Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Generation limits”

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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Evaluating Precipitation Features and Rainfall Characteristics in a Multi-scale Modeling Framework

Cloud and precipitation systems over the tropics and subtropics are simulated with a multi-scale modeling framework (MMF) and compared against the TRMM radar precipitation features (RPFs) product. A methodology, in close analogy to the TRMM RPFs, is developed to analyze simulated cloud precipitating structures from the embedded two-dimensional cloud-resolving models (CRMs) within an MMF. Despite the two-dimensionality of the CRMs, the simulated RPFs population distribution, and horizontal and vertical structure are in good agreement with TRMM observations. However, some deficits are also found in the model simulations. The model tends to overestimate mean convective precipitation rates for RPFs with a size less than 100 km, contributing to the excessive precipitation biases in the warm pool and western Pacific, western and northern India Ocean, and eastern Pacific commonly found in most MMFs. For large features with a size greater than 150 km, both convective and stratiform rain rates are underestimated. The distribution of maximum radar echo top heights as a function of RPF size is well simulated except the model tends to underestimate the occurrence frequency of maximum heights greater than 15 km. The maximum echo top heights for convective cells embedded within large RPFs with a size greater than 150 km are also underestimated. The cyclic lateral boundary with a limited model domain generates artificial occurrences for RPFs with a size close to the model domain size, producing a significant contribution to the total rainfall due to their sizes. This cyclic lateral boundary effect can be easily identified and quantified in both probability and cumulative distribution functions of RPFs. The geophysical distribution of the population of the largest RPFs in the control experiment shows they are mainly located in the Subtropics but also partially contribute to the common MMF biases of excessive precipitation in the Tropics. Sensitivity experiments using CRMs with different domain sizes and different grid spacings show larger domains (higher resolution) tend to shift the RPFs distribution to large (small) sizes. The cyclic lateral boundary biases increase as CRM domain size decreases. The impacts of model horizontal and vertical resolution on simulated convective systems are also investigated.

Chern, Jiun-Dar↗
NASA NTRSDate not supplied

Overview of A Survey Methods Test for the NASA Quesst Community Survey Campaign

In its mission to expand knowledge and improve aviation, NASA conducts research to address sonic boom noise, the prime barrier to overland supersonic flight. NASA is currently preparing for a community survey campaign to assess response to noise from the new X-59 aircraft. During each community survey, a substantial number of observations must be collected over a limited timeframe to generate a dose response relationship. A sample of residents will be recruited in advance to fill out a brief survey each time X-59 flies over, approximately 80 times throughout a month. In preparation NASA conducted a month-long test of survey methods in 2023. A sample of 800 residents was recruited from a simulated fly-over area. Because there were no actual X-59 fly-overs, respondents were asked about their reactions to noise from normal aircraft operations. The respondents chose whether to fill out the survey on the web or via a smartphone application. Evaluating response rates and how they evolved over time was a specific focus of the test. Also, a graduated incentive structure was implemented to keep respondents engaged. Finally, location data was collected from respondents since it will be needed to estimate individual noise exposure from X-59. The results of this survey test will help determine the design of the community survey campaign.

Sonic boom↗
NASA NTRS1998

g-LIMIT: A Vibration Isolation System for the Microgravity Science Glovebox

For many microgravity science experiments using the Microgravity Science Glovebox (MSG), the ambient acceleration environment will exceed desirable levels. To provide a more quiescent acceleration environment, a vibration isolation system named g-LIMIT (GLovebox Integrated Microgravity Isolation Technology) is being designed. g-LIMIT is the next generation of technology developed for and demonstrated by STABLE on the USML-2 mission in October 1995. Although g-LIMIT is a sub-rack level isolation system that can be used in a variety of applications, g-LIMIT is uniquely optimized for MSG implementation. Standard MSG structural and umbilical interfaces will be used so that the isolation mount is transparent to the user with no additional accommodation requirements. g-LIMIT consists of three integrated isolator modules, each of which is comprised of a dual axis actuator, two axes of acceleration sensing, two axes of position sensing, control electronics, and data transmission capabilities in a minimum-volume package. In addition, this system provides the unique capability for measuring absolute acceleration of the experiment independent of accelerometers as a by-product of the control system and will have the capability of generating pristine accelerations to enhance experiment operations. g-LIMIT is scheduled for flight during the UF-2 mission and will be available to glovebox investigators immediately after characterization testing.

