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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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At least 739 records · Page 41

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NASA NTRS1995

Attitude determination using an adaptive multiple model filtering Scheme

Attitude determination has been considered as a permanent topic of active research and perhaps remaining as a forever-lasting interest for spacecraft system designers. Its role is to provide a reference for controls such as pointing the directional antennas or solar panels, stabilizing the spacecraft or maneuvering the spacecraft to a new orbit. Least Square Estimation (LSE) technique was utilized to provide attitude determination for the Nimbus 6 and G. Despite its poor performance (estimation accuracy consideration), LSE was considered as an effective and practical approach to meet the urgent need and requirement back in the 70's. One reason for this poor performance associated with the LSE scheme is the lack of dynamic filtering or 'compensation'. In other words, the scheme is based totally on the measurements and no attempts were made to model the dynamic equations of motion of the spacecraft. We propose an adaptive filtering approach which employs a bank of Kalman filters to perform robust attitude estimation. The proposed approach, whose architecture is depicted, is essentially based on the latest proof on the interactive multiple model design framework to handle the unknown of the system noise characteristics or statistics. The concept fundamentally employs a bank of Kalman filter or submodel, instead of using fixed values for the system noise statistics for each submodel (per operating condition) as the traditional multiple model approach does, we use an on-line dynamic system noise identifier to 'identify' the system noise level (statistics) and update the filter noise statistics using 'live' information from the sensor model. The advanced noise identifier, whose architecture is also shown, is implemented using an advanced system identifier. To insure the robust performance for the proposed advanced system identifier, it is also further reinforced by a learning system which is implemented (in the outer loop) using neural networks to identify other unknown quantities such as spacecraft dynamics parameters, gyro biases, dynamic disturbances, or environment variations.

Lam, Quang↗

NASA NTRS1998

Analysis of a Rocket Based Combined Cycle Engine during Rocket Only Operation

The all rocket mode of operation is a critical factor in the overall performance of a rocket based combined cycle (RBCC) vehicle. However, outside of performing experiments or a full three dimensional analysis, there are no first order parametric models to estimate performance. As a result, an axisymmetric RBCC engine was used to analytically determine specific impulse efficiency values based upon both full flow and gas generator configurations. Design of experiments methodology was used to construct a test matrix and statistical regression analysis was used to build parametric models. The main parameters investigated in this study were: rocket chamber pressure, rocket exit area ratio, percent of injected secondary flow, mixer-ejector inlet area, mixer-ejector area ratio, and mixer-ejector length-to-inject diameter ratio. A perfect gas computational fluid dynamics analysis was performed to obtain values of vacuum specific impulse. Statistical regression analysis was performed based on both full flow and gas generator engine cycles. Results were also found to be dependent upon the entire cycle assumptions. The statistical regression analysis determined that there were five significant linear effects, six interactions, and one second-order effect. Two parametric models were created to provide performance assessments of an RBCC engine in the all rocket mode of operation.

Smith, T. D.↗

NASA NTRS1999

Random Dopant Induced Threshold Voltage Lowering and Fluctuations in Sub 50 nm MOSFETs: a Statistical 3D 'Atomistic' Simulation Study

A 3D 'atomistic' simulation study of random dopant induced threshold voltage fluctuations and lowering in sub 50 nm MOSFETs is presented. The attention is focused mainly on devices with 30 nm effective channel length which represent the expected level of scaling at the end of the Silicon Roadmap. An efficient algorithm, based on a single 3D ap solution of the Poisson equation and a simplified current continuity equation, is used in the simulations. Large samples of microscopically different devices (typically 200) arc used in order to obtain statistically reliable results. The influence of different aspects of the conventional MOSFET design on the threshold voltage fluctuations and lowering are investigated. Results for fluctuation resistant device architectures based on low-doped epitaxial channel MOSFETs are also presented.

Asenov, Asen↗

NASA NTRS2015

Statistics Examples from Kennedy Space Center and Cape Canaveral Air Force Station

A few examples of projects in meteorology and engineering that used statistics at Kennedy Space Center and Cape Canaveral Air Force Station.

Statistics↗

NASA NTRSDate not supplied

The Return of the ICPS: A Statistical Perspective on Artemis Upper Stage Disposal

Prior to the launch of Artemis I, it was discovered that the Interim Cryogenic Propulsion Stage (ICPS) of the Space Launch System may not dispose heliocentrically as intended. This paper summarizes the results of an investigation which looked into why the ICPS may return in less than a year for certain Launch Days. Evidence is presented showing the ICPS mimics the behavior of known Three-Body Periodic Orbits for certain Sun-Earth geometries. This paper discusses the primary mechanisms causing ICPS to return, describes the statistics of these returns, and also discusses interactions between Artemis I mission design and the lunar month.

