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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.

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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Thoughts Without Content are Empty, Intuitions Without Concepts are Blind - Determinism and Contingency Revisited

Was the emergence of life a predictable outcome of chemical evolution on earth? Could evolution produce life very different from ours? These are one of the oldest questions in the field of the origin of life that not only have broad philosophical implications but also impact how we approach the problem from the methodological standpoint. Framing the issue in terms of the dichotomy between contingency and determinism is not a fortunate because these two terms in their conventional meaning are neither mutually exclusive nor jointly exhaustive. Determinism, represented in natural sciences by Newtonian physics, relies on the assumption that every event is causally determined by a chain of previous events. In the context of the origin of life it means that once the initial conditions on the early earth have been specified further evolution follows inevitably. Considering uncertainties about conditions on the prebiotic earth, many plausible sets of initial conditions can be defined, each followed by a separate deterministic trajectory. This conventional understanding of determinism does not admit contingency. Further, it has no implications for evaluating how many sets of initial conditions lead to the emergence of life. It appears that a better framing of the problem is as follows: given plausible sets of initial conditions on the early earth how probable and broadly spread are evolutionary trajectories that lead to life? Instead of undertaking an impossible task of specifying microscopic initial conditions for all components of the system one uses a reduced representation of this system and specify only a small set of essential macroscopic parameters, values (or ranges of values) of which can be identified, inferred or estimated from experiment, theory or historical record. The following evolutionary trajectories are still governed by laws of physics and chemistry but become probabilistic and "contingency" is admitted as variations in other variables in the system. A similar reasoning is common in other fields of science, for example in statistical mechanics. Some trajectories lead to life, perhaps in different forms, whereas others do not. Of our true interest is the ratio of these two outcomes. The issue of determinism does not directly enter the picture. The debate about the likelihood of the emergence of life is quite old. One view holds that the origin of life is an event governed by chance, and the result of so many random events (contingencies) is unpredictable. This view was eloquently expressed by Monod. In his book "Chance or Necessity" he argued that life was a product of "nature's roulette." In an alternative view, expressed in particular by deDuve and Morowitz, the origin of life is considered a highly probable or even inevitable event (although its details need not be determined in every respect). Only in this sense the origin of life can be considered a "deterministic event".

Pohorille, Andrew↗
NASA NTRS2018

Sensor Integrated Metal Dielectric Filters for Solar-Blind Silicon Ultraviolet Detectors

A filter for electromagnetic radiation including one or more dielectric spacer regions and one or more reflective regions integrated on a semiconductor substrate, the semiconductor substrate including a semiconductor photodetector, such that the filter transmits ultraviolet radiation to the semiconductor photodetector, the ultraviolet radiation having a range of wavelengths, and the filter suppresses transmission of electromagnetic radiation, having wavelengths outside the range of wavelengths, to the semiconductor photodetector.

Hoenk, Michael E.↗
NASA NTRS2019

Blind Study Validating Parametric Costing Tools PRICE True Planning and SEER-H for NASA Science Missions

Two of the primary parametric costing tools used to estimate the development and production cost of future spacecraft hardware are PRICE True Planning - Space Missions Catalog by PRICE Systems, and SEER-H by Galorath. These are standard tools used by NASA and industry to estimate the cost of new aerospace hardware. However, no independent verification of the accuracy of these tools is publicly available. Both PRICE Systems and Galorath have completed internal validation studies of their parametric cost estimating tools; however, they only provided the results of the studies and did not detail the exact methods used to perform the validation. In the present study, cost estimators used PRICE True Planning and SEER-H to estimate the cost of twelve different past NASA science missions. The estimators were prevented from knowing the actual cost of the missions in an effort to minimize cognitive biases. In the present study, SEER had an average error of 23%, median error of -0.3%, with a standard deviation of 43%. PRICE had an average error of 52%, median error of 50%, and standard deviation of 45%. There were several factors independent of PRICE and SEER which may have affected the accuracy of the results in the present study including: uncertainty in the technical data used for the estimates, the methods used to estimate uncertainty in spacecraft component mass and numbers of prototypes, and the experience of the estimators.

Friz, Paul D.↗
NASA NTRS2018

Blind to Chemistry: Molecular Contaminant Films We Could Be Missing During Visual Inspections and the Potential Impact to System Performance

Throughout the assembly, integration and test process, molecular contamination levels of space mission hardware are monitored to meet system performance requirements. Qualitatively, reflective surfaces and witness mirrors are continuously inspected for the visible presence of molecular contaminant films. Quantitatively, periodic reflectance measurements of witness mirrors indicate changes of mirror reflectivity over time due to the accumulation of molecular contaminant films. However, both methods only consider the presence of a contaminant film and not the molecular composition. Additionally, there is a risk that hardware may appear to be “visibly clean” even with a molecular contaminant film present on critical surfaces. To address these issues, experiments were performed to quantify the maximum molecular contaminant film that could be missed in visual inspections on witness mirrors with five different contaminants present. The corresponding changes in mirror reflectivity were modeled using the program STACK to determine the impact to space mission hardware performance. The results of this study not only show the criticality in considering the chemical make-up of molecular contaminant films on system performance, but also the need to recognize and understand the limitations of traditional visual inspection techniques on detecting molecular contaminant films.