Whorton, Mark S.↗
NASA NTRS1993

EOS attitude determination and next generation star tracker enhancements

The pointing knowledge required for the Earth Observing System (EOS) AM mission is at the limit of the current generation of star trackers, with little margin. Techniques for improving the performance of existing star trackers are explored, with performance sensitivities developed for each alternative. These are extended to define the most significant performance enhancements for a next generation star tracker. Since attitude determination studies tend to be computationally intensive, an approach for using a simpler one degree of freedom formulation is contrasted with a full three degree of freedom formulation. Additionally, covariance analysis results are compared with time domain simulation performance results.

Kudva, P.↗
NASA NTRS2018

A Concept for Civil Space Traffic Management

As technology has improved, operators have sought to use cubesats, as well as smallsats more generally, to perform increasingly more ambitious and sophisticated functions. Despite this, practical concerns associated with cubesat infant mortality, conjunctions, limited maneuverability, and debris generation have been relatively muted because most cubesats have been launched to lower orbits that limit both their orbital lifetime and consequences should a collision occur. NASA ARC has developed a concept for a highly-automated and distributed space traffic management (STM) architecture, drawing on similar work done to provide traffic management for small unmanned aerial systems (UAS) operating at low altitudes. The system proposes a strategy to accommodate growing space traffic volume safely, as well as pave the way for a transition of civil STM authority to a civilian governmental entity. The architecture envisions an open-access software platform architecture of data and service suppliers, consumers, and regulators, connected via a set of application programming interfaces (APIs). The platform would build on, rather than replicate existing integration and coordination efforts within the space situational awareness ecosystem, using existing standards for data message formats from organizations like the Consultative Committee for Space Data Systems and wrapping, rather than replacing existing integrations. We will present an initial STM architecture in this presentation, with a few examples showing how stakeholders can interact structurally, but flexibly, within this architecture.

Space Situational Awareness↗
NASA NTRSDate not supplied

Transcriptomics-based Machine Learning Analysis Predicts Space-Exposed Murine Livers

Limited sample sizes, high data dimensionality, and sensitivity to technical and biological variability of next generation sequencing (NGS), typically limits machine learning (ML) approaches in spaceflight studies that include radiation effects. However, pooling smaller studies while addressing intra- and inter-study variabilities allows for ML predictive modeling. Here, integration methods were applied to whole transcriptome shotgun sequencing (RNA-seq) data from six mouse liver GeneLab datasets (GLDS) (n ranging from 6 to 39 samples) from with a total of 81 spaceflight and ground-control samples to determine top features (i.e. genes) relevant to spaceflight including the effect of radiation exposure. RNASeq counts were normalized for each study, then merged and scaled across all datasets. Data dimensionality was reduced using a minimum redundancy maximum relevance (MRMR) methodology. Redundancy and relevance were computed using the Pearson correlation and F-statistic, respectively. The top 100 MRMR features were used to predict spaceflight vs. ground-control samples using Random Forest (RF), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA) classifiers with 5-fold cross validation (CV). Principal component analysis (PCA) on the complete feature set versus the MRMR features shows separation between spaceflight samples and ground controls (Figure 1A). The ML-based gene sets were compared against differential gene expression results obtained with DESeq2 from individual GLDS. Using all features or randomly sampled subsets at matching set sizes with MRMR, a maximum classifier accuracy of 69% was shown on the test set over 5 folds. For all classifiers, CV training using at least the top 30 MRMR genes show minimum 89% accuracy and 0.95 AUC value on the test set over 5 folds (Figure 1B). Baseline set analysis on differentially expressed genes (DEGs) identified using padj ≤ 0.05 show 295 DEGs that overlap at least two studies and 13 DEGs that overlap three studies (Figure 1C). Set analysis between the top 100 MRMR features and the DEGs showed 47 genes that overlap at least one study and 24 genes that overlap two studies. Over-representation analysis showed overlapping biological processes related to fatty acid and lipid metabolism which may indicate these processes in the response to spaceflight stressors. MRMR feature selection for the selected ML methods improve performance relative to a classifier built on all features or randomly sampled subsets. Permutation feature importance within the decorrelated MRMR features showed concordance in feature ranking between ML methods. A challenge of applying ML methods across heterogeneous NGS data is accounting for signal:noise. Here, signal validation across studies was shown by intersecting sets between top MRMR genes and DEGs from DESeq2 analysis. Non-intersecting sets introduce opportunity to explore genes relevant to differentiating space flight exposed groups and implementing ML methods across existing NGS datasets may overcome sample size limitations.