W B Stein↗

NASA NTRSDate not supplied

The Return of the ICPS: A Statistical Perspective on Artemis Upper Stage Disposal

W. B. Stein↗

DOE OSTI2025

System Engineers and Decisions: It?s All about Knowledge

In order to guarantee that a system meets adequate levels of reliability and availability, system performances are continuously monitored and analyzed thanks to the technological advancements driving the Industry 4.0 revolution. An Industry 4.0 approach is typically based on advanced statistical, big data mining, machine learning, and internet-of-things methods designed to detect anomalies in the behavior of system, detect the most likely failure modes, and provide indications to system engineers on when maintenance activities should be performed before system performance are deemed unacceptable (which can be generated by diagnostic and prognostic methods). However, these analyses, which are designed to automatize and increase the efficacy of the system maintenance program, require large amount of data which can come in various forms: numeric, textual, images, sounds etc. Such data constitutes the historic knowledge benchmark to track system performances and support system engineer decisions. Here we claim that data is not sufficient to support this kind of analyses when applied to systems characterized by complex architectures and behaviors. Robust system engineer decisions require the ability to understand the system operational context that lies behind the observed data elements. In this respect, system models are in fact necessary to “put data in context” and capture relationships between data elements. Industry 4.0 methods require in fact contextual knowledge as a basis upon which hypotheses can be generated and assumptions tested. In our view, for complex systems, model-based system engineering (MBSE) models can afford this contextual knowledge, as they are typically used to describe systems architecture and dynamic behaviors. System knowledge is here intended as the blending of collected data and system architecture which takes the form of a “knowledge graph”. A knowledge graph is a database which consists of a large set of nodes (in our case an entity can be either a data or an MBSE element) which are linked to each other. The types of nodes and links follow a pre-defined topology, sometimes also refers as an ontology, that is designed to fit the actual decisions that needs to be performed. We show here how a knowledge graph can be defined to support system engineer maintenance decisions and how the same graph can be built based on system MBSE models and pre-processed data from numeric (through anomaly detections and diagnostic methods) and textual elements (through technical language processing TLP).

97 - MATHEMATICS AND COMPUTING↗

NASA NTRS1985

Star formation in grand design and flocculent spiral galaxies

An examination is conducted of the colors and neutral hydrogen contents of spiral galaxies which have been classified in the Elmegreen and Elmegreen arm morphology system. Using these data, possible differences between the star formation activity in spiral galaxies with and without classic spiral arms are delineated. At the same revised Hubble type, spiral galaxies with regular global arm patterns (the grand design spirals) are bluer than spiral galaxies lacking such patterns (the flocculent spirals) by a small, but statistically significant amount (approximately 0.05 in B-V and approximately 0.15 in U-V). The neutral hydrogen contents of the two groups are roughly similar, implying the star formation rate averaged over a Hubble time has been approximately the same in grand design and flocculent systems. The color differences can be explained either by using an initial mass function in the flocculent spiral galaxies which is deficient in massive stars by a factor of 2 compared with the grand design systems, or by a decrease of 30 percent in the ratio of recent to past star formation rates in flocculent galaxies. The possibility is discussed that systematic Hubble type misclassifications significantly affect these conclusions.

Romanishin, W.↗

DOE OSTI2023

Sequence Design of Random Heteropolymers as Protein Mimics

Random heteropolymers (RHPs) have been computationally designed and experimentally shown to recapitulate protein-like phase behavior and function. However, unlike proteins, RHP sequences are only statistically defined and cannot be sequenced. Recent developments in reversible-deactivation radical polymerization allowed simulated polymer sequences based on the well-established Mayo–Lewis equation to more accurately reflect ground-truth sequences that are experimentally synthesized. This led to opportunities to perform bioinformatics-inspired analysis on simulated sequences to guide the design, synthesis, and interpretation of RHPs. We compared batches on the order of 10000 simulated RHP sequences that vary by synthetically controllable and measurable RHP characteristics such as chemical heterogeneity and average degree of polymerization. Our analysis spans across 3 levels: segments along a single chain, sequences within a batch, and batch-averaged statistics. We discuss simulator fidelity and highlight the importance of robust segment definition. Examples are presented that demonstrate the use of simulated sequence analysis for in-silico iterative design to mimic protein hydrophobic/hydrophilic segment distributions in RHPs and compare RHP and protein sequence segments to explain experimental results of RHPs that mimic protein function. To facilitate the community use of this workflow, the simulator and analysis modules have been made available through an open source toolkit, the RHPapp.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRSDate not supplied

