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At least 55 records · Page 3

Sampling Mars: Analytical requirements and work to do in advance

Sending a mission to Mars to collect samples and return them to the Earth for analysis is without doubt one of the most exciting and important tasks for planetary science in the near future. Many scientifically important questions are associated with the knowledge of the composition and structure of Martian samples. Amongst the most exciting questions is the clarification of the SNC problem- to prove or disprove a possible Martian origin of these meteorites. Since SNC meteorites have been used to infer the chemistry of the planet Mars, and its evolution (including the accretion history), it would be important to know if the whole story is true. But before addressing possible scientific results, we have to deal with the analytical requirements, and with possible pre-return work. It is unlikely to expect that a possible Mars sample return mission will bring back anything close to the amount returned by the Apollo missions. It will be more like the amount returned by the Luna missions, or at least in that order of magnitude. This requires very careful sample selection, and very precise analytical techniques. These techniques should be able to use minimal sample sizes and on the other hand optimize the scientific output. The possibility to work with extremely small samples should not obstruct another problem: possible sampling errors. As we know from terrestrial geochemical studies, sampling procedures are quite complicated and elaborate to ensure avoiding sampling errors. The significance of analyzing a milligram or submilligram sized sample and putting that in relationship with the genesis of whole planetary crusts has to be viewed with care. This leaves a dilemma on one hand, to minimize the sample size as far as possible in order to have the possibility of returning as many different samples as possible, and on the other hand to take a sample large enough to be representative. Whole rock samples are very useful, but should not exceed the 20 to 50 g range, except in cases of extreme inhomogeneity, because for larger samples the information tends to become redundant. Soil samples should be in the 2 to 10 g range, permitting the splitting of the returned samples for studies in different laboratories with variety of techniques.

Koeberl, Christian↗

Investigation of the Specht density estimator

The feasibility of using the Specht density estimator function on the IBM 360/44 computer is investigated. Factors such as storage, speed, amount of calculations, size of the smoothing parameter and sample size have an effect on the results. The reliability of the Specht estimator for normal and uniform distributions and the effects of the smoothing parameter and sample size are investigated.

Speed, F. M.↗

Calibrating the Ordovician Radiation of marine life: implications for Phanerozoic diversity trends

It has long been suspected that trends in global marine biodiversity calibrated for the Phanerozoic may be affected by sampling problems. However, this possibility has not been evaluated definitively, and raw diversity trends are generally accepted at face value in macroevolutionary investigations. Here, we analyze a global-scale sample of fossil occurrences that allows us to determine directly the effects of sample size on the calibration of what is generally thought to be among the most significant global biodiversity increases in the history of life: the Ordovician Radiation. Utilizing a composite database that includes trilobites, brachiopods, and three classes of molluscs, we conduct rarefaction analyses to demonstrate that the diversification trajectory for the Radiation was considerably different than suggested by raw diversity time-series. Our analyses suggest that a substantial portion of the increase recognized in raw diversity depictions for the last three Ordovician epochs (the Llandeilian, Caradocian, and Ashgillian) is a consequence of increased sample size of the preserved and catalogued fossil record. We also use biometric data for a global sample of Ordovician trilobites, along with methods of measuring morphological diversity that are not biased by sample size, to show that morphological diversification in this major clade had leveled off by the Llanvirnian. The discordance between raw diversity depictions and more robust taxonomic and morphological diversity metrics suggests that sampling effects may strongly influence our perception of biodiversity trends throughout the Phanerozoic.

Non-NASA Center↗

Sampling for area estimation - A comparison of full-frame sampling with the sample segment approach

The objective of this investigation was to evaluate the effect of sampling on the accuracy (precision and bias) of crop area estimates made from classifications of Landsat MSS data. Full-frame classifications of wheat and non-wheat for eighty counties in Kansas were repetitively sampled to simulate alternative sampling plans. Four sampling schemes involving different numbers of samples and different size sampling units were evaluated. The precision of the wheat area estimates increased as the segment size decreased and the number of segments was increased. Although the average bias associated with the various sampling schemes was not significantly different, the maximum absolute bias was directly related to sampling unit size.