Machine Learning↗
NASA NTRSDate not supplied

Transcriptomics-based Machine Learning (ML) Analysis Predicts Space-Exposed Murine Livers

Limited sample sizes, high data dimensionality, and sensitivity to technical and biological variability of next generation sequencing (NGS), typically limits machine learning (ML) approaches in spaceflight studies that include radiation effects. However, pooling smaller studies while addressing intra- and inter-study variabilities allows for ML predictive modeling. Here, integration methods were applied to whole transcriptome shotgun sequencing (RNA-seq) data from six mouse liver GeneLab datasets (GLDS) (n ranging from 6 to 39 samples) from with a total of 81 spaceflight and ground-control samples to determine top features (i.e. genes) relevant to spaceflight including the effect of radiation exposure. RNASeq counts were normalized for each study, then merged and scaled across all datasets. Data dimensionality was reduced using a minimum redundancy maximum relevance (MRMR) methodology. Redundancy and relevance were computed using the Pearson correlation and F-statistic, respectively. The top 100 MRMR features were used to predict spaceflight vs. ground-control samples using Random Forest (RF), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA) classifiers with 5-fold cross validation (CV). Principal component analysis (PCA) on the complete feature set versus the MRMR features shows separation between spaceflight samples and ground controls (Figure 1A). The ML-based gene sets were compared against differential gene expression results obtained with DESeq2 from individual GLDS. Using all features or randomly sampled subsets at matching set sizes with MRMR, a maximum classifier accuracy of 69% on the test set over 5 folds. For all classifiers, CV training using at least the top 30 MRMR genes show minimum 89% accuracy and 0.95 AUC value on the test set over 5 folds (Figure 1B). Baseline set analysis on differentially expressed genes (DEGs) identified using padj ≤ 0.05 show 295 DEGs that overlap at least two studies and 13 DEGs that overlap three studies (Figure 1C). Set analysis between the top 100 MRMR features and the DEGs showed 47 genes that overlap at least one study and 24 genes that overlap two studies. Over-representation analysis showed overlapping biological processes related to fatty acid and lipid metabolism which may indicate these processes in the response to spaceflight stressors. MRMR feature selection for the selected ML methods improve performance relative to a classifier built on all features or randomly sampled subsets. Permutation feature importance within the decorrelated MRMR features showed concordance in feature ranking between ML methods. A challenge of applying ML methods across heterogeneous NGS data is accounting for signal:noise. Here, signal validation across studies was shown by intersecting sets between top MRMR genes and DEGs from DESeq2 analysis. Non-intersecting sets introduce opportunity to explore genes relevant to differentiating space flight exposed groups and implementing ML methods across existing NGS datasets may overcome sample size limitations.

