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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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NASA NTRS2025

A Minority Report Submitted as an Addendum to the Report of the Mars 2020 Organic Contamination Panel

This Minority Report (MR) presents seven findings in addition to or contrary to the main OCP report: 1. Contamination control for the Mars 2020 cache must be strict. Mars’ surface is known to be organics-poor from laboratory studies, Mars meteorite analyses, and from four previous NASA missions. It is imperative that contamination control measures are enacted that enable reliable and robust detection of potential biomarker compounds at the ppb level. 2. Since Mars 2020 is a sample return mission and analyses of samples in the returnable cache are expected to occur after return to Earth, positive controls are not recommended for flight on Mars 2020 unless a compelling case can be made for their use. 3. The findings of previous panels dedicated to organic compound analysis in Martian samples (OCSSG, ND-SAG, SDT) recommend TOC limits between 10-40 ppb. The MR finds that the lower limit of 10 ppb is recommended and that insufficient justification is given by the OCP Panel Report (PR) to raise the TOC limit to 40 ppb. 4. Analytical capability is sufficiently advanced that analytical capability is an irrelevant consideration with respect to differentiating between 10 and 40 ppb TOC. 5. Perceived contamination control challenges are an irrelevant consideration for raising the TOC contamination limit from 10 to 40 ppb since those challenges, and the procedures to ameliorate them, will exist regardless of whether the limit is 10 or 40 ppb. 6. The “dilution cleaning” method has not been adequately proven for utilization on the Mars 2020 mission. Shortcomings have been identified in terms of peer review, method verification, analytical and testing approach, application to space flight hardware, and performance under Martian conditions. The method should be revisited and independently tested using statistically and analytically robust methods, and scrutinized in a rigorous peer review process. 7. The Mars 2020 mission claims considerable heritage from the Mars Science Laboratory (MSL) mission, but MSL contamination control efforts contain significant errors and implementation discrepancies that would imperil the Mars 2020 caching mission were they repeated. A standing contamination control panel should be formed to provide independent oversight for the Mars 2020 mission.

Mars Sample Return↗

NASA NTRS1989

Transmission overhaul and replacement predictions using Weibull and renewel theory

A method to estimate the frequency of transmission overhauls is presented. This method is based on the two-parameter Weibull statistical distribution for component life. A second method is presented to estimate the number of replacement components needed to support the transmission overhaul pattern. The second method is based on renewal theory. Confidence statistics are applied with both methods to improve the statistical estimate of sample behavior. A transmission example is also presented to illustrate the use of the methods. Transmission overhaul frequency and component replacement calculations are included in the example.

Savage, M.↗

NASA NTRS1989

Transmission overhaul and replacement predictions using Weibull and renewal theory

Savage, M.↗

NASA NTRSDate not supplied

Estimating Bidirectional Reflectance and Monitoring Stability of SNPP-VIIRS Reflective Solar Bands Using A Deep Neural Network

The NASA Clouds and the Earth's Radiant Energy System project provides the scientific community with observed top-of-atmosphere shortwave and longwave fluxes for climate monitoring and climate model validation. To provide consistent VIIRS cloud retrievals, the CERES Imager and Geostationary Calibration Group (IGCG) must understand and quantify the stability of the VIIRS instruments. To achieve this, the IGCG utilizes tropical deep convective clouds (DCCs) as invariant targets. Proper seasonal characterization of the DCC bidirectional reflectance distribution function (BRDF) is key to the success of DCC-based calibration methods, particularly for shortwave infrared (SWIR) bands. This article proposes the use of a deep neural network (DNN) to characterize VIIRS solar reflective band BRDF reflectance, with which individual channel trends are isolated by manipulating the DNN time input. Initial results show that the DNN method can extract statistically significant SNPP-VIIRS band trends, using only SNPP-VIIRS inputs, that are correlative to and match the magnitude of significant trends determined using methods that rely on an external angular distribution model. It may be possible to apply this approach to actively monitor the stability of new instruments without the need for predetermined seasonal BRDF corrections.