Hixson, M. M.↗

Sampling for area estimation: A comparison of full-frame sampling with the sample segment approach

The effect of sampling on the accuracy (precision and bias) of crop area estimates made from classifications of LANDSAT MSS data was investigated. Full-frame classifications of wheat and non-wheat for eighty counties in Kansas were repetitively sampled to simulate alternative sampling plants. Four sampling schemes involving different numbers of samples and different size sampling units were evaluated. The precision of the wheat area estimates increased as the segment size decreased and the number of segments was increased. Although the average bias associated with the various sampling schemes was not significantly different, the maximum absolute bias was directly related to sampling unit size.

Hixson, M. M.↗

Chondrules in Apollo 14 samples and size analyses of Apollo 14 and 15 fines.

Chondrules have been observed in several breccia samples and one fines sample returned by the Apollo 14 mission. The chondrules are formed by at least three different processes that appear to be related to large impacts: (1) crystallization of shock-melted spherules and droplets; (2) rounding of rock clasts and mineral grains by abrasion in the base surge; and (3) diffusion and recrystallization around clasts in hot base surge and fall-back deposits. In the case of the Apollo 14 samples, the large impact almost certainly is the Imbrian event. Grain size analyses of undisturbed fines samples from the Apollo 14 site and from the Apollo 15 Apennine Front are almost identical, indicating that the two localities have similar meteoroid bombardment exposure ages, approximately 3.7 x 10 to the 9th yr. This observation is consistent with the interpretation that both the Fra Mauro formation and the Apennine Front material originated as ejecta from the Imbrian event.

King, E. A., Jr.↗

Increasing the Statistical Rigor of Cross-Species Differential Expression Analysis

Microgravity inflicts substantial, but undercharacterized, pressure on organisms that induces metabolic responses such as increased microbial virulence and antibiotic resistance, altered organ weights in developing rats, and loss of bone tissue in astronauts. Numerous studies have analyzed the effects of microgravity on specific organisms, tissues, or test conditions, but these projects are necessarily limited by the small sample size of space research. Increasing the sample size of spaceflight studies is non-trivial; however, pooling data from numerous studies can greatly increase the statistical rigor of comparative analyses. The GeneLab houses datasets from 73 spaceflight studies that performed transcription profiling assays. These data encompass a diverse array of organisms ranging from Escherichia coli to Mus musculus to Homo sapiens and comprise studies analyzing ionizing radiation, mammalian pregnancy, etc. Collectively, the GeneLab database contains a large quantity of transcription assays and RNA sequence data analyzing Differential Gene Expression (DGE) between microand normogravity. Xspecies, a cross-species analysis method for DGE developed by Kristiansson, et al. in 2012, identifies homologous genes between species that are universally up- or downregulated in response to test conditions. Previous work by an intern at GeneLab applied Xspecies to 19 datasets containing seven different species and identified 14 homologous groups differentially expressed under spaceflight conditions including several heat shock proteins and cytoskeletal components. Unfortunately, these results may be biased by the disproportionate number of studies on Arabidopsis thaliana (5) and Mus musculus (6) and the results are not normalized by evolutionary distances. Here, we present modifications to the Xspecies algorithm that permits incorporation of multi-omic data and normalizes data for effect size, directionality, and evolutionary distances. We then apply this algorithm to all currently available GeneLab studies

Xspecies↗

Evaluating the Feasibility of Data Simulation for Radiation Research: Estimating RBE Values for HZE Radiation

