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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 NTRS1994

Space Active Modular Materials Experiments (SAMMES): Low Earth Orbital mission aboard the Space Test Experiments STEP-3 platform

The requirement of satellite systems to survive in the space environment for 5 to 10 years to achieve greater cost effectiveness is discussed. Characterization of the orbital space environment and its effects on spacecraft systems have received considerable research attention. Instrumentation for long term measurement of key physical parameters characterizing the low Earth orbit (LEO) environment and its effects on degradation of spacecraft materials and solar arrays is reported. These measurements enable active, real time monitoring of the health of spacecraft and payload systems. SAMMES is designed to be autonomous, compact, low power, and lightweight.

Joshi, P.↗
NASA NTRS2023

Spaceflight Autonomous Multigenerational Microbial Sequencer (SAMMS) in Support of Plant-Growth Systems

As the National Aeronautics and Space Association (NASA) begins to pursue long-duration space flights, they will need to be able to provide astronauts with a nutritious and reliable food source. To meet the administration’s goal of traveling to the Moon and Mars, astronauts will need to begin to grow their own food in space. To protect their food source, extensive monitoring will occur to test for the effects of a space flight environment (e.g., radiation) as well as for early pathogen and disease detection. Genomic sequencing allows for both concerns to be tested on a regular basis. However, NASA’s current sequencer is unable to process plant tissues. Therefore, a novel method for plant DNA extraction using microneedle (MN) patches that will be able to feed into NASA’s existing system, but also require minimal human input is proposed. To support this, the design was broken down into four components (1) MN patch fabrication (2) MN patch extraction, (3) automated sampling motion control, and (4) a processing module. The MN patch is fabricated using a custom mold with conically shaped needles. The mold is filled with Polyvinyl alcohol (PVA) solution and placed in a vacuum desiccator. The mold is left in the vacuum overnight until the patch is dry and ready for use. The protocol was tested with varying pressures, drying times, volume amounts, and preparation methods to determine if highquality needles can be produced. A MN is a method of DNA extraction where the patch is applied to a leaf, the needles penetrate the leaf, breaking the rigid plant cell wall to isolate the DNA. A protocol for this method of extraction was tested to ensure the patch could produce the needed yield and purity. The tests varied by the number of patches, number of applications, and plant type. To automate the MN extraction method, motion control will utilize two separate axis tables which move in the x and y directions. The y-axis table will have an end effector that fits a MN patch and will have the ability to apply the patch to the leaf sample. This end effector will also act as a lid for a downstream processing module. The other axis will position the leaf sample and processing container so that the patch can be applied accurately. The Joint Comprehensive Sequencing System (JCSS) module integrates all the components together. The output of this module feeds into the NASA Charged Information-Storage Polymer Preparation System (CHIPPS) for genomic sequencing. The extraction module operates using a series of syringes and tubing to pump the varying reagents needed for the extraction protocol. The results of the study proved that MN patches are a viable method of DNA extraction. While fabrication of high-quality needles was unsuccessful, the protocol was able to be further developed using centrifugation. The integrated design between the motion control and the JCSS enabled the potential for automation with a complete conceptual design and prototype. Future research and development for this study would include (1) further testing for fabrication (2) expanding the range of plant species compatible with the MN patch, and (3) building a working prototype for the integrated system.

Peter Ling↗
NASA NTRS1992

Low Earth Orbital Mission Aboard the Space Test Experiments Platform (STEP-3)

A discussion of the Space Active Modular Materials Experiments (SAMMES) is presented in vugraph form. The discussion is divided into three sections: (1) a description of SAMMES; (2) a SAMMES/STEP-3 mission overview; and (3) SAMMES follow on efforts. The SAMMES/STEP-3 mission objectives are as follows: assess LEO space environmental effects on SDIO materials; quantify orbital and local environments; and demonstrate the modular experiment concept.