Benjamin Scarino↗

NASA NTRS1985

Evaluation of fault-tolerant system performance by approximate techniques

An approximate method for calculating the statistics of the performance of a fault-tolerant system is developed. An approximate method is necessary because the statistical model of the system behavior is large-scale and the time horizon of interest encompasses many cycles of the Redundancy Management logic. In the development, a compact representation of the necessary information called the v-transform is introduced and discussed. Based upon this representation, an approximation that leads to a very efficient computational procedure is suggested and numerically analyzed. A very brief discussion of other related work is also presented.

Walker, B. K.↗

NASA NTRS1988

Detection of road boundary

Several researchers have proposed and implemented various systems pertaining to the development of autonomous land vehicles (ALVs). One fundamental problem associated with the navigation of an ALV is the ability to efficiently extract the boundaries of the pathway that need to be navigated. In this paper a method is presented that will determine the road boundaries in one pass using a limited search area in the input image. The method employs the statistical information regarding the gray levels present in the images along with geometrical constraints concerning the road. Some examples are given to demonstrate the efficacy of the method.

Sowers, James P.↗

NASA NTRSDate not supplied

Evaluation of Correction Methods for NASA GeneLab Transcriptomic Datasets

Conducting space biology experiments aboard the International Space Station, particularly those utilizing complex model organisms like mice, is expensive and difficult due to limited crew availability, hardware, and space. As a result, sample numbers from these studies are low, reducing the statistical power of any one experiment. Aggregating spaceflight datasets serves as a method to increase sample numbers, allowing for novel insights through bioinformatic analysis of ‘omics data from merged datasets. However, aggregating datasets can introduce unwanted variation including 1) differences in sample handling, processing, and sequencing platforms between datasets (technical variation) as well as 2) differences in experimental design between datasets. In the present study, NASA GeneLab-hosted RNAseq datasets from mouse liver tissues were used to evaluate several statistical methods to correct for this unwanted variation through two approaches, reference-based and standard. The following correction algorithms were applied with (reference-based) and/or without (standard) considering Universal Mouse RNA Reference samples: ComBat and ComBat_seq from the SVA package, median polish, empirical Bayes, and ANOVA-based algorithms from the MBatch package, and negative binomial regression normalization in the DESeq2 package. For each approach, after the correction algorithm was applied, differential gene expression (DGE) analysis of flight and ground control samples was performed with the combined data. The robustness of each tool was evaluated using BatchQC to determine statistical differences between datasets before and after correction, Principal Component Analysis to evaluate global gene expression in samples before and after correction, and by comparing DGE analysis of individual datasets and combined datasets before and after correction. The results showed that the reference-based approach introduced several additional (and likely artificial) DEGs when compared with the respective standard approach. Of the methods tested, standard ComBat and DESeq2 were identified as the most robust correction methods for combining spaceflight mouse liver RNAseq datasets hosted on GeneLab.

GeneLab↗

NASA NTRSDate not supplied

Expedited Model Building Method for Rocket Nozzle Side Loading

Statistical analysis of test data is currently the preferred method of creating models for uncharacterized side loading in rocket nozzles. However, statistical analysis requires multiple data sets to be reliable; getting these sets requires building and testing multiple rocket motors, which is not feasible given the incredible time and cost required to do so. By using a combination of geometry, simplified finite element analysis (FEA) analogs, and algebra we can create a limited predictive model from only one test data set. Once created, the model requires only the input from one strain gauge located at each yaw and pitch attachment bracket for the actuation system. This process is not computationally intensive, therefore saving an abundance of time and budget over using full 3D FEA models to develop a similar predictive model. To develop the model, conversion factors between the strain at the gauge locations and corresponding actuator load is derived from the data. These conversion factors are used to create a “conversion ellipse” that bounds the constitutive properties of the nozzle as one lumped factor. Using a 2D cross-sectional analog of the nozzle exit plane, we create a function that allows us to determine the azimuthal location of the unexpected load based on the ratio between yaw and pitch strain readings. Combining this with the “conversion ellipse” yields a function that given the strain reading outputs an induced actuator load, regardless of the azimuthal location of the unexpected load. As previously mentioned, this predictive model is limited in its application as there is inaccuracy introduced by the use of data by only one test as well as simplifying assumptions. This approach makes a useful tool to quickly determine whether uncharacterized actuator loading events can damage actuation systems or induce loading that exceeds design limits.

