any potential lunar bases still a decade or more away, there’s ample time for researchers to look at the hazards and plan for them. 
“This is an ideal way of studying both the direct risks, the risk of being hit by debris or being blinded by a flash of light, but also the indirect risk, the risk of being hit by a cloud of ejected material and having that disrupt or interfere with spacecraft functions in lunar orbit as well,” Fernando says. 
Article reasoning-pattern comparisonThis article: 12.2%Javier Carbajal: 1.4%WIRED: 1.7%Confirmation Bias12.2%This article: 6.2%Javier Carbajal: 0.7%WIRED: 0.6%Anchoring Bias6.2%This article: 9.4%Javier Carbajal: 2.2%WIRED: 2.7%Availability Heuristic9.4%This article: 0.0%Javier Carbajal: 0.0%WIRED: 0.7%Representativeness Heuristic0.0%This article: 3.6%Javier Carbajal: 0.2%WIRED: 0.8%Hindsight Bias3.6%This article: 9.4%Javier Carbajal: 1.5%WIRED: 1.2%Overconfidence Bias9.4%This article: 8.5%Javier Carbajal: 4.0%WIRED: 3.4%Framing Effect8.5%This article: 8.3%Javier Carbajal: 0.8%WIRED: 0.4%Loss Aversion8.3%This article: 0.0%Javier Carbajal: 0.6%WIRED: 0.4%Status Quo Bias0.0%This article: 0.0%Javier Carbajal: 0.0%WIRED: 0.2%Sunk Cost Effect0.0%This article: 10.7%Javier Carbajal: 2.5%WIRED: 2.0%Optimism Bias10.7%This article: 10.6%Javier Carbajal: 2.3%WIRED: 1.2%Pessimism Bias10.6%This article: 9.6%Javier Carbajal: 4.2%WIRED: 5.2%Negativity Bias9.6%This article: 0.0%Javier Carbajal: 2.1%WIRED: 1.0%Self-Serving Bias0.0%This article: 8.3%Javier Carbajal: 0.6%WIRED: 0.7%Fundamental Attribution Error8.3%This article: 0.0%Javier Carbajal: 0.0%WIRED: 0.2%Actor-Observer Bias0.0%This article: 0.0%Javier Carbajal: 0.0%WIRED: 0.8%In-Group Bias0.0%This article: 0.0%Javier Carbajal: 0.0%WIRED: 0.2%Out-Group Homogeneity Bias0.0%This article: 3.1%Javier Carbajal: 0.6%WIRED: 1.6%Halo Effect3.1%This article: 0.0%Javier Carbajal: 0.0%WIRED: 0.0%Horn Effect0.0%This article: 0.0%Javier Carbajal: 0.0%WIRED: 0.0%Dunning-Kruger Effect0.0%This article: 2.1%Javier Carbajal: 0.7%WIRED: 0.9%Recency Bias2.1%This article: 6.0%Javier Carbajal: 0.4%WIRED: 0.2%Primacy Effect6.0%This article: 0.0%Javier Carbajal: 0.0%WIRED: 0.1%Blind-Spot Bias0.0%This article: 0.0%Javier Carbajal: 0.0%WIRED: 0.4%Ad Hominem0.0%This article: 0.0%Javier Carbajal: 0.0%WIRED: 0.2%Straw Man0.0%This article: 6.0%Javier Carbajal: 2.1%WIRED: 2.6%Appeal to Authority6.0%This article: 8.3%Javier Carbajal: 0.6%WIRED: 1.0%False Dilemma8.3%This article: 0.0%Javier Carbajal: 1.1%WIRED: 0.5%Slippery Slope0.0%This article: 0.0%Javier Carbajal: 0.5%WIRED: 0.1%Circular Reasoning0.0%This article: 4.4%Javier Carbajal: 1.3%WIRED: 3.9%Hasty Generalization4.4%This article: 0.0%Javier Carbajal: 0.0%WIRED: 0.1%Red Herring0.0%This article: 0.0%Javier Carbajal: 0.0%WIRED: 0.4%Bandwagon0.0%This article: 7.8%Javier Carbajal: 3.6%WIRED: 2.5%Appeal to Emotion7.8%This article: 0.0%Javier Carbajal: 0.2%WIRED: 0.3%Begging the Question0.0%This article: 3.4%Javier Carbajal: 0.5%WIRED: 2.0%Post Hoc (False Cause)3.4%This article: 0.0%Javier Carbajal: 0.0%WIRED: 0.1%Tu Quoque0.0%This article: 4.2%Javier Carbajal: 1.1%WIRED: 0.3%Burden of Proof4.2%This article: 0.0%Javier Carbajal: 0.0%WIRED: 0.1%Appeal to Nature0.0%This article: 0.0%Javier Carbajal: 0.1%WIRED: 0.2%Composition/Division0.0%This article: 0.0%Javier Carbajal: 0.0%WIRED: 2.9%Anecdotal0.0%This article: 0.0%Javier Carbajal: 0.0%WIRED: 0.0%No True Scotsman0.0%This article: 6.2%Javier Carbajal: 0.9%WIRED: 1.1%Ambiguity (Equivocation)6.2%This article: 0.0%Javier Carbajal: 0.0%WIRED: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Javier Carbajal: 0.0%WIRED: 0.1%Middle Ground0.0%This article: 0.0%Javier Carbajal: 0.2%WIRED: 0.1%Personal Incredulity0.0%This article: 0.0%Javier Carbajal: 0.2%WIRED: 0.1%Special Pleading0.0%This article: 0.0%Javier Carbajal: 0.0%WIRED: 0.1%Genetic Fallacy0.0%This article: 6.7%Javier Carbajal: 1.7%WIRED: 1.0%Unattributed Quote6.7%This article: 2.0%Javier Carbajal: 0.6%WIRED: 0.5%Quote-first Misdirection2.0%This article: 1.8%Javier Carbajal: 2.6%WIRED: 3.2%Biased Writer Voice1.8%This article: 9.4%Javier Carbajal: 2.3%WIRED: 0.7%Indoctrination9.4%This article: 0.0%Javier Carbajal: 0.0%WIRED: 0.3%Politically Left Leaning Bias0.0%This article: 0.0%Javier Carbajal: 0.0%WIRED: 0.1%Politically Right Leaning Bias0.0%This article: 0.0%Javier Carbajal: 1.4%WIRED: 1.6%Attempt to Sell a Product or S…0.0%

615 words analyzed.

Speakers

1speaker20%attributed speech494writer words
Selected voice

Benjamin Fernando

100%flagged-word coverage
121 attributed words100% of attributed speech85% writer coverage
0%25.0%50.0%Indoctrination+47.9 ptsWriter: 0.0%Benjamin Fernando: 47.9%47.9%Quote-first Misdirection+9.9 ptsWriter: 0.0%Benjamin Fernando: 9.9%9.9%Unattributed Quote-8.3 ptsWriter: 8.3%Benjamin Fernando: 0.0%0.0%Biased Writer Voice-2.2 ptsWriter: 2.2%Benjamin Fernando: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.