Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “data conditioning”

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.

At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Development and implementation of the NASA Metrology and Information System

The NASA Metrology Information System (NMIS) was developed as a subsystem of the NASA Equipment Management System (NEMS) to provide a standardized technique in managing the calibration programs of its field Centers and facilities. The NMIS is a computerized data-base system providing: automatic instrument calibration recall and control, historical data including calibration and repair labor and parts costs, incoming instrument performance condition; instrument data including description, manufacturer, model and serial number, and instrument user name location. NMIS automatically provides 28 standardized calibration system performance reports on a user selected schedule. An ad hoc report generation capability is also provided. A standardized form, the Metrology Control Document, was developed for use as a calibration work order and data input document. System implementation plan is presented.

German, Earl S.↗
NASA NTRS1994

Integrated developmental model of life-support capabilities in wheat

The objective of this project was to develop a model for CO2, O2, H2O, and nitrogen use during the life cycle of wheat. Spreadsheets and accompanying graphs were developed to illustrate plant population reactions to environmental parameters established in the Controlled Ecological Life Support System (CELSS) program at Kennedy Space Center, Fl. The spreadsheets and graphs were produced using validated biomass production chamber (BPC) data from BWT931. Conditions of the BPC during the 83 day plant growth period were as follows: The BPC area is 27.8 m(exp 2), volume is 113 m(exp 3). Temperatures during the 83 day plant growth period ranged from 16.3 to 24.8 C during the light cycle (except for day 69, when the minimum and maximum temperatures were 7.7 C and 7.9 C, respectively) and 14.5 C and 23.6 C during the dark cycle (except for day 49, when the minimum and maximum temperatures were 11.1 C and 11.3 C, respectively). Relative humidity was 85 percent for the first seven days of plant growth, and 70 percent thereafter. The plant leaf canopy area was 10 m(exp 2). Presented is a list and explanation of each spreadsheet and accompanying graph(s), conditions under which the data were collected, and formulas used to obtain each result.

Darnell, R. L.↗
NASA NTRS2014

Investigation of Spiral Bevel Gear Condition Indicator Validation via AC-29-2C Using Fielded Rotorcraft HUMS Data

This report presents the analysis of gear condition indicator data collected on a helicopter when damage occurred in spiral bevel gears. The purpose of the data analysis was to use existing in-service helicopter HUMS flight data from faulted spiral bevel gears as a Case Study, to better understand the differences between HUMS data response in a helicopter and a component test rig, the NASA Glenn Spiral Bevel Gear Fatigue Rig. The reason spiral bevel gear sets were chosen to demonstrate differences in response between both systems was the availability of the helicopter data and the availability of a test rig that was capable of testing spiral bevel gear sets to failure. The objective of the analysis presented in this paper was to re-process helicopter HUMS data with the same analysis techniques applied to the spiral bevel rig test data. The damage modes experienced in the field were mapped to the failure modes created in the test rig. A total of forty helicopters were evaluated. Twenty helicopters, or tails, experienced damage to the spiral bevel gears in the nose gearbox. Vibration based gear condition indicators data was available before and after replacement. The other twenty tails had no known anomalies in the nose gearbox within the time frame of the datasets. These twenty tails were considered the baseline dataset. The HUMS gear condition indicators evaluated included gear condition indicators (CI) Figure of Merit 4 (FM4), Root Mean Square (RMS) or Diagnostic Algorithm 1 (DA1) and +/- 3 Sideband Index (SI3). Three additional condition indicators, not currently calculated on-board, were calculated from the archived data. These three indicators were +/- 1 Sideband Index (SI1), the DA1 of the difference signal (DiffDA1) and the peak-to-peak of the difference signal (DP2P). Results found the CI DP2P, not currently available in the on-board HUMS, performed the best, responding to varying levels of damage on thirteen of the fourteen helicopters evaluated. Two additional CIs also not in the on-board system, DiffDA1and SI1, also performed well responding to twelve and ten of the fourteen helicopters evaluated respectively. Of the three CIs currently available in the MSPU, DA1, FM4 and SI3, SI3, responded to eight, DA1 responded to six and FM4 responded to four of the fourteen helicopters evaluated. FM4, the poorest performing CI, was not as responsive to damage as the other five CIs. Conversely, when compared to the other two, it was the only CI that responded to damage on two helicopters. CI response could not be correlated to specific failure modes due to limited pictures and subjective descriptions found within the TDA. Flight regime did affect CI response to some gear faults. Due to the range of operating conditions for each regime, more studies are required to determine their sensitivity to regimes.

