Summary of acceleration and airspeed data from commercial transport airplanes during the period from 1933 to 1945
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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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Vibration tests were performed to develop and validate the forced limited vibration testing capability at the NASA Langley Research Center. The force limited vibration test technique has been utilized at the Jet Propulsion Laboratory and other NASA centers to provide more realistic vibration test environments for aerospace flight hardware. In standard random vibration tests, the payload is mounted to a rigid fixture and the interface acceleration is controlled to a specified level based on a conservative estimate of the expected flight environment. In force limited vibration tests, both the acceleration and force are controlled at the mounting interface to compensate for differences between the flexible flight mounting and rigid test fixture. This minimizes the over test at the payload natural frequencies and results in more realistic forces being transmitted at the mounting interface. Force and acceleration response data was provided by NASA Goddard Space Flight Center for a test article that was flown in 1998 on a Black Brant sounding rocket. The measured flight interface acceleration data was used as the reference acceleration spectrum. Using this acceleration spectrum, three analytical methods were used to estimate the force limits. Standard random and force limited vibration tests were performed and the results are compared with the flight data.
Experimental data show that there is a neurogenic response to acceleration stress in the front to back direction and that this response is intensified during higher accelerative forces. The afferent limb of this response is unknown but possibilities are suggested. The integrated response at high acceleration levels might serve to conserve oxygen during the stress time. The effector limb is the constriction of less critical vascular beds to preserve blood flow to the heart and brain. The concomitant increase in vagal activity causes a slowing down of the heart.
An analysis of the data leading to a proposed accelerated life test scheme to test a nickel cadmium cell under spacecraft usage conditions is described. The amount and concentration of electrolyte and the amount of precharge in the cell are discussed in relation to the design of the cell and the accelerated test design. A failure analysis of the cell is summarized. The analysis included such environmental test variables as the depth of discharge, the temperature, the amount of recharge and the charge and discharge rate.
Radio metric data from the Pioneer 10/11, Galileo, and Ulysses Spacecraft indicate an apparent anomalous, constant, acceleration acting on the spacecraft with a magnitude ~8.5 x 10(sup -8) cm/s(sup 2), directed towards the Sun.
To construct Venus' gravity disturbance field (or gravity anomaly) with the spacecraft-observer line of site (LOS) acceleration perturbation data, both a global and a local approach can be used. The global approach, e.g., spherical harmonic coefficients, and the local approach, e.g., the integral operator method, based on geodetic techniques are generally not the same, so that they must be used separately for mapping long wavelength features and short wavelength features. Harmonic spline, as an interpolation and extrapolation technique, is intrinsically flexible to both global and local mapping of a potential field. Theoretically, it preserves the information of the potential field up to the bound by sampling theorem regardless of whether it is global or local mapping, and is never bothered with truncation errors. The improvement of harmonic spline methodology for global mapping is reported. New basis functions, a singular value decomposition (SVD) based modification to Parker & Shure's numerical procedure, and preliminary results are presented.
Experimental data are presented for heat transfer to the turbulent boundary layer subjected to transpiration and acceleration at constant values of the acceleration parameter K of approximately .00000145. This is a moderately strong acceleration, but not so strong as to result in laminarization of the boundary layer. The results for transpiration fractions F of -0.002, 0.0, and +0.0058 are presented in detail in tabular form, and in graphs of Stanton number versus enthalpy thickness Reynolds number. In addition, temperature profiles at several stations are presented. Stanton number results for F = -0.004, +0.002, and +0.004 are also presented, but in graphical form only. The data were obtained using air as both the free-stream and the transpired fluid, at relatively low velocities, and with temperature differences sufficiently low so that the influence of temperature-dependent fluid properties is minimal. All data were obtained with the surface maintained at a temperature invariant in the direction of flow.