Brinza, David E.↗
NASA NTRS1993

Lightweight Modular Instrumentation for Planetary Applications

An instrumentation, called Space Active Modular Materials ExperimentS (SAMMES), is developed for monitoring the spacecraft environment and for accurately measuring the degradation of space materials in low earth orbit (LEO). The SAMMES architecture concept can be extended to instrumentation for planetary exploration, both on spacecraft and in situ. The operating environment for planetary application will be substantially different, with temperature extremes and harsh solar wind and cosmic ray flux on lunar surfaces and temperature extremes and high winds on venusian and Martian surfaces. Moreover, instruments for surface deployment, which will be packaged in a small lander/rover (as in MESUR, for example), must be extremely compact with ultralow power and weight. With these requirements in mind, the SAMMES concept was extended to a sensor/instrumentation scheme for the lunar and Martian surface environment.

Joshi, P. B.↗
NASA NTRSDate not supplied

Spaceflight Autonomous Multigenerational Microbial Sequencer in Support of Plant-Growth Systems

The CubeSat platform has proven successful in obtaining meaningful life science information when biological payloads are incorporated. Examples include: 1) the first-ever CubeSat with a biological payload, GeneSat-1, which demonstrated decreased growth rates for flight samples of Escherichia coli in low Earth orbit (Parra et al. 2008); 2) PharmaSat, demonstrated that Saccharomyces cerevisiae in the microgravity environment exhibits a significant level of metabolic activity even at high doses of applied antifungal (Ricco et al. 2011); 3) O/OREOS, which used Bacillus subtilis(bacteria) to demonstrate for the first time that microorganisms can be loaded in a dried, dormant form and then rehydrated and grown in orbit months after launch (Nicholson et al. 2011; Ehrenfreund et al. 2014; 4) the SporeSat payload, which investigated Ceratopteris richardii(fern spores) using lab-on-a-chip devices (BioCDs) and minicentrifuges to produce artificial gravitational forces in ground studies (Park et al. 2017), with demonstration of the BioCD and minicentrifuge in space; 5) EcAMSat, the first CubeSat to be directly deployed from the ISS for an experiment assessing antibiotic resistance of E. coli in the microgravity environment (Padgen et al. 2020); 6) BioSentinel, exposed a culture of yeast to galactic cosmic radiation (GCR) and solar particle events while in heliocentric orbit to measure the rate of double-strand-break repair using DNA-repair-deficient mutants. This effort measures the metabolic parameters of yeast in a deep-space environment compared to Earth ambient conditions using a 3-color LED detection system (Ricco et al. 2020; Padgen et al. 2021). We aim to expand this list to include a Spaceflight Autonomous Multigenerational Microbial Sequencer (SAMMS). SAMMS will allow for the genome level understanding of changes in growth and metabolic activity for any organism. While microbes are suitable for early studies in our proposed platform because of their small size, small and relatively less-complicated genomes, fast generation times, and relevance to life support systems; multicellular organisms can similarly be evaluated for their genetic response to the spaceflight environment. The Spaceflight Autonomous Multigenerational Microbial Sequencer (SAMMS) will enable autonomous sequencing of biological samples in plant production units, cislunar orbit and on the lunar surface to examine spaceflight effects (ie. radiation, altered gravity, reduced pressures) on plant and microbial genomes.On this team a Kennedy Space Center (KSC) space crop production and water systems microbiologist/molecular biologist works with a Johnson Space Center (JSC) International Space Station (ISS) microbial sequencing expert and an Ames Research Center (ARC) CubeSat Engineering team to convert an automated Oxford Nanopore librarypreparation and sequencing method to a fluidic CubeSat payload system. The Oxford Nanopore MinION sequencing platform has proven successful in the spaceflight environment onboard the ISS (Stahl-Rommel et al. 2021). Further long-duration spaceflight and exposure to high levels of radiation will cause genotypic effects in biological organisms that may affect their function. Monitoring the adaption of a population to the spaceflight environment and any subsequent beneficial mutations will allow for the harnessing of organisms best suited for use in life support systems. This will ensure that the selected life support-essential microorganisms maintain their intended specified function over generations of culturing in the relevant spaceflight environment without becoming hazardous to crew or spacecraft systems.