As the drive for deep space exploration intensifies, a comprehensive understanding of the health effects of radiation exposure becomes paramount to the future of human space flight. However, epidemiological data for radiation exposure, particularly to high-energy (HZE) ions, is limited, partially due to the financial and logistical costs of radiation studies. As an alternative, this study aims to assess the viability of data simulation strategies to accurately model potential study parameters prior to utilizing laboratory conditions. This study estimates a relative biological effectiveness (RBE) factor based on the solid tumor data for outbred mice provided by Edmundson et al. 2020. Excess relative risk (ERR) models for HZE-Fe ions and gamma radiation were estimated using Poisson regression with Weibull models to represent the background solid tumor hazard without radiation. RBE values were calculated from the ratio of the heavy ion linear slope to the gamma linear slope. The parameters from these models were then applied to simulate iterations of 300 datasets across HZE-Fe doses of 0.05, 0.2, 0.4, and 0.75 Gy; gamma radiation doses of 0.75, 2, and 3 Gy, as well as an unirradiated control group. Sample size per dose varied from 100-500 mice across simulations (800-4000 mice total per dataset). 1500 datasets were generated total (300 each for sample sizes 800, 1600, 3200, and 4000). For each dataset, ERR per radiation type and RBE for HZE-Fe were calculated. The RBE from the Edmondson data was calculated to be 5.55. The RBEs from the simulated data converged around this value across the increasing sample sizes. For n = 4000, the mean RBE across the 300 datasets was 5.71 (95% CI: 5.47-5.95). These results suggest that RBEs calculated from simulated data are credible. Based on this exploration, data simulation is a viable method of testing radiation studies. It provides a method of testing study assumptions and refining research questions prior to embarking on costly laboratory experiments.

Sneha Mehta↗

Improving Computational Efficiency of Prognostics Algorithms in Resource-Constrained Settings

The field of prognostics and health management provides quantitative methods for monitoring and predicting the health of physical systems. Prognostics algorithms are useful in that they can be employed to assess the current state of a system, propagate the system state throughout time, and predict potential anomalies or failures that may occur. However, effective prognosis can be challenging to achieve in resource-constrained settings due to computational limitations and high computational latency, leading to obsolete predictions. Thus, computationally efficient and accurate algorithms are necessary for some prognostics applications. In this work, we implement three new algorithmic approaches to prediction (sampling methods, variable prediction time step, variable prediction sample size) with the goal of improving computational efficiency while minimizing decrease in model accuracy. To quantitatively analyze our results, we examine a use-case of degradation of a Lithium-ion battery. Notably, through this work it was found that none of the sampling approaches had a significant impact on computational efficiency or model accuracy in predicting EOD of the battery. However, our results show that prediction accuracy is highly dependent on the time step used, and that an appropriate time step can optimize both model accuracy and simulation efficiency. Finally, implementing a variable sample size also affected prediction, and our results show that tuning both the magnitude and timing of the sample size adjustment in an application-specific manner may prove useful in some applications. Taken together, our findings highlight the challenge of performing prognostics in resource-constrained settings, and illustrate the potential of developing new prediction algorithms to improve computational efficiency of prognosis.

Prognostics↗

Improving Computational Efficiency of Prognostics Algorithms in Resource-Constrained Settings