Seasly, Elaine↗
NASA NTRS2019

Blind Validation Study of Parametric Cost Estimation Tool SEER-H for NASA Space Missions

One of the primary parametric cost modeling tools used by NASA and the aerospace industry to estimate the development and production cost of future spacecraft hardware is SEER-H by Galorath. To date, no independent validation of this tool for cost estimation of space missions has been reported in the literature. In the present validation study, cost estimators used SEER-H to estimate the cost of twelve different past NASA science missions. The estimators were prevented from knowing the actual cost of the missions in an effort to minimize cognitive biases. The point estimates of SEER-H had an average error of 23%, median error of -0.3%, and a standard deviation of 43%. Nine of the twelve mission's actual costs fell within the 80% confidence interval of SEER's probabilistic estimates. Several factors independent of SEER that may have affected the accuracy of the results have been identified and are discussed; these include: uncertainty in the technical data used for the estimates, the methods used to estimate uncertainty in spacecraft component mass and numbers of prototypes, and the experience of the estimators.

SEER-H↗
NASA NTRS2018

Blind Study Validating Parametric Costing Tools PRICE TruePlanning and SEER-H for NASA Science Missions

Two of the primary parametric costing tools used to estimate the development and production cost of future spacecraft hardware are PRICE TruePlanning - Space Missions Catalog by PRICE Systems, and SEER-H by Galorath. These are standard tools used by NASA and industry to estimate the cost of new aerospace hardware. However, no independent verification of the accuracy of these tools is publicly available. Both PRICE Systems and Galorath have completed internal validation studies of their parametric cost estimating tools; however, they only provided the results of the studies and did not detail the exact methods used to perform the validation. In the present study, cost estimators used PRICE TruePlanning and SEER-H to estimate the cost of twelve different past NASA science missions. The estimators were prevented from knowing the actual cost of the missions in an effort to minimize cognitive biases. In the present study, SEER had an average error of 23%, median error of -0.3%, with a standard deviation of 43%. PRICE had an average error of 52%, median error of 50%, and standard deviation of 45%. There were several factors independent of PRICE and SEER which may have affected the accuracy of the results in the present study including: uncertainty in the technical data used for the estimates, the methods used to estimate uncertainty in spacecraft component mass and numbers of prototypes, and the experience of the estimators.

Paul D Friz↗
NASA NTRSDate not supplied

Flying Blind: Keeping aircraft safe without a pilot on board.

The unmanned aircraft market is one of the fastest growing sectors in the world today, poised to become a billion dollar industry in the next several years. This explosive growth in unmanned aircraft, both small and large, brings an increased risk of these vehicles interfering with current aircraft, or harming unsuspecting bystanders. This talk will discuss some of the research NASA is doing to keep the airspace safe, while allowing drone pilots the freedom to fly. The discussion will center on two NASA-developed systems: Safeguard, a platform-independent geofence; and DAIDALUS, a software suite for detect and avoid. In addition to describing what the systems are supposed to do, we'll also discuss how NASA uses formal methods to provide assurance that they actually do as intended.

unmanned aircraft↗
NASA NTRS2023

A Blind Convolutional Deep Autoencoder for Spectral Unmixing of Hyperspectral Images Over Waterbodies

Harmful algal blooms have dangerous repercussions for biodiversity, the ecosystem, and public health. Automatic identification based on remote sensing hyperspectral image analysis provides a valuable mechanism for extracting the spectral signatures of harmful algal blooms and their respective percentage in a region of interest. This paper proposes a new model called a non-symmetrical autoencoder for spectral unmixing to perform endmember extraction and fractional abundance estimation. The model is assessed in benchmark datasets, such as Jasper Ridge and Samson. Additionally, a case study of the HSI2 image acquired by NASA over Lake Erie in 2017 is conducted for extracting optical water types. The results using the proposed model for the benchmark datasets improve unmixing performance, as indicated by the spectral angle distance compared to five baseline algorithms. Improved results were obtained for various metrics. In the Samson dataset, the proposed model outperformed other methods for water (0.060) and soil (0.025) endmember extraction. Moreover, the proposed method exhibited superior performance in terms of mean spectral angle distance compared to the other five baseline algorithms. The non-symmetrical autoencoder for the spectral unmixing approach achieved better results for abundance map estimation, with a root mean square error of 0.091 for water and 0.187 for soil, compared to the ground truth. For the Jasper Ridge dataset, the non-symmetrical autoencoder for the spectral unmixing model excelled in the tree (0.039) and road (0.068) endmember extraction and also demonstrated improved results for water abundance maps (0.1121). The proposed model can identify the presence of chlorophyll-a in waterbodies. Chlorophyll-a is an essential indicator of the presence of the different concentrations of macrophytes and cyanobacteria. The non-symmetrical autoencoder for spectral unmixing achieves a value of 0.307 for the spectral angle distance metric compared to a reference ground truth spectral signature of chlorophyll-a. The source code for the proposed model, as implemented in this manuscript, can be found at https://github.com/EstefaniaAlfaro/autoencoder_owt_spectral.git.

hyperspectral imaging↗