Seetha A Kolli↗

NASA NTRSDate not supplied

Evaluation of Correction Methods for NASA GeneLab Transcriptomic Datasets

Conducting space biology experiments aboard the International Space Station, particularly those utilizing complex model organisms like mice, is expensive and difficult due to limited crew availability, hardware, and space. As a result, sample numbers from these studies are low, reducing the statistical power of any one experiment. Aggregating spaceflight datasets serves as a method to increase sample numbers, allowing for novel insights through bioinformatic analysis of ‘omics data from merged datasets. However, aggregating datasets can introduce unwanted variation including 1) differences in sample handling, processing, and sequencing platforms between datasets (technical variation) as well as 2) differences in experimental design between datasets such as sex or age of the model organism used. In the present study, NASA GeneLab-hosted RNAseq datasets from rodent liver tissues were used to evaluate several statistical methods to correct for this unwanted variation through two approaches, reference-based and standard. The following correction algorithms were applied with (reference-based) and/or without (standard) considering Universal Mouse RNA Reference samples: ComBat and ComBat_seq from the SVA package, median polish, empirical Bayes, and ANOVA-based algorithms from the MBatch package, and negative binomial regression normalization in the DESeq2 package. For each approach, after the correction algorithm was applied, differential gene expression (DGE) analysis of flight and ground control samples was performed with the combined data. The robustness of each tool was evaluated using BatchQC, to determine statistical differences between datasets before and after correction, Principal Component Analysis, to evaluate global gene expression in samples before and after correction, and by comparing DGE analysis of individual datasets and combined datasets before and after correction. The results showed that the reference-based approach introduced several additional (and likely artificial) DEGs when compared with the standard approach. Thus, the most robust standard correction will be implemented in the GeneLab Visualization 2.0 platform when datasets are combined.

GeneLab, RNA-seq, Batch Correction↗

NASA NTRS2004

An Analysis Methodology for the Gamma-ray Large Area Space Telescope

The Large Area Telescope (LAT) instrument on the Gamma Ray Large Area Space Telescope (GLAST) has been designed to detect high-energy gamma rays and determine their direction of incidence and energy. We propose a reconstruction algorithm based on recent advances in statistical methodology. This method, alternative to the standard event analysis inherited from high energy collider physics experiments, incorporates more accurately the physical processes occurring in the detector, and makes full use of the statistical information available. It could thus provide a better estimate of the direction and energy of the primary photon.

Morris, Robin D.↗

NASA NTRS1977

Prediction of slant path rain attenuation statistics at various locations

The paper describes a method for predicting slant path attenuation statistics at arbitrary locations for variable frequencies and path elevation angles. The method involves the use of median reflectivity factor-height profiles measured with radar as well as the use of long-term point rain rate data and assumed or measured drop size distributions. The attenuation coefficient due to cloud liquid water in the presence of rain is also considered. Absolute probability fade distributions are compared for eight cases: Maryland (15 GHz), Texas (30 GHz), Slough, England (19 and 37 GHz), Fayetteville, North Carolina (13 and 18 GHz), and Cambridge, Massachusetts (13 and 18 GHz).

Goldhirsh, J.↗

NASA NTRS1974

Statistical mechanics of 'negative temperature' states

Consideration of the dynamics of a two-dimensional guiding center plasma, recently shown by Taylor and McNamara (1971) to be identical to the dynamics of the discrete vortex model of Onsager (1949). A semirigorous application of the methods of equilibrium statistical mechanics to the guiding center plasma (or equivalently, the line vortex system) is presented. An adaptation of the apparatus of the theory of probability is attempted, in the form given by Khinchin (1949) to obtain ensemble-average predictions for the states of the guiding center plasma. Interest focuses primarily on the regime in which the interaction energy is high enough to be above the Onsager 'negative temperature' threshold.

