SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Water monitoring data acquisition system is structured about central computer that controls sampling and sensor operation, and analyzes and displays data in real time. Unit is essentially separated into two systems: computer system, and hard wire backup system which may function separately or with computer.
A bibliography of articles concerning topics on the deep space network, data acquisition, telecommunication, and related aerospace studies is presented. A sample of the diverse subjects include, solar energy remote sensing, computer science, Earth resources, astronomy, and satellite communication.
A test rig designed to generate heat exchanger pressure drop information under oscillating flow conditions is described. This oscillating flow rig is based on a variable stroke and variable frequency linear drive motor. A frequency capability of 120 hertz and a mean test pressure up to 15 mPA (2200 psi) allows for testing at flow conditions found in modern high specific power Stirling engines. An important design feature of this rig is that it utilizes a single close coupled dynamic pressure transducer to measure the pressure drop across the test sample. This eliminates instrumentation difficulties associated with the pressure sensing lines common to differential pressure transducers. Another feature of the rig is that it utilizes a single displacement piston. This allows for testing of different sample lengths and configurations without hardware modifications. All data acquisition and reduction for the rig is performed with a dedicated personal computer. Thus the overall system design efficiently integrates the testing and data reduction procedures. The design methodology and details of the test rig is described.
A test rig designed to generate heat exchanger pressure drop information under oscillating flow conditions is described. This oscillating flow rig is based on a variable stroke and variable frequency linear drive motor. A frequency capability of 120 hertz and a mean test pressure up to 15 mPA (2200 psi) allows for testing at flow conditions found in modern high specific power Stirling engines. An important design feature of this rig is that it utilizes a single close coupled dynamic pressure transducer to measure the pressure drop across the test sample. This eliminates instrumentation difficulties associated with the pressure sensing lines common to differential pressure transducers. Another feature of the rig is that it utilizes a single displacement piston. This allows for testing of different sample lengths and configurations without hardware modifications. All data acquisition and reduction for the rig is performed with a dedicated personal computer. Thus the overall system design efficiently integrates the testing and data reduction procedures. The design methodology and details of the test rig are described.
Tifft (1980, 1982) claimed that observations of double galaxies reveal a 72 km/s periodicity. Sharp showed that the 'periodicities' in the observations are completely consistent with the statistics of small numbers. Here it is shown that Tifft's statistical procedure would ascribe a periodicity to small sets of Gaussian random noise. Satisfying the null hypothesis that the observations are not samples drawn from a normal population would require the acquisition of at least an order of magnitude more data.
Ratios of C-12/C-13 in CO2 have been measured using a tunable diode laser (TDL) spectrometer to an accuracy of better than 0.4 percent. These results were made possible by the use of state-of-the-art high-temperature TDLs, an etalon and wavenumber calibration technique, high-speed assembly language controlled data acquisition, and the ratioing of absorbances from simultaneously acquired sample and reference data scans. The dual beam spectrometer that is employed uses the sweep integration technique in a spectral region where adjacent spectral lines are of approximately equal absorbance at the expected isotopic abundances.
A large-scale, outdoor, ground-based test capability for acquiring aerodynamic data in a simulated rain environment was developed at the Langley Aircraft Landing Dynamics Facility (ALDF) to assess the effect of heavy rain on airfoil performance. The ALDF test carriage was modified to transport a 10-ft-chord NACA 64210 wing section along a 3000-ft track at full-scale aircraft approach speeds. An overhead rain simulation system was constructed along a 525-ft section of the track with the capability of producing simulated rain fields of 2, 10, 30, and 40 in/hr. The facility modifications, the aerodynamic testing and rain simulation capability, the design and calibration of the rain simulation system, and the operational procedures developed to minimize the effect of wind on the simulated rain field and aerodynamic data are described in detail. The data acquisition and reduction processes are also presented along with sample force data illustrating the environmental effects on data accuracy and repeatability for the 'rain-off' test condition.
A laser Doppler velocimeter (LDV) system developed for the Aeroacoustic Propulsion Laboratory (APL) at the NASA Lewis Research Center is described. This system was developed to acquire detailed flow field data which could be used to quantify the effectiveness of internal exhaust gas mixers (IEGM's) and to verify and calibrate computational codes. The LDV was used as an orthogonal, three component system to measure the flow field downstream of the exit of a series of IEGM's and a reference axisymmetric splitter configuration. The LDV system was also used as a one component system to measure the internal axial flow within the nozzle tailpipe downstream of the mixers. These IEGM's were designed for low-bypass ratio turbofan engines. The data were obtained at a simulated low flight speed, high-power operating condition. The optical, seeding, and data acquisition systems of the LDV are described in detail. Sample flow field measurements are provided to illustrate the capabilities of the system at the time of this test, which represented the first use of LDV at the APL. A discussion of planned improvements to the LDV is also included.