A Framework for Software Health Management Using Bayesian Statistics

Software Health Management (SWHM) must make sure that the software always remains in safe and healthy regions of the state space. Boundaries between healthy and unhealthy regions are important for the detection of violations and health management.In this position paper, we present a framework, which employs techniques from Bayesian statistical modeling and active learning to efficiently characterize health boundaries in high-dimensional spaces. We will discuss, how this framework supports SWHM during design time and during operation of learning/adapting software systems

software health management↗

DOE OSTI2025

Stokes-dependent droplet collection efficiency on a NACA 0012 airfoil from droplet-informed simulations with statistical overloading

Accurate modelling of ice accretion on aircraft wings requires analysing droplet impingement on the surface to optimize the design of ice-protection systems. We perform Euler–Lagrange simulations of a droplet-laden flow impinging on a NACA 0012 airfoil. Our study includes water droplets with eight discrete sizes ranging from 1 to 160 microns. We vary the free-stream velocity of the incoming airflow in the range 60 ≤ U ≤ 240 m s −1 and the chord length of the airfoil in the range 0.5 ≤ c ≤ 2 m. Due to the dilute nature of supercooled clouds, one-way coupling is used in the simulations. The effects of droplet breakup and collision are also neglected. To reduce the computational cost, we employ statistical overloading of droplets, allowing us to simulate millions of impinging droplets in a time span on the order of milliseconds. Our results show that the droplet collection efficiency, which measures the likelihood of droplet impingement on the airfoil surface, increases with droplet size and free-stream velocity but decreases with airfoil size. We demonstrate that collection efficiency, impingement velocity and impingement angle are primarily dictated by a single non-dimensional parameter, the droplet Stokes number. We also identify a critical stagnation-streamline Stokes number below which impingements do not occur and use it to estimate the minimum droplet size for impingement. In addition, we observe droplet behaviour to become Stokes number independent at large values of the Stokes number. This article is part of the theme issue ‘Heat and mass transfer in frost and ice’.

Science & Technology - Other Topics↗

DOE OSTI2025

PNNL-Predictive-Phenomics/ProteoMeter

ProteoMeter is a Python package that assists in the statistical analysis of global proteomics, protein post-translation modification (PTM), and limited proteolysis (LiP) data. It contains batch correction, normalization, and statistical testing methods, as well as functions that "roll up" peptide-level data to the single-site level. It has a robust user configuration system, allowing it to flexibly integrate different types of experiment designs. For basic usage, a simple configuration file provides the essential functionality. Advanced users have access to the entire statistical pipeline for fine-tuning analyses. Processed data is easily exported to many common spreadsheet and data-frame formats.

Rozum, Jordan [Pacific Northwest National Lab]↗

NASA NTRS1991

A statistical model of carbon/carbon composite failure

A failure model which considers the stochastic nature of the damage accumulation process is essential to assess reliability and to accurately scale the results from standard test specimens to composite structures. A superior filamentary composite for high temperature applications is composed of carbon fibers in a carbon matrix. Carbon-carbon composites are the strongest known material at very high temperatures. Since there appears to be a significant randomness in C-C material strength which cannot be controlled or detected with current technology, a better model of the material failure based upon statistical principles should be used. Simple applications of the model based upon the limited data provide encouraging results that indicate that better design of test specimens would provide a substantially higher prediction for the design strength of C-C composites. An A-basis strength for the C-C tensile rings from a first stage D-5 billets was estimated. A statistical failure model was developed for these rings which indicates that this strength may be very conservative for larger C-C parts. The analysis may be improved by use of a heterogeneous/noncontinuum finite element approach on the minimechanical level.

Slattery, Kerry T.↗

NASA NTRS2007

A Comparison of Two Balance Calibration Model Building Methods

Simulated strain-gage balance calibration data is used to compare the accuracy of two balance calibration model building methods for different noise environments and calibration experiment designs. The first building method obtains a math model for the analysis of balance calibration data after applying a candidate math model search algorithm to the calibration data set. The second building method uses stepwise regression analysis in order to construct a model for the analysis. Four balance calibration data sets were simulated in order to compare the accuracy of the two math model building methods. The simulated data sets were prepared using the traditional One Factor At a Time (OFAT) technique and the Modern Design of Experiments (MDOE) approach. Random and systematic errors were introduced in the simulated calibration data sets in order to study their influence on the math model building methods. Residuals of the fitted calibration responses and other statistical metrics were compared in order to evaluate the calibration models developed with different combinations of noise environment, experiment design, and model building method. Overall, predicted math models and residuals of both math model building methods show very good agreement. Significant differences in model quality were attributable to noise environment, experiment design, and their interaction. Generally, the addition of systematic error significantly degraded the quality of calibration models developed from OFAT data by either method, but MDOE experiment designs were more robust with respect to the introduction of a systematic component of the unexplained variance.