Machine Learning↗
NASA NTRSDate not supplied

Transcriptomics-based Machine Learning Analysis Predicts Space-Exposed Murine Livers

Limited sample sizes, high data dimensionality, and sensitivity to technical and biological variability of next generation sequencing (NGS), typically limits machine learning (ML) approaches in spaceflight studies that include radiation effects. However, pooling smaller studies while addressing intra- and inter-study variabilities allows for ML predictive modeling. Here, integration methods were applied to whole transcriptome shotgun sequencing (RNA-seq) data from six mouse liver GeneLab datasets (GLDS) (n ranging from 6 to 39 samples) from with a total of 81 spaceflight and ground-control samples to determine top features (i.e. genes) relevant to spaceflight including the effect of radiation exposure. RNASeq counts were normalized for each study, then merged and scaled across all datasets. Data dimensionality was reduced using a minimum redundancy maximum relevance (MRMR) methodology. Redundancy and relevance were computed using the Pearson correlation and F-statistic, respectively. The top 100 MRMR features were used to predict spaceflight vs. ground-control samples using Random Forest (RF), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA) classifiers with 5-fold cross validation (CV). Principal component analysis (PCA) on the complete feature set versus the MRMR features shows separation between spaceflight samples and ground controls (Figure 1A). The ML-based gene sets were compared against differential gene expression results obtained with DESeq2 from individual GLDS. Using all features or randomly sampled subsets at matching set sizes with MRMR, a maximum classifier accuracy of 69% was shown on the test set over 5 folds. For all classifiers, CV training using at least the top 30 MRMR genes show minimum 89% accuracy and 0.95 AUC value on the test set over 5 folds (Figure 1B). Baseline set analysis on differentially expressed genes (DEGs) identified using padj ≤ 0.05 show 295 DEGs that overlap at least two studies and 13 DEGs that overlap three studies (Figure 1C). Set analysis between the top 100 MRMR features and the DEGs showed 47 genes that overlap at least one study and 24 genes that overlap two studies. Over-representation analysis showed overlapping biological processes related to fatty acid and lipid metabolism which may indicate these processes in the response to spaceflight stressors. MRMR feature selection for the selected ML methods improve performance relative to a classifier built on all features or randomly sampled subsets. Permutation feature importance within the decorrelated MRMR features showed concordance in feature ranking between ML methods. A challenge of applying ML methods across heterogeneous NGS data is accounting for signal:noise. Here, signal validation across studies was shown by intersecting sets between top MRMR genes and DEGs from DESeq2 analysis. Non-intersecting sets introduce opportunity to explore genes relevant to differentiating space flight exposed groups and implementing ML methods across existing NGS datasets may overcome sample size limitations.

Machine Learning↗
NASA NTRS1982

NASA Deep Space Network performance analysis

As part of the Control Center Operations, the Performance Analysis Group has responsibility for validating all committed Deep Space Network support to the various user projects. The group provides the Network with the analysis support necessary to assure that actual Network performance meets or exceeds committed levels throughout the mission. Validation is carried out as the signals are received in real time by monitoring the data streams and comparing the data quality against predicted values and established performance standards and tolerance limits. An important function is to generate the predictions used to point the antennas, acquire the radio frequency, and validate the monitored Network performance. Another function is anomaly investigation. An integral part of validation is the support task of generating and maintaining performance standards and tolerance limits for each flight project. The Performance Analysis Group is broadly divided into two subgroups: real-time personnel and nonreal-time personnel.

Bartok, C. D.↗
NASA NTRS2004

Detecting Organic Compounds in Martian Soil Analogues Using Gas Chromatography Mass Spectrometry