Ground-based measurements of upper atmospheric parameters, such as temperature and wind velocity, can be made by observing airglow emissions that have a well-defined altitude profile and that are known to be representative of the emitting region. We describe the optical observatory at Maynooth (53.23 deg N, 6.4 deg W) at which two instruments, a Fabry-Perot interferometer and a Fourier transform spectrometer, are used to record atmospheric airglow emissions in Ireland at visible and near-infrared wavelengths, respectively. Descriptions of the instruments, data acquisition, and analysis procedures are provided, together with some sample results.
We describe a general methodology to Design for Producibility and Reliability (DFPAR) for very small volume production runs. In cases where the entire volume for fabrication is less than five products, traditional Statistical Process Control (SPC) is inadequate due to reliance on statistics of much larger volumes and the Central Limit Theorem. Data acquisition for process parameter estimation from such a small sample size is difficult; however, it is critical to producing high reliability product.
This is an update of the progress of a 4-year data restoration project effort funded by the LASER program to digitize photographs of the Apollo lunar rock samples and create high resolution digital images and undertaken by the Astromaterials Acquisition and Curation Office at JSC [1]. The project is currently in its last year of funding. We also provide an update on the derived products that make use of the digitized photos including the Lunar Sample Catalog and Photo Database[2], Apollo Sample data files for GoogleMoon[3].
Clean room standards like ISO 14644 used for facilities that construct spacecraft and store returned samples do not explicitly account for microbial contamination. While there are associated ISO standards for monitoring and controlling bio-contamination in clean rooms it is not always standard practice to do so. The NASA Astromaterials Acquisition and Curation Office maintains seven separate clean labs for storing extraterrestrial samples from the Moon, meteorites, cosmic dust, asteroids, comets, solar wind particles, and microparticle impact samples. These labs are routinely monitored for particulate and trace metal contamination. However, the sample collections are either non-sterile at the time of collection (e.g., meteorites) or are no longer being used to address scientific questions that could be affected by non-sterile conditions (e.g., Lunar samples). Outside of isolated studies there has not been a systematic, longitudinal characterization of the microbial ecology of NASA curation clean rooms. In accordance with the advanced curation initiative, and to prepare for future sample return missions, we have initiated a routine microbiological monitoring program in the Antarctic Meteorite Lab. This monitoring program will be used to determine what microbes are capable of surviving in these oligotrophic environments and whether or not they are capable of altering the sample collections in any significant manner. Repeat sampling will allow us to understand how routine use of these labs affects the microbial ecology over time.
The human visual system comprises layers of networks which sample, process, and code images. Understanding these networks is a valuable means of understanding human vision and of designing autonomous vision systems based on network processing. Ames Research Center has an ongoing program to develop computational models of such networks. The models predict human performance in detection of targets and in discrimination of displayed information. In addition, the models are artificial vision systems sharing properties with biological vision that has been tuned by evolution for high performance. Properties include variable density sampling, noise immunity, multi-resolution coding, and fault-tolerance. The research stresses analysis of noise in visual networks, including sampling, photon, and processing unit noises. Specific accomplishments include: models of sampling array growth with variable density and irregularity comparable to that of the retinal cone mosaic; noise models of networks with signal-dependent and independent noise; models of network connection development for preserving spatial registration and interpolation; multi-resolution encoding models based on hexagonal arrays (HOP transform); and mathematical procedures for simplifying analysis of large networks.
This study sets forth conceptual mission design strategies for the ascent and rendezvous phase of the proposed NASA/ESA joint Mars Sample Return Campaign. The current notional mission architecture calls for the launch of an acquisition/ caching rover in 2018, an Earth return orbiter in 2022, and a fetch rover with ascent vehicle in 2024. Strategies are presented to launch the sample into a nearly coplanar orbit with the Orbiter which would facilitate robust optical detection, orbit determination, and rendezvous. Repeating ground track orbits existat 457 and 572 km which would provide multiple launch opportunities with similar geometries for detection and rendezvous.