DeLoach, Richard↗

NASA NTRS1981

Exceedance statistics of accelerations resulting from thruster firings on the Apollo-Soyuz mission

Spacecraft acceleration resulting from firings of vernier control system thrusters is an important consideration in the design, planning, execution and post-flight analysis of laboratory experiments in space. In particular, scientists and technologists involved with the development of experiments to be performed in space in many instances required statistical information on the magnitude and rate of occurrence of spacecraft accelerations. Typically, these accelerations are stochastic in nature, so that it is useful to characterize these accelerations in statistical terms. Statistics of spacecraft accelerations are summarized.

Fichtl, G. H.↗

NASA NTRS1983

Exceedance statistics of accelerations resulting from thruster firings on the Apollo-Soyuz mission

Fichtl, G. H.↗

DOE OSTI2020

Size-dependent stochastic tensile properties in additively manufactured 316L stainless steel

Recent work in metal additive manufacturing (AM) suggests that mechanical properties may vary with feature size; however, these studies do not provide a statistically robust description of this phenomenon, nor do they provide a clear causal mechanism. Because of the huge design freedom afforded by 3D printing, AM parts typically contain a range of feature sizes, with particular interest in smaller features, so the size effect must be well understood in order to make informed design decisions. This work investigates the effect of feature size on the stochastic mechanical performance of laser powder bed fusion tensile specimens. A high-throughput tensile testing method was used to characterize the effect of specimen size on strength, elastic modulus and elongation in a statistically meaningful way. The effective yield strength, ultimate tensile strength and modulus decreased strongly with decreasing specimen size: all three properties were reduced by nearly a factor of two as feature dimensions were scaled down from 6.25 mm to 0.4 mm. Hardness and microstructural observations indicate that this size dependence was not due to an intrinsic change in material properties, but instead the effects of surface roughness on the geometry of the specimens. Finite element analysis using explicit representations of surface topography shows the critical role surface features play in creating stress concentrations that trigger deformation and subsequent fracture. The experimental and finite element results provide the tools needed to make corrections in the design process to more accurately predict the performance of AM components.

316L stainless steel↗

NASA NTRS2007

The X-43A Flight Research Program: Lessons Learned on the Road to Mach 10

During an aerospace engineer's undergraduate studies, he or she will attend classes in aerodynamics, thermodynamics, structures, stability and control, dynamics, design, propulsion, and computer science, along with the related courses in mathematics, physics, statistics, and chemistry required to understand the material. Upon graduation, the new engineer will have acquired a basic knowledge of how to build an aerospace vehicle. What only comes through experience, however, is the understanding of the inevitable imperfect process through which an aerospace vehicle is built. This is the adventure of turning a basic concept into functional hardware. Engineers working on a project must often deal with ambiguous situations. They are routinely asked by management to provide risk assessments of a project, yet even after careful analysis uncertainties remain. The project must be accomplished within finite limits of time and money. The question an engineer answers is whether the solution to potential problem is worth the cost and schedule delay, or if the solution might actually be worse than the problem it is meant to solve. Review protocols are established to ensure that an unknown has not been overlooked. But these cannot protect against an unknown unknown. Examples of these situations can be found in the history of the X-43A Hyper-X (Hypersonic Experiment) program. In this NASA project, a supersonic combustion ramjet (scramjet) engine was flight tested on a subscale vehicle. The X-43A Hyper-X Research Vehicle (HXRV) was launched from a B-52B mothership, then boosted to the test speed by a modified Pegasus rocket first stage, called the Hyper-X Launch Vehicle (HXLV). Once at the proper speed and altitude, the X-43A separated from the booster, stabilized itself, and then the engine test began. Although wind-tunnel scramjet engine tests had begun in the late 1950s, before the Hyper-X program there had never been an actual in-flight test of such an engine integrated with an appropriate airframe. Thus, while the scramjet had successfully operated in the artificial airflow of wind tunnels, the concept had yet to be proven in real air. These conditions meant changes in density and temperature, as well as changes in angle of attack and sideslip of a free-flying vehicle. A wind tunnel is limited in its ability to simulate these subtle factures, which have a major impact on almost any vehicle, but especially that of a scramjet's performance. The Hyper-X project was to provide a real-world benchmark of the ground test data. The full scale X-43A engine would be operated in the wind tunnel, and then flown, and the data from its operation would then be compared with projections. If these matched, the wind tunnel data would be considered a reliable design tool for future scramjet. If there were significant differences, the reasons for these would have to be identified. Until such information was available, scramjets would lack the technological maturity to be considered for future space launch or high-speed atmospheric flight vehicles.

Peebles, Curtis↗