One of the primary objectives of the 1976 Viking missions was to determine whether organic compounds, possibly of biological origin, were present in the Martian surface soils. The Viking gas chromatography mass spectrometry (GCMS) instruments found no evidence for any organic compounds of Martian origin above a few parts per billion in the upper 10 cm of surface soil [l], suggesting the absence of a widely distributed Martian biota. However, Benner et d. have suggested that significant amounts of non-volatile organic compounds, possibly including oxidation products of bioorganic molecules (e.g. carboxylic acids) would not have been detected by the Viking GCMS [2]. Moreover, other key organic compounds important to biology, such as amino acids and nucleobases, would also likely have been missed by the Viking GCMS as these compounds require chemical derivatization to be stable in a GC column [3]. Recent pyrolysis experiments with a Mars soil analogue that had been innoculated with Escherichia coli bacteria have shown that amino acid decomposition products (amines) and nucleobases are among the most abundant products generated after pyrolysis of the bacterial cells [4,5]. At the part per billion level (Viking GCMS detection limit), these pyrolysis products generated from several million bacterial cells per gram of Martian soil would not have been detected by the Viking GCMS instruments [4]. Analytical protocols are under development for upcoming in situ lander opportunities to target several important biological compounds including amino acids and nucleobases. For example, extraction and chemical derivatization techniques [3] are being adapted for space flight use to transform reactive or fragile molecules that would not have been detected by the Viking GCMS instruments, into species that are sufficiently volatile to be detected by GCMS. Recent experiments carried out at NASA Goddard have shown that using this derivatization technique all of the targeted compounds mentioned above can be separated on a GC column and detected by MS at sub-picomole (< 10(exp -l2 mole) levels. With these methods, the detection limit for amino acids, carboxylic acids and nucleobases is several orders of magnitude more sensitive than the Viking GCMS instruments for these compounds. Preliminary results using this analytical technique on a variety of Martian soil analogues will be presented.

Glavin, D. P.↗
NASA NTRS1994

Computational analysis of forebody tangential slot blowing on the high alpha research vehicle

Current and future fighter aircraft can maneuver in the high-angle-of-attack flight regime while flying at low subsonic and transonic freestream Mach numbers. However, at any flight speed, the ability of the vertical tails to generate yawing moment is limited in high-angle-of-attack flight. Thus, any system designed to provide the pilot with additional side force and yawing moment must work in both low subsonic and transonic flight. However, previous investigations of the effectiveness of forebody tangential slot blowing in generating the desired control forces and moments have been limited to the low subsonic freestream flow regime. In order to investigate the effectiveness of tangential slot blowing in transonic flight, a computational fluid dynamics analysis was carried out during the grant period. Computational solutions were obtained at three different freestream Mach numbers and at various jet mass flow ratios. All results were obtained using the isolated F/A-18 forebody grid geometry at 30.3 degrees angle of attack. One goal of the research was to determine the effect of freestream Mach number on the effectiveness of forebody tangential slot blowing in generating yawing moment. The second part of the research studied the force onset time lag associated with blowing. The time required for the yawing moment to reach a steady-state value from the onset of blowing may have an impact on the implementation of a pneumatic system on a flight vehicle.

Gee, Ken↗
NASA NTRS1980

Ion beams from laser-generated plasmas

The paper describes the space-charge-limited beams produced by the plasma blowoffs generated by 20-MW bursts of 1.06-micron radiation from an active Q-switched Nd:YAG laser. Laser power densities near 10 to the 11th/sq cm on solid targets generate thermalized plasma plumes which drift to a 15-kV gridded extraction gap where the ions are extracted, accelerated, and electrostatically focused; the spatially defined ion beams are then magnetically analyzed to determine the charge state content in the beams formed from carbon, aluminum, copper, and lead targets. This technique preserves time-of-flight (TOF) information in the plasma drift region, which permits plasma ion temperatures and mass flow velocities to be determined from the Maxwellian ion curve TOF shapes for the individual charge species.

Hughes, R. H.↗
NASA NTRS1996

Parametric Amplification For Detecting Weak Optical Signals

Optical-communication receivers of proposed type implement high-sensitivity scheme of optical parametric amplification followed by direct detection for reception of extremely weak signals. Incorporates both optical parametric amplification and direct detection into optimized design enhancing effective signal-to-noise ratios during reception in photon-starved (photon-counting) regime. Eliminates need for complexity of heterodyne detection scheme and partly overcomes limitations imposed on older direct-detection schemes by noise generated in receivers and by limits on quantum efficiencies of photodetectors.