Aubrie E Orourke↗
NASA NTRS1981

Pilot guidance and display considerations for energy efficient flight profiles

Two computer programs are applied to energy efficient flight operation in order to minimize aircraft operating costs. One algorithm (OPTIM) computes vertical flight profiles which optimize direct operating costs, including fuel and time costs, for an aircraft flying over a fixed range and with a fixed time-of-arrival. The second program (TRAGEN) simulates an aircraft steered to fly along a specified vertical flight trajectory, in order to examine fuel and cost penalties involved in flying nonoptimal trajectories. Constraints such as air traffic control procedures, and atmospheric and weight conditions are considered and supported by graphs and diagrams. The use of the algorithms as preflight planning tools is discussed, emphasizing OPTIM's future application for on-board energy management. Finally, research questions concerning pilot guidance and display considerations for advanced energy/flight management systems are addressed.

Samms, K. H.↗
NASA NTRS1983

Information theory analysis of sensor-array imaging systems for computer vision

Information theory is used to assess the performance of sensor-array imaging systems, with emphasis on the performance obtained with image-plane signal processing. By electronically controlling the spatial response of the imaging system, as suggested by the mechanism of human vision, it is possible to trade-off edge enhancement for sensitivity, increase dynamic range, and reduce data transmission. Computational results show that: signal information density varies little with large variations in the statistical properties of random radiance fields; most information (generally about 85 to 95 percent) is contained in the signal intensity transitions rather than levels; and performance is optimized when the OTF of the imaging system is nearly limited to the sampling passband to minimize aliasing at the cost of blurring, and the SNR is very high to permit the retrieval of small spatial detail from the extensively blurred signal. Shading the lens aperture transmittance to increase depth of field and using a regular hexagonal sensor-array instead of square lattice to decrease sensitivity to edge orientation also improves the signal information density up to about 30 percent at high SNRs.

Huck, F. O.↗
NASA NTRS1984

Image-plane processing for improved computer vision

The proper combination of optical design with image plane processing, as in the mechanism of human vision, which allows to improve the performance of sensor array imaging systems for edge detection and location was examined. Two dimensional bandpass filtering during image formation, optimizes edge enhancement and minimizes data transmission. It permits control of the spatial imaging system response to tradeoff edge enhancement for sensitivity at low light levels. It is shown that most of the information, up to about 94%, is contained in the signal intensity transitions from which the location of edges is determined for raw primal sketches. Shading the lens transmittance to increase depth of field and using a hexagonal instead of square sensor array lattice to decrease sensitivity to edge orientation improves edge information about 10%.

Huck, F. O.↗
NASA NTRS1984

A simulation of remote sensor systems and data processing algorithms for spectral feature classification

A computational model of the deterministic and stochastic processes involved in multispectral remote sensing was designed to evaluate the performance of sensor systems and data processing algorithms for spectral feature classification. Accuracy in distinguishing between categories of surfaces or between specific types is developed as a means to compare sensor systems and data processing algorithms. The model allows studies to be made of the effects of variability of the atmosphere and of surface reflectance, as well as the effects of channel selection and sensor noise. Examples of these effects are shown.

Arduini, R. F.↗
NASA NTRS1984

Imaging system design for improved information capacity

Shannon's theory of information for communication channels is used to assess the performance of line-scan and sensor-array imaging systems and to optimize the design trade-offs involving sensitivity, spatial response, and sampling intervals. Formulations and computational evaluations account for spatial responses typical of line-scan and sensor-array mechanisms, lens diffraction and transmittance shading, defocus blur, and square and hexagonal sampling lattices.

Fales, C. L.↗
NASA NTRS1984

Image-plane processing of visual information

Shannon's theory of information is used to optimize the optical design of sensor-array imaging systems which use neighborhood image-plane signal processing for enhancing edges and compressing dynamic range during image formation. The resultant edge-enhancement, or band-pass-filter, response is found to be very similar to that of human vision. Comparisons of traits in human vision with results from information theory suggest that: (1) Image-plane processing, like preprocessing in human vision, can improve visual information acquisition for pattern recognition when resolving power, sensitivity, and dynamic range are constrained. Improvements include reduced sensitivity to changes in lighter levels, reduced signal dynamic range, reduced data transmission and processing, and reduced aliasing and photosensor noise degradation. (2) Information content can be an appropriate figure of merit for optimizing the optical design of imaging systems when visual information is acquired for pattern recognition. The design trade-offs involve spatial response, sensitivity, and sampling interval.