rotorcraft↗
DOE OSTI2023

Effective data sampling strategies and boundary condition constraints of physics-informed neural networks for identifying material properties in solid mechanics

Material identification is critical for understanding the relationship between mechanical properties and the associated mechanical functions. However, material identification is a challenging task, especially when the characteristic of the material is highly nonlinear in nature, as is common in biological tissue. In this work, we identify unknown material properties in continuum solid mechanics via physics-informed neural networks (PINNs). To improve the accuracy and efficiency of PINNs, we develop efficient strategies to nonuniformly sample observational data. We also investigate different approaches to enforce Dirichlet-type boundary conditions (BCs) as soft or hard constraints. Finally, we apply the proposed methods to a diverse set of time-dependent and time-independent solid mechanic examples that span linear elastic and hyperelastic material space. The estimated material parameters achieve relative errors of less than 1%. As such, this work is relevant to diverse applications, including optimizing structural integrity and developing novel materials.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Hybrid geological modeling: Combining machine learning and multiple-point statistics

Accurately modeling and constructing a geologically realistic subsurface model remains an outstanding problem as the morphology controls the flow behaviors. Particularly, one of the pattern-based methods, namely cross-correlation based simulation, has been proved to be an effective way to reconstruct a realistic model, at both small and large scales. However, conditioning to point data in the large-scale problems is still a crucial issue in these algorithms, since there is always a trade-off between the quality of the realizations and the degree of point data reproduction. Specifically, it is not practical to build a training image (TI) which includes all the possibilities and variabilities. Therefore, finding a pattern that can represent the point data and, at the same time, preserving the connectivities is difficult. This leads to producing highly-connected realizations with a significant mismatch or poor models with a reasonable degree of point data reproduction. To accurately reproduce the densely distributed hard data, pixel-based methods can also produce some unrealistic artifacts around the hard data. In this paper, to overcome this challenge, however, we use pattern-based methods as they often produce more disconnected geobodies when dealing with dense hard data, and proposed a hybrid algorithm using the pattern-based methods and convolutional neural network (CNN). The trained CNN model is utilized to improve the quality of conditioning to point data for the original realizations generated by the pattern-based algorithm. As such, the mismatch locations are identified, and the same regions are used in the training of CNN to mimic the procedure through which a missing region can be filled. To evaluate the performance of the proposed hybrid algorithm, it is tested on cases with different dimensions and different numbers of facies. Then, the newly improved realizations are compared with the initial realizations generated by the pattern-based algorithm. The comparison is also conducted by the flow simulation test. And it indicates that the proposed hybrid algorithm can better reproduce the point data, while the connectivities are better preserved.

58 GEOSCIENCES↗
DOE OSTI2022

Marine Boundary Layer Decoupling and the Stable Isotopic Composition of Water Vapor

Decoupling of the subcloud layer in stratocumulus-topped marine boundary layers (STMBL) influences low-cloud cover by limiting the supply of water vapor from the surface. However, the relative importance of mixing between surface fluxes and other reservoirs of water vapor as a function of the degree of decoupling is poorly understood. Water vapor transport within the STMBL and its response to decoupling is explored using surface measurements of water vapor isotopic composition that were obtained from Graciosa Island, Azores, during the summer and fall of 2018. The data show an inverse relationship between the decoupling metric, Δq, and the degree of drying from an isotopically depleted water vapor source. The isotopic data require some degree of drying with an isotopically depleted source for coupled conditions, and likely require a small amount of mixing even for strongly decoupled conditions. The data are consistent with mixing between purely local reservoirs of water vapor, subjected to a small amount of condensation and fractionation, and do not require the invocation of large-scale transport of water vapor aloft or additional cloud-formation effects aloft.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1981