Hemmati, Hamid↗
NASA NTRS1990

Development of a two photon/laser induced fluorescence technique for the detection of atmospheric OH radicals

The development of a new mid-IR laser source was the primary goal. Backward propagating stimulated D2 Raman frequency down conversion of a commercially available 1.06 micron Nd:YAG laser was shown to generate an efficient source of 1.56 micron radiation with near diffraction limited beam quality. The efficient generation of a 2.9 micron laser source was also achieved using backward propagating CH4 Raman frequency down conversion of the 1.56 micron pump. Slightly higher efficiencies were obtained for frequency down conversion of the 1.06 micron Nd:YAG using the H2 Raman shift yielding a near diffraction limited source in the 200 mJ range at 1.9 micron. Similar conversion efficiencies are anticipated as a result of extending the wavelength coverage of recently available Ti:sapphire pulse laser to not only cover the 740 to 860 nm fundamental wavelength range but also the .95 to 1.15 and 1.06 to 1.33 micron range using D2 and H2, respectively. The anticipated sensitivity of a TP-LIF OH sensor using this mid-IR source would give signal limited detection of 1.4 x 10(exp 5) OH/cu cm under boundary layer conditions and 5.5 x 10(exp 4) OH/cu cm under free troposphere sampling conditions for a five minute signal integration period. This level of performance coupled with the techniques non-perturbing nature and freedom from both interferences and background would allow reliable tropospheric OH measurement to be obtained under virtually any ambient condition of current interest, including interstitial and sampling.

Bradshaw, John↗
NASA NTRS1990

The selection of convertible engines with current gas generator technology for high speed rotorcraft

NASA-Lewis sponsored two studies to determine the most promising convertible engine concepts for high speed rotorcraft. These studies projected year 2000 convertible technology limited to present gas generator technology. Propulsion systems for utilization on aircraft needing thrust only during cruise and those aircraft needing both power and thrust at cruise were investigated. Mission calculations for the two contractors involved were based upon the fold tilt rotor concept. Analysis and comparison of the General Electric concepts (geared UDF, clutched fan, and Variable Inlet Guide Vane (VIGV) fan), and the Allison Gas Turbine concepts (clutched fan, VIGV fan, variable pitch fan, single rotation tractor propfan, and counter rotation tractor propfan) are presented.

Eisenberg, Joseph D.↗
NASA NTRS1990

The selection of convertible engines with current gas generator technology for high speed rotorcraft

NASA-Lewis has sponsored two studies to determine the most promising convertible engine concepts for high speed rotorcraft. These studies projected year 2000 convertible technology limited to present gas generator technology. Propulsion systems for utilization on aircraft needing thrust only during cruise and those aircraft needing both power and thrust at cruise were investigated. Mission calculations for the two contractors involved were based upon the fold tilt rotor concept. Analysis and comparison of the General Electric concepts (geared UDF, clutched fan, and VIGV fan), and the Allison Gas Turbine concepts (clutched fan, VIGV fan, variable pitch fan, single rotation tractor propfan, and counter rotation tractor propfan) are presented.

Eisenberg, Joseph D.↗
NASA NTRS1972

Pseudorandom noise for telemetry error rate measurement applications and limitations.

A pseudorandom noise (PRN) generator functional design has been developed which is superior to the commercially available instrument in usable bandwidth and in the closeness of fit to the gaussian probability distribution in the 'tails' of the curve. The principal disadvantage of PRN sources for bit error rate (BER) measurements is that the probability distribution is truncated in the tails. This truncation of the probability distribution results in a similar truncation of the BER curve - i.e., there is a minimum BER which can be measured, below which the only possible result is zero. The minimum nonzero BER actually computed with the PRN source developed was 0.00001 with a pseudorandom sequence of 131,071 bits. It is theoretically possible, with a longer sequence, to achieve a minimum BER of 0.000001 with the same design.

Hopkins, P. M.↗
NASA NTRS2009

Improved Efficiency Type II Second Harmonic Generation

Second harmonic efficiency is limited by lateral and temporal separation of the ordinary and extraordinary components of the fundamental. A mode locked dual beam laser demonstrated these effects and a novel method to minimize them.

Barnes, Norman P.↗