In engineering and aerospace applications, it is vital to operational success to have insight into the expected performance and health of physical systems. The field of prognostics and health management provides quantitative methods for monitoring, predicting, and managing system health. Prognostics algorithms can be employed to assess the current state of a system, propagate the system throughout time, and predict potential anomalies or failures that may occur. While they can provide accurate prediction results, effective prognostics algorithms can be challenging to use in resource-constrained settings due to computational limitations and high computational latency, leading to obsolete predictions. Thus, computationally efficient and accurate algorithms are necessary for future remaining useful life predictions. In this work, we implement new algorithmic approaches for prediction, quantitatively compare them via a battery degradation use-case, and provide recommendations of potential improvements to a prognostics framework. One approach to prediction is through sampling, whereby the current state of a physical system is sampled many times and each sample is propagated forward until failure is reached, resulting in a distribution of failure values. To improve the efficiency of this process, we implemented five new algorithmic approaches to prediction, including three distinct sampling methods (standard Monte Carlo, Quasi-Monte Carlo, and Latin Hypercube Sampling), a variable time step algorithm, and a variable sample size algorithm. To compare the algorithms, we employ a variety of metrics designed specifically to analyze both computational efficiency and model accuracy. Our metrics include accuracy to compare the average predicted value to ground truth, mean absolute deviation to illustrate dispersion, specific percentile error to describe accuracy within a user-defined risk tolerance, and code run-time. To quantitatively analyze our results, we employ a use-case of degradation of a Lithium-ion battery. We use an electrochemistry-based model to describe the current health state of the battery, and implement our prediction algorithms to propagate forward in time until end-of-discharge (EOD) is reached. Notably, through this work it was found that none of our sampling approaches had a significant impact on computational efficiency or model accuracy in predicting EOD of the battery. We find that while the sampling methods are unique, the distributions they generate are similar, ultimately producing final predictions that are nearly identical. In exploring the effect of the time step within the prediction algorithm, we found that prediction accuracy was highly dependent on the time step used, and that implementing a variable time step within a particular prediction may provide an increase in computational efficiency while also maintaining prediction accuracy. Finally, implementing a variable sample size also affected prediction, and our results show that tuning both the magnitude and timing of the sample size adjustment can result in improved computation speed and maintained prediction accuracy. Taken together, our findings highlight the challenge of performing prognostics in resource-constrained settings, and illustrate the potential of developing new prediction algorithms to improve computational efficiency.

prognostics↗

Long-term reliability of hand-soldering M55365 Ta capacitors

This is a continuation of the report “Effects of Hand Soldering MIL-PRF-55365 Tantalum Capacitors,” which discusses the parametric effects of convection reflow soldering, JPL standard hand soldering, and optimized hand soldering on solid tantalum capacitors. The current focus is determining the long-term reliability effects of the various soldering techniques. Unfortunately, the 100-piece sample size chosen for the highly accelerated life tests was too small to reliably determine the effects of the different soldering techniques on the lifespan of the parts. In hindsight, this likely could have been predicted based on the large alphas and small betas of the Weibull failure distributions discovered during the scouting trials. Now that the effects of inadequate sample size are better understood, an opportunity exists to not only discover whether there are real differences in the reliability associated with the various soldering techniques, but also the potential to discover the voltage acceleration model and the temperature acceleration effect for these capacitors. It is recommended that the testing be repeated with a more appropriate sample size to capture this useful information.