Multisensor analysis of hydrologic features with emphasis on the Seasat SAR

Synthetic aperture radar (SAR) imagery of the Wind River Range area in Wyoming is compared with visible and near-infrared imagery of the same area. Data from the Seasat L-Band SAR and an aircraft X-Band SAR are compared with Landsat Return Beam Vidicon (RBV) visible data and near-infrared aerial photography and topographic maps of the same area. It is noted that visible and near-infrared data provide more information than the SAR data when conditions are the most favorable. The SAR penetrates clouds and snow, however, and data can be acquired day or night. Drainage density detail is good on SAR imagery because individual streams show up well owing to riparian vegetation; this causes higher radar reflections which result from the 'rough' surface which vegetation creates. In the winter image, the X-Band radar data show high returns because of cracks on the lake ice surfaces. High returns can also be seen in the L-Band SAR imagery of the lakes due to ripples on the surface induced by wind. It is concluded that the use of multispectral data would optimize analysis of hydrologic features.

Foster, J. L.↗
NASA NTRS1988

Microgravity bubble migration in rotating flows

The NASA KC-135 microgravity-environment aircraft was used to gather experimental data on the migration of bubbles in rotating liquid fields under reduced gravity conditions. The data thus obtained were compared to those of an analysis for the prediction of fluid particle trajectories in the presence of both gravitational and rotational fields at the limit of quasi-steady creeping flow. Reasonable agreement with experimental results was achieved, despite the large size of the bubbles, their close proximity to a bounding surface over significant portions of their migration time, and their rather nonspherical geometry.

Ruggles, J. S.↗
NASA NTRS2008

Data Assimilation Cycling for Weather Analysis

This software package runs the atmospheric model MM5 in data assimilation cycling mode to produce an optimized weather analysis, including the ability to insert or adjust a hurricane vortex. The program runs MM5 through a cycle of short forecasts every three hours where the vortex is adjusted to match the observed hurricane location and storm intensity. This technique adjusts the surrounding environment so that the proper steering current and environmental shear are achieved. MM5cycle uses a Cressman analysis to blend observation into model fields to get a more accurate weather analysis. Quality control of observations is also done in every cycle to remove bad data that may contaminate the analysis. This technique can assimilate and propagate data in time from intermittent and infrequent observations while maintaining the atmospheric field in a dynamically balanced state. The software consists of a C-shell script (MM5cycle.driver) and three FORTRAN programs (splitMM5files.F, comRegrid.F, and insert_vortex.F), and are contained in the pre-processor component of MM5 called "Regridder." The model is first initialized with data from a global model such as the Global Forecast System (GFS), which also provides lateral boundary conditions. These data are separated into single-time files using splitMM5.F. The hurricane vortex is then bogussed in the correct location and with the correct wind field using insert_vortex.F. The modified initial and boundary conditions are then recombined into the model fields using comRegrid.F. The model then makes a three-hour forecast. The three-hour forecast data from MM5 now become the analysis for the next short forecast run, where the vortex will again be adjusted. The process repeats itself until the desired time of analysis is achieved. This code can also assimilate observations if desired.

Tran, Nam↗
NASA NTRS1986

Use of remotely sensed data for assessing forest stand conditions in the Eastern United States

Techniques for the detection, classification, and measurement of forest disturbances, using digital Landsat data for three study areas (Pennsynvania, North Carolina, and Maine) are reported. Results with respect to (1) the delineation and assessment of forest damage due to the use of two forest insect defoliators, and (2) qualitative assessment of the Multispectral Scanner (MSS) and the Thematic Mapper data for delineating forest stand characteristics are presented. Key results include a development of a statewide MSS digital data base and associated image-processing techniques for accurately delineating insect-damaged and healthy forest areas. For classification of broad land-cover classes which are spectrally homogeneous, the accuracy yielded by the use of either MSS data or TM Simulator data is similar. However, the TMS data provided 20 percent accuracy improvement over the MSS results when detailed (Level III) forest classes were mapped.

