Abstract
This paper develops a novel approach to modeling and predicting advancement in spacecraft technology for deep space exploration. As spacecraft lifetimes increase, ever more elaborate missions and even quasi-permanent bases become more and more possible. We use the NASA (National Aeronautical and Space Agency) yearly budget along with the time variable to model their relationship with spacecraft lifespans and compare the level of fit of our model with an exponential (generalized Moore's law) model. The results indicate that our model provides a better curve fit, suggesting the usefulness of NASA’s budget in predicting the progression of space exploration technology. Additionally, the evidence that the NASA budget has a statistically significant impact on spacecraft lifespans suggests that the government could increase future funding of NASA to foster quicker technological improvement in space exploration technology.
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Notes
- 1.
Data was compiled into a Google Sheet file that can be viewed and/or acquired by accessing the following web address: https://docs.google.com/spreadsheets/d/1fpYB3pMHcq77vQPMvpkA-sWFPzr2zlcWnEsDyawVfyI/edit#gid=846789546.
References
Bailey, A., Bui, Q.M., Farmer, J., Margolis, R., Ramesh, R.: Forecasting technological innovation. In: ARCS Workshops (ARCS), pp. 1–6 (2012)
Ball, P.: Moore's law found to apply to evolution of technologies beyond transistors. Scientific American (2013). https://www.scientificamerican.com/article/moores-law-found-to-apply-beyond-transistors
Bardi, U.: John Glenn (1921–2016): the end of an era. Cassandra's Legacy (2016). https://cassandralegacy.blogspot.com/2016/12/john-glenn-1921-2016-end-of-era.html
Benson, C.L., Magee, C.L.: On improvement rates for renewable energy technologies: solar PV, wind turbines, capacitors, and batteries. Renew. Energy 68, 745–751 (2014)
Benson, C.L., Magee, C.L.: Quantitative determination of technological improvement from patent data. PlosS ONE 10(4), e0121635 (2015). https://doi.org/10.1371/journal.pone.0121635
Berleant, D., Kodali, V., Segall, R., Aboudja, H., Howell, M.: Moore's law, Wright's law, and the countdown to exponential space. The Space Review (2019). https://www.thespacereview.com/article/3632/1
Dosi, G.: Technological paradigms and technological trajectories. Res. Policy 11(3), 147–162 (1982)
Elliott, G.: Figure 4: the population of space. Nefarious Plots. http://www.nefariousplots.com/figures/4, Accessed 15 Apr 2021
Farmer, J.D., Lafond, F.: How predictable is technological progress? Res. Policy 45(3), 647–665 (2016)
Hall, C., Berleant, D., Segall, R., Lu, S.: Steps toward quantifying advancement in space exploration. In: Proceedings of 20th World Multi-Conference on Systemics, Cybernetics and Informatics, WMSCI 2017, Orlando, FL, 8–11 July 2017, vol. II, pp. 106–112 (2017)
Hicks, K.: Astronomy: It’s sad that human space exploration has stalled. Columbus Dispatch (2015). https://www.dispatch.com/article/20151106/NEWS/311069676
Howell, M., et al.: Trends in technology development in the US and USSR during the Space Race. The Space Review (2019). https://www.thespacereview.com/article/3840/1
Howell, M., Kodali, V., Segall, R., Aboudja, H., Berleant, D.: Moore’s law and space exploration: new insights and next steps. J. Arkansas Acad. Sci. 73, 13–17 (2019)
Kodali, V., Duggirala, R., Segall, R., Aboudja, H., Berleant, D.: Travel to extraterrestrial destinations over time: some exploratory analyses of mission data. J. Arkansas Acad. Sci. 72, 58–66 (2018)
Koh, H., Magee, C.L.: A functional approach for studying technological progress: application to information technology. Technol. Forecast. Soc. Chang. 73, 1061–1083 (2006)
Koh, H., Magee, C.L.: A functional approach for studying technological progress: extension to energy technology. Technol. Forecast. Soc. Chang. 75, 735–758 (2008)
Lafond, F., et al.: How well do experience curves predict technological progress? a method for making distributional forecasts. Technol. Forecast. Soc. Chang. 128, 104–117 (2018)
MacDonald, A., Schrattenholzer, L.: Learning rates for energy technologies. Energy Policy 29(4), 255–261 (2001)
Mack, C.A.: Fifty years of Moore’s law. IEEE Trans. Semicond. Manuf. 24(2), 202–207 (2001)
Magee, C.L., Basnet, S., Funk, J.L., Benson, C.L.: Quantitative empirical trends in technical performance. Technol. Forecast. Soc. Chang. 104, 237–246 (2016)
Mollick, E.R.: Establishing Moore’s law. IEEE Ann. Hist. Comput. 28, 62–75 (2006)
Moore, G.E.: Cramming more components onto integrated circuits. Electronics 38(8), 114–117 (1965)
Nagy, B., Farmer, J.D., Bui, Q.M., Trancik, J.E.: Statistical basis for predicting technological progress. PLoS One 8(2), e52669 (2013)
NASA Jet Propulsion Laboratory: Did you know? https://voyager.jpl.nasa.gov/mission/did-you-know, Accessed 28 Oct 2020
Nielsen, J.: Nielsen’s law of internet bandwidth. http://www.nngroup.com/articles/law-of-bandwidth, Accessed 27 Sept 2019
Singh, A., Triulzi, G., Magee, C.L.: Technological improvement rate estimates for all technologies: use of patent data and an extended domain description (2020). arXiv:2004.13919 [econ.GN]
Singularity Symposium: What is Moore’s law? http://www.singularitysymposium.com/moores-law.html, Accessed 15 Apr 2021
SpacePunx: Population of space over time. https://en.wikipedia.org/wiki/File:Space_Population.png, Accessed 8 Oct 2020
Specter, M.: A life of its own: Where will synthetic biology lead us? The New Yorker (2009). https://www.newyorker.com/magazine/2009/09/28/a-life-of-its-own
Sood, A., James, G.M., Tellis, G.J., Zhu, J.: Predicting the path of technological innovation: SAW vs. Moore, Bass, Gompertz, and Kryder. Mark. Sci. 31(6), 964–979 (2012)
Trancik, J.E., Cross-Call, D.: Energy technologies evaluated against climate targets using a cost and carbon trade-off curve. Environ. Sci. Technol. 47, 6673–6680 (2013)
Triulzi, G., Alstott, J., Magee, C. L.: Estimating technology performance improvement rates by mining patent data. SSRN (2018). https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2987588
Walter, C.: Kryder’s law. Sci. Am. 293(2), 32–33 (2005)
Wikipedia: Budget of NASA. https://en.wikipedia.org/wiki/Budget_of_NASA, Accessed 30 Oct 2020
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Tsai, PH., Berleant, D., Segall, R.S., Aboudja, H., Batthula, V.J.R., Howell, M. (2022). Spacecraft for Deep Space Exploration: Combining Time and Budget to Model the Trend in Lifespan. In: Arai, K. (eds) Proceedings of the Future Technologies Conference (FTC) 2021, Volume 3. FTC 2021. Lecture Notes in Networks and Systems, vol 360. Springer, Cham. https://doi.org/10.1007/978-3-030-89912-7_25
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