Spence, Penelope↗

Initial analysis of “stone” size Ryugu samples: current status

As a part of the initial analysis of the Ryugu samples, we perform a variety of analyses of millimeter-sized "stones". Our goals are to elucidate the entire formation process of C-type asteroid Ryugu from the viewpoint of petrology and mineralogy ande obtain necessary information by sample analysis, and then simulate the formation of Ryugu based on the evidencef obtained rom sample analysis. Eighteen stones (8 from Room A and 10 from Room C) were received from the ISAS curation facility on June 1, 2021, and brought into a fully nitrogen-displaced glove box at Tohoku University. At the same time, we also received the powder samples from Room A and Room C. To completely block the atmosphere from leaking into the container, all samples were put in the sample transport containers prepared by ISAS, transferred from the main chamber to the glovebox at ISAS, and then all containers were completely sealed in plastic bags with moisture and oxygen absorbers. No moisture or oxygen was detected when the bags were opened in the glove box at Tohoku University, so it was confirmed that there was no exposure to the atmosphere during transport. To date, a number of analyses have been carried out successfully and almost on schedule. The analysis started with the measurement of reflectance spectra, which are sensitive to atmospheric oxidation, hydroxylation, and adsorbed water. The visible, near-infrared, and mid-infrared reflectance spectra were measured while the samples were kept airtight. The spectra of powder samples and stone samples (as aggregates and as single stone) were successfully obtained. A major feature of the stone team's analysis is the use of synchrotron radiation facilities around the world. Since this analysis is non-destructive, stone samples whose reflectance spectra were measured were sent to KEK, SPring-8, ESRF (France), SOLEIL (France), DESY (Germany), and APS (USA). Using these synchrotron radiation facilities, high spatial resolution and sensitivity XRD, STXM, XANES, CT [1], IR-CT, FT-IR [2, 3], XRF, and Mössbauer analyses were performed. Most of the analyses were carried out under air-tight conditions on the stone samples and the particulates separated from the stone samples. These analyses allowed us to determine the three-dimensional distribution of minerals and elements, redox state, density and porosity of the stone samples. Furthermore, as a characteristic analysis of the stone team, light elemental analysis using negative Muon was performed at the MLF facility of J-PARC with an exceptionally long allocation of machine time. This is the only non-destructive method to measure the concentration of light elements in the whole (not the surface) of stone samples. Because the characteristic X-rays produced by muon irradiation are much higher in energy than the fluorescent X-rays produced by X-ray irradiation, there is little effect of self-absorption by the sample, and therefore, the concentration of light elements such as carbon, oxygen, and Na in the entire "stone" sample can be determined. Some stone samples are currently being measured for heat and strength physical properties in order to understand the physical properties of asteroid Ryugu. The data obtained from these measurements are useful for interpreting the remote-sensing data data taken from the surface layer of the asteroid Ryugu [4-7]. It is also important for understanding the behavior of the Ryugu material during impact events. The surfaces of many stone samples were observed by electron microscopy and other techniques, especially on natural “flat” surfaces formed on 5 stomes. As a result, characteristric mineral aggregates formed by the reactions with water and characteiristic impact features were observed on some of the samples. Based on the observations of surfaces and the synchrotron measurements of the whole stones, important objects such as characteristic structures and specific crystal aggregates for understanding the formation history of the asteroid were identified, and these parts were separated from the stone samples using an Xe beam (pFIB) and analyzed by various methods including transmission electron microscopy and synchrotron radiation analysis. Many stone samples, from which important objects have been separated, are embedded in epoxy resin and cut to produce many polished sections. Electron microscopy and spectroscopic measurements of the polished surfaces are being carried out to reveal the detailed mineralogical properties and elemental distribution inside the stone samples. In the fall, machine time for synchrotron radiation will begin, and we plan to analyze single crystals and characteristic objects separated from the stone samples.

Tomoki Nakamura↗

Efficacy of FTIR Analysis in Determining CO2 Loading on Diglycolamine

In support of advanced air revitalization technologies to enable human spaceflight beyond low earth orbit, performance studies have been conducted using a liquid amine, Diglycolamine (DGA) between teams at NASA?s Johnson Spaceflight Center (JSC) and Ames Research Center (ARC). Liquid amines have been used in regenerable earth-based systems to remove CO2 from industrial systems as well as for closed-environment air revitalization because they can be regenerated at lower temperatures than solid sorbent systems. As an additional advantage to solid sorbent based systems, liquid sorbents can be cycled between an adsorbing contactor and degassing chamber, thereby reducing system complexity by operation in a continuous loop. In an effort to inform a regeneration system design for micro-gravity applications, ARC has performed a number of tests to characterize the degas mechanics of DGA. In order to accurately measure the amount of CO2 captured or released by the amine, methods such as gravimetric weighing and chemical decomposition are reasonable, however the initial design for a scaled down degas system required analysis on small sample sizes. In order to accomplish CO2 loading measurements with a sample size of approximately 500µL, Fourier-transform infrared spectroscopy (FTIR) was used. Calibration against acid decomposition showed relatively good correlation and test data showed reasonable adherence to expected trends, however more extensive testing should be conducted to fully validate the usage of FTIR to determine CO2 loading on DGA.