Huck, F. O.↗
NASA NTRS1985

Image gathering and processing - Information and fidelity

In this paper we formulate and use information and fidelity criteria to assess image gathering and processing, combining optical design with image-forming and edge-detection algorithms. The optical design of the image-gathering system revolves around the relationship among sampling passband, spatial response, and signal-to-noise ratio (SNR). Our formulations of information, fidelity, and optimal (Wiener) restoration account for the insufficient sampling (i.e., aliasing) common in image gathering as well as for the blurring and noise that conventional formulations account for. Performance analyses and simulations for ordinary optical-design constraints and random scences indicate that (1) different image-forming algorithms prefer different optical designs; (2) informationally optimized designs maximize the robustness of optimal image restorations and lead to the highest-spatial-frequency channel (relative to the sampling passband) for which edge detection is reliable (if the SNR is sufficiently high); and (3) combining the informationally optimized design with a 3 by 3 lateral-inhibitory image-plane-processing algorithm leads to a spatial-response shape that approximates the optimal edge-detection response of (Marr's model of) human vision and thus reduces the data preprocessing and transmission required for machine vision.

Huck, F. O.↗
NASA NTRS1987

Combined optimization of image-gathering and image-processing systems for scene feature detection

The relationship between the image gathering and image processing systems for minimum mean squared error estimation of scene characteristics is investigated. A stochastic optimization problem is formulated where the objective is to determine a spatial characteristic of the scene rather than a feature of the already blurred, sampled and noisy image data. An analytical solution for the optimal characteristic image processor is developed. The Wiener filter for the sampled image case is obtained as a special case, where the desired characteristic is scene restoration. Optimal edge detection is investigated using the Laplacian operator x G as the desired characteristic, where G is a two dimensional Gaussian distribution function. It is shown that the optimal edge detector compensates for the blurring introduced by the image gathering optics, and notably, that it is not circularly symmetric. The lack of circular symmetry is largely due to the geometric effects of the sampling lattice used in image acquisition. The optimal image gathering optical transfer function is also investigated and the results of a sensitivity analysis are shown.

Halyo, Nesim↗
NASA NTRS1986

Combined optimization of image-gathering optics and image-processing algorithm for edge detection

This paper investigates the relationships between the image-gathering and image-processing systems for minimum mean-squared error estimation of scene characteristics. A stochastic optimization problem is formulated in which the objective is to determine a spatial characteristic of the scene rather than a feature of the already blurred, sampled, and noisy image data. The Wiener filter for the sampled image case is obtained as a special case, where the desired characteristics is scene restoration. Optimal edge detection is investigated. It is shown that the optimal edge detector compensates for the blurring introduced by the image-gathering optics, and, notably, that it is not circularly symmetric. The lack of circular symmetry is largely due to the geometric effects of the sampling lattice used in image acquisition.

Halyo, N.↗
NASA NTRS1987

Development of response models for the Earth Radiation Budget Experiment (ERBE) sensors. Part 1: Dynamic models and computer simulations for the ERBE nonscanner, scanner and solar monitor sensors

Dynamic models and computer simulations were developed for the radiometric sensors utilized in the Earth Radiation Budget Experiment (ERBE). The models were developed to understand performance, improve measurement accuracy by updating model parameters and provide the constants needed for the count conversion algorithms. Model simulations were compared with the sensor's actual responses demonstrated in the ground and inflight calibrations. The models consider thermal and radiative exchange effects, surface specularity, spectral dependence of a filter, radiative interactions among an enclosure's nodes, partial specular and diffuse enclosure surface characteristics and steady-state and transient sensor responses. Relatively few sensor nodes were chosen for the models since there is an accuracy tradeoff between increasing the number of nodes and approximating parameters such as the sensor's size, material properties, geometry, and enclosure surface characteristics. Given that the temperature gradients within a node and between nodes are small enough, approximating with only a few nodes does not jeopardize the accuracy required to perform the parameter estimates and error analyses.

Halyo, Nesim↗