Williams, D. L.↗
DOE OSTI2022

Opportunities and data requirements for data-driven prognostics and health management in liquid hydrogen storage systems

During the past decade, Prognostics and Health Management (PHM) has become an important set of tools in various areas of industry and academic reliability engineering. PHM consists of a variety of mathematical and computational methods used to support data-driven decision-making to increase the safety, availability, and reliability of complex engineering systems. In particular, PHM can provide crucial insight into reliability and safety design improvements for developing technologies where historical performance and failure data are limited. This is the case of hydrogen fueling and storage technologies. This work presents a high-level approach for designing data-driven PHM applications for bulk liquid hydrogen (LH 2 ) storage systems for hydrogen fueling stations. This paper addresses core aspects of the design, development, and implementation of data-driven PHM applications that can improve the reliability assessment of hydrogen components. The analysis focuses on the relationship between data availability and diagnostic/prognostic capabilities; potential challenges; and integration schemes for current risk mitigation measures. We identify potential condition-monitoring data sources for key components in an LH 2 storage system, including storage tanks, piping, and pumps. Further, we determine that the short-term goals for the implementation of data-driven models in PHM frameworks in hydrogen systems should focus on developing adequate data collection and analysis strategies, as well as exploring the effect on reliability, safety, and regulations for hydrogen systems.

08 HYDROGEN↗
NASA NTRS1981

Additional noise data on the SR-3 propeller

The noise generated by supersonic-tip-speed propellers is investigated. An eight bladed propeller was tested in the Lewis 8- by 6-foot wind tunnel with conditions providing data in the subsonic operating region of the propeller. These conditions resulted in a slight reshaping of the curve for blade passing tone as a function of helical tip Mach number as compared with previous results. Directivity curves with an additional transducer position gave an indication of a lobe pattern for this propeller that was not previously observed. The present data at the aft-most position indicate that some reflections, possibly from the test rig support strut, may have affected the data taken previously.

Dittmar, J. H.↗
NASA NTRS1988

Particle cloud combustion in reduced gravity

The prinicipal objectives of this microgravity experiment program are to obtain flame propagation rate and flame extinction limit data for several important premixed, quiescent particle cloud combustion systems under near zero-gravity conditions. The data resulting from these experiments are needed for utilization with currently available and tractable flame propagation and extinction theory. These data are also expected to provide standards for the evaluation of fire hazards in particle suspensions in both Earth-based and space-based applications. Both terrestrial and space-based fire safety criteria require the identification of the critical concentrations of particulate fuels and inerts at the flame extinction conditions.

Berlad, A. L.↗
NASA NTRS1993

Performance and rotor loads measurements of the Lynx XZ170 helicopter with rectangular blades

This report presents the results of a series of flight tests on the Lynx XZ170 helicopter with rectangular blades. The test objectives were to explore the flight envelope and to measure the performance and structural loads of the Lynx main-rotor system. The tests were conducted as part of the British Experimental Rotor Program (BERP) under a contract with the Ministry of Defense in England. Data were acquired for steady-level flights at five weight coefficients. Some flight conditions were tested at beyond the retreating-blade stall boundary, which was defined by a predetermined limit on the pitchlink vibratory load. In addition to documenting the flight conditions and data, this report describes the aircraft, particularly the rotor system, in detail.