Diglycolamine↗

Statistical computation of tolerance limits

Based on a new theory, two computer codes were developed specifically to calculate the exact statistical tolerance limits for normal distributions within unknown means and variances for the one-sided and two-sided cases for the tolerance factor, k. The quantity k is defined equivalently in terms of the noncentral t-distribution by the probability equation. Two of the four mathematical methods employ the theory developed for the numerical simulation. Several algorithms for numerically integrating and iteratively root-solving the working equations are written to augment the program simulation. The program codes generate some tables of k's associated with the varying values of the proportion and sample size for each given probability to show accuracy obtained for small sample sizes.

Wheeler, J. T.↗

Large-Scale Spacecraft Fire Safety Tests

An international collaborative program is underway to address open issues in spacecraft fire safety. Because of limited access to long-term low-gravity conditions and the small volume generally allotted for these experiments, there have been relatively few experiments that directly study spacecraft fire safety under low-gravity conditions. Furthermore, none of these experiments have studied sample sizes and environment conditions typical of those expected in a spacecraft fire. The major constraint has been the size of the sample, with prior experiments limited to samples of the order of 10 cm in length and width or smaller. This lack of experimental data forces spacecraft designers to base their designs and safety precautions on 1-g understanding of flame spread, fire detection, and suppression. However, low-gravity combustion research has demonstrated substantial differences in flame behavior in low-gravity. This, combined with the differences caused by the confined spacecraft environment, necessitates practical scale spacecraft fire safety research to mitigate risks for future space missions. To address this issue, a large-scale spacecraft fire experiment is under development by NASA and an international team of investigators. This poster presents the objectives, status, and concept of this collaborative international project (Saffire). The project plan is to conduct fire safety experiments on three sequential flights of an unmanned ISS re-supply spacecraft (the Orbital Cygnus vehicle) after they have completed their delivery of cargo to the ISS and have begun their return journeys to earth. On two flights (Saffire-1 and Saffire-3), the experiment will consist of a flame spread test involving a meter-scale sample ignited in the pressurized volume of the spacecraft and allowed to burn to completion while measurements are made. On one of the flights (Saffire-2), 9 smaller (5 x 30 cm) samples will be tested to evaluate NASAs material flammability screening tests. The first flight (Saffire-1) is scheduled for July 2015 with the other two following at six-month intervals. A computer modeling effort will complement the experimental effort. Although the experiment will need to meet rigorous safety requirements to ensure the carrier vehicle does not sustain damage, the absence of a crew removes the need for strict containment of combustion products. This will facilitate the first examination of fire behavior on a scale that is relevant to spacecraft fire safety and will provide unique data for fire model validation.

Combustion↗

A Future Moon Mission: Curatorial Statistics on Regolith Fragments Applicable to Sample Collection by Raking

The strategy of raking rock fragments from the lunar regolith as a means of acquiring representative samples has wide support due to science return, spacecraft simplicity (reliability) and economy [3, 4, 5]. While there exists widespread agreement that raking or sieving the bulk regolith is good strategy, there is lively discussion about the minimum sample size. Advocates of consor-tium studies desire fragments large enough to support petrologic and isotopic studies. Fragments from 5 to 10 mm are thought adequate [4, 5]. Yet, Jolliff et al. [6] demonstrated use of 2-4 mm fragments as repre-sentative of larger rocks. Here we make use of cura-torial records and sample catalogs to give a different perspective on minimum sample size for a robotic sample collector.

Allton, J. H.↗

Statistical theory and methodology for remote sensing data analysis

A model is developed for the evaluation of acreages (proportions) of different crop-types over a geographical area using a classification approach and methods for estimating the crop acreages are given. In estimating the acreages of a specific croptype such as wheat, it is suggested to treat the problem as a two-crop problem: wheat vs. nonwheat, since this simplifies the estimation problem considerably. The error analysis and the sample size problem is investigated for the two-crop approach. Certain numerical results for sample sizes are given for a JSC-ERTS-1 data example on wheat identification performance in Hill County, Montana and Burke County, North Dakota. Lastly, for a large area crop acreages inventory a sampling scheme is suggested for acquiring sample data and the problem of crop acreage estimation and the error analysis is discussed.

Odell, P. L.↗