Montgomery, D.↗

NASA NTRS1986

Pattern recognition of satellite cloud imagery for improved weather prediction

The major accomplishment was the successful development of a method for extracting time derivative information from geostationary meteorological satellite imagery. This research is a proof-of-concept study which demonstrates the feasibility of using pattern recognition techniques and a statistical cloud classification method to estimate time rate of change of large-scale meteorological fields from remote sensing data. The cloud classification methodology is based on typical shape function analysis of parameter sets characterizing the cloud fields. The three specific technical objectives, all of which were successfully achieved, are as follows: develop and test a cloud classification technique based on pattern recognition methods, suitable for the analysis of visible and infrared geostationary satellite VISSR imagery; develop and test a methodology for intercomparing successive images using the cloud classification technique, so as to obtain estimates of the time rate of change of meteorological fields; and implement this technique in a testbed system incorporating an interactive graphics terminal to determine the feasibility of extracting time derivative information suitable for comparison with numerical weather prediction products.

Gautier, Catherine↗

NASA NTRS1984

Time series modeling of human operator dynamics in manual control tasks

A time-series technique is presented for identifying the dynamic characteristics of the human operator in manual control tasks from relatively short records of experimental data. Control of system excitation signals used in the identification is not required. The approach is a multi-channel identification technique for modeling multi-input/multi-output situations. The method presented includes statistical tests for validity, is designed for digital computation, and yields estimates for the frequency responses of the human operator. A comprehensive relative power analysis may also be performed for validated models. This method is applied to several sets of experimental data; the results are discussed and shown to compare favorably with previous research findings. New results are also presented for a multi-input task that has not been previously modeled to demonstrate the strengths of the method.

Biezad, D. J.↗

NASA NTRS1984

Time Series Modeling of Human Operator Dynamics in Manual Control Tasks

A time-series technique is presented for identifying the dynamic characteristics of the human operator in manual control tasks from relatively short records of experimental data. Control of system excitation signals used in the identification is not required. The approach is a multi-channel identification technique for modeling multi-input/multi-output situations. The method presented includes statistical tests for validity, is designed for digital computation, and yields estimates for the frequency response of the human operator. A comprehensive relative power analysis may also be performed for validated models. This method is applied to several sets of experimental data; the results are discussed and shown to compare favorably with previous research findings. New results are also presented for a multi-input task that was previously modeled to demonstrate the strengths of the method.

Biezad, D. J.↗

NASA NTRSDate not supplied

Validation Testing and Statistical Analysis of the Rotary Tumbler Fabric Abrasion Method

The Artemis space suit glove environmental protection garment (EPG) will be the first line of protection used to shield the crewmember’s hands from the environments encountered during extravehicular activity (EVA). As the Artemis missions will include more extreme environments than those experienced on the International Space Station, development, verification, and validation of gloves requires the development of new test methods. A previous paper focused on the development of a test procedure to characterize lunar EVA glove fabrics using ASTM standardized test methods and the design and validation of a new standardized test procedure for comparing abrasion resistance between fabrics using a dust and rock filled rotary tumbler. Preliminary results of testing were presented in that paper. This paper reports on the validation testing and statistical analysis of the newly developed tumbler abrasion test method.

Robert J Jones↗

NASA NTRS2020

Development of TID Hardness Assurance Methodologies to Capitalize on Statistical Radiation Environment Models

We develop methods for bounding part-to-part variation in TID data. When used in conjunction with statistical radiation environment models, these methods allow development of RHA that deliver estimated piece part reliability for any desired confidence level, moving beyond risk avoidance methodologies based on radiation design margin. Two methods are developed, and their results compared for realistic data.

Total Ionizing Dose↗

NASA NTRS2020

Development of TID Hardness Assurance Methodologies to Capitalize on Statistical Radiation Environment Models

Total ionizing dose↗