Lau, Benton H.↗
NASA NTRS1996

The thermal conductance of solid-lubricated bearings at cryogenic temperatures in vacuum

The thermal conductance of Hertzian contacts is of great importance to cryogenic spacecraft mechanisms such as the Infra-Red Space Observatory (ISO) and the Far Infra-Red Space Telescope (FIRST). At cryogenic temperatures, cooling of mechanism shafts and associated components occurs via conduction through the bearings. When fluid lubricants are cooled below their pour points, they no longer lubricate effectively, and it is necessary to use low shear strength solid lubricants. Currently, only very limited low temperature data exists on the thermal conductance of Hertzian contacts in both unlubricated and lubricated conditions. This paper reports on measurements of thermal conductance made on stationary ball bearings under cryo-vacuum conditions. Quantitative data is provided to support the development of computer models predicting the thermal conductance of Hertzian contacts and solid lubricants at cryogenic temperatures.

Anderson, M. J.↗
DOE OSTI2020

Calibration of hyperelastic constitutive models: the role of boundary conditions, search algorithms, and experimental variability

The calibration of hyperelastic constitutive models of soft tissue and tissue surrogates is often treated as an exercise in curve-fitting to the average experimental response, and many of the complicating factors such as experimental boundary conditions and data variability are ignored. Here, we focus on three questions that arise in this area: the ramifications of ignoring the experimental boundary conditions, the use of local optimizers, and the role of data variability. Using data from a uniaxial extension experiment on a tissue surrogate, we study how these three factors affect the calibration of isotropic hyperelastic constitutive models. Our results show that even with the simplest of constitutive models, it is necessary to look beyond a "good fit" to the average.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Data for "Soil carbon dynamics during drying vs. rewetting: Importance of antecedent moisture conditions"

This dataset contains data used for the paper "Soil carbon dynamics during drying vs. rewetting: importance of antecedent moisture conditions". The Related References field will be updated with a full citation when available.Soil moisture influences soil carbon dynamics, including microbial growth and respiration. The response of such ‘soil respiration’ to moisture changes is generally assumed to be linear and reversible, i.e. to depend only on the current moisture state. Current models thus do not account for antecedent soil moisture conditions when determining soil respiration or the available substrate pool. We conducted a laboratory incubation to determine how the antecedent conditions of drought and flood influenced soil organic matter (SOM) chemistry, bioavailability, and respiration. We sampled soils from an upland coastal forest, Beaver Creek, WA USA, and subjected them to drying and rewetting treatments. For the drying treatment, field moist soils were saturated and then dried to 75, 50, 35, and 5 % saturation. In the rewetting treatment, field moist soils were air-dried and then rewet to 35, 50, 75, and 100 % saturation. We measured respiration and water extractable organic carbon (WEOC) concentrations and used 1H-NMR and FT-ICR-MS to characterize the WEOC pool across the treatments. The drying vs. wetting treatment strongly influenced SOM bioavailability, as rewet soils (with antecedent drought) had greater WEOC concentrations and respiration fluxes compared to the drying soils (with antecedent flood). In addition, air-dry soils had the highest WEOC concentrations, and the NMR-resolved peaks showed a strong contribution of protein groups in these soils. Both NMR and FT-ICR-MS analyses indicated increased contribution of complex aromatic groups/molecules in the rewet soils, compared to the drying soils. We suggest that drying introduced organic matter into the WEOC pool via desorption of aromatic molecules and/or by microbial cell lysis, and this stimulated microbial mineralization rates. Our work indicates that even short-term shifts in antecedent moisture conditions can strongly influence soil C dynamics at the core scale. The predictive uncertainties in current soil models may be reduced by a more accurate representation of soil water and C persistence that includes a mechanistic and quantitative understanding of the impact of antecedent moisture conditions.This dataset contains a compressed (.zip) archive of the data and R scripts used for this manuscript. The dataset includes files in .csv and .txt format, which can be accessed and processed using MS Excel or R. NMR data are provided as raw output data (accessed in Bruker TopSpin or MestreNova) as well as the MestreNova-processed files. This archive can also be accessed on GitHub at https://github.com/kaizadp/hysteresis_and_soil_carbon (DOI: 10.5281/zenodo.4432885).

1H-NMR↗