A dilatometer based on a laser interferometer is being developed to measure mechanical creep and coefficients of thermal expansion (CTEs) of materials at temperatures ranging from ambient down to 15 K. This cryogenic dilatometer has been designed to minimize systematic errors that limit the best previously available dilatometers. At its prototype stage of development, this cryogenic dilatometer yields a strain measurement error of 35 ppb or 1.7 ppb/K CTE measurement error for a 20-K thermal load, for low-expansion materials in the temperature range from 310 down to 30 K. Planned further design refinements that include a provision for stabilization of the laser and addition of a high-precision sample-holding jig are expected to reduce the measurement error to 5-ppb strain error or 0.3-ppb/K CTE error for a 20-K thermal load. The dilatometer (see figure) includes a common-path, differential, heterodyne interferometer; a dual-frequency, stabilized source bench that serves as the light source for the interferometer; a cryogenic chamber in which one places the material sample to be studied; a cryogenic system for cooling the interior of the chamber to the measurement temperature; an ultra-stable alignment stage for positioning the chamber so that the sample is properly positioned with respect to the interferometer; and a data-acquisition and control system. The cryogenic chamber and the interferometer portion of the dilatometer are housed in a vacuum chamber on top of a vibration isolating optical table in a cleanroom. The sample consists of two pieces a pillar on a base both made of the same material. Using reflections of the interferometer beams from the base and the top of the pillar, what is measured is the change in length of the pillar as the temperature in the chamber is changed. In their fundamental optical and electronic principles of operation, the laser light source and the interferometer are similar to those described in Common-Path Heterodyne Interferometers (NPO-20786), NASA Tech Briefs, Vol. 25, No. 7 (July 2001), page 12a, and Interferometer for Measuring Displacement to Within 20 pm (NPO- 21221), NASA Tech Briefs, Vol. 27, No. 7 (July 2003), page 8a. However, the present designs incorporate a number of special geometric, optical, and mechanical features to minimize optical and thermal-expansion effects that contribute to measurement errors. These features include the use of low-thermal expansion materials for structural components, kinematic mounting and symmetrical placement of optical components, and several measures taken to minimize spurious reflections of laser beams.
The optimum acquisition sweep strategy was determined for a PN code despreader when the a priori probability density function was not uniform. A psuedo noise spread spectrum system was considered which could be utilized in the DSN to combat radio frequency interference. In a sample case, when the a priori probability density function was Gaussian, the acquisition time was reduced by about 41% compared to a uniform sweep approach.
Precipitation estimates from satellites are subject to a number of uncertainties involving design characteristics, satellite positioning, natural variability of precipitation, and the noncontinuous acquisition of data. The sources and sizes of these uncertainties are in need of proper evaluation and estimation. The present sampling and estima-theory seems to be adequate for some measurement problems (e.g., determining precipitation at a point), while others require further theoretical work (e.g., determining the time history of precipitation over large areas).
Bayesian optimization (BO) can accelerate materials discovery by guiding expensive experiments toward the most promising processing conditions. We systematically compare five BO surrogate and framework combinations (Gaussian processes in Ax, Gaussian processes and Monte-Carlo neural networks in BayBE, random forests in Lolopy, and tree-structured Parzen (TPE) estimators in Hyperopt) on three benchmarks that mimic common materials design tasks (a discrete solid-electrolyte composition space, a hybrid discrete/continuous laminate-composite design problem solved with micromechanics modeling, and the continuous Ishigami analytic function which is a standard optimization benchmark). Each BO surrogate is paired with posterior mean, probability of improvement, and expected improvement acquisition functions and run for 100 trials from randomized initial samples with uniform random search providing a control. Across five random seeds per setting, BayBE’s Gaussian-process surrogate with expected improvement consistently reached ≥95 % of the known optimum in the fewest evaluations, while Lolopy’s random forest matched or exceeded GP performance on purely categorical or mixed spaces at a higher computational cost. Posterior mean alone often stagnated at local optima, underscoring the need for exploration, whereas probability and expected improvement balanced exploration and exploitation leading to better optimization in fewer trials. Execution times ranged from milliseconds for TPE to minutes for neural-network and random-forest surrogates. These results establish baseline expectations for BO in automated materials laboratories and highlight expected improvement with Gaussian processes as a reliable first choice, with random forests offering a strong alternative when categorical variables dominate. The benchmark suite and code are released to facilitate future surrogate, acquisition, and constraint-handling research in data-driven materials optimization.