The project aims to develop mechanistic degradation models that realistically predict long-term Solid Oxide Electrolysis Cell (SOEC) durability, using input data from accelerated electrochemical life testing combined with quantitative microstructural and microchemical evaluation. A promising SOEC type will be further developed. The understanding achieved by combining experimental results and theory will be used to guide improvements in long-term SOEC durability, and validate that this technology can reach DOE H 2 production cost and durability targets. Planned outcomes include: (1) new experimental accelerated testing data on SOEC degradation at the oxygen electrode, fuel electrode, and electrolyte; (2) predictive theory of degradation developed based on the accelerated test data; (3) new electrode materials and processing methods that minimize degradation rate; (4) determination of the impact of SOEC electrolyte thickness and electrode composition/microstructure on performance and degradation; (5) determination of the operating conditions where degradation is minimized; and (6) validation of degradation models for extrapolating accelerated test data to predict long-term durability.
Cycle life regression model, cycle life prediction model, and acceleration factors are discussed. A method was presented to: (1) select a mathematical model; (2) determine model coefficients using accelerated test data; (3) test model fit of the accelerated test data; and (4) predict normal packs.
Experimental data were combined with one-dimensional conservation relations to yield information on the energy deposition ratio in a parallel-plate accelerator, where the downstream flow was confined to a constant area channel. Approximately 70% of the total input power was detected in the exhaust flow, of which only about 20% appeared as directed kinetic energy, thus implying that a downstream expansion to convert chamber enthalpy into kinetic energy must be an important aspect of conventional high power MPD arcs. Spectroscopic experiments on a quasi-steady MPD argon accelerator verified the presence of A(III) and the absence of A(I), and indicated an azimuthal structure in the jet related to the mass injection locations. Measurements of pressure in the arc chamber and impact pressure in the exhaust jet using a piezocrystal backed by a Plexiglas rod were in good agreement with the electromagnetic thrust model.
Foundation Models (FM) are AI models that are designed to replace a task or an application specific model. These FM can be applied to many different downstream applications. These FM are trained using self supervised techniques and can be built on any type of sequence data. The use of self supervised learning removes the hurdle for developing a large labeled dataset for training. Most FM use transformer architecture utilizes the notion of self attention which allows the network to model the influence of distant data points to each other both in space and time. The FM models exhibit emergent properties that are induced from the data. FM can be an important tool for science. The scale of these models results in better performance for different downstream applications and these applications show better accuracy over models built from scratch. FM drastically reduces the cost of entry to build different downstream applications both in time and effort. FM for selected science datasets such as optical satellite data, can accelerate applications ranging from data quality monitoring, feature detection and prediction. FM can make it easier to infuse AI into scientific research by removing the training data bottleneck and increasing the use of science data.
Over the course of 60 years of shape memory alloy research and development, the properties of these alloys have been measured using various testing methods, which are often customized by the organization performing the test. However, commercial adoption of shape memory alloys in aeronautic actuator applications requires reducing property uncertainty through standardizing test methods. Historically, differential scanning calorimetry (DSC) has been used to measure transformation temperatures under stress-free conditions. This testing method is well established, and tests are run under the applicable standard, ASTM F2004-17: Standard Test Method for Transformation Temperature of Nickel-Titanium Alloys by Thermal Analysis. Two other test methods for measuring strains and transformation temperatures under constant load or free recovery after prestraining have only recently been standardized—ASTM E3097: Standard Test Method for Mechanical Uniaxial Constant Force Thermal Cycling of SMAs (UCFTC) and ASTM E3098: Standard Test Method for Mechanical Uniaxial Pre-Strain and Thermal Free Recovery of SMAs (UPFR). These standards represent a critical step forward in producing reliable material property data for the use of these alloys in aeronautics and other commercial areas. However, no standard programs or software packages were previously available for postprocessing UCFTC- and UPFR-type test data to extract property data. Each organization that performed the testing analyzed data using its own custom manual methods, such as using a plot and a straight edge, spreadsheet plotting methods, or custom code routines, to extract the required values for strains, stresses, and transformation temperatures. SMAnalytics represents the first publicly available uniform software package for processing data generated using the DSC, UCFTC, and UPFR test methods, as well as many modifications of these methods, including loading in martensite versus austenite and performing multiple thermal cycles at stress. In doing so, it provides a tool for reducing potential error or variability in the measured values due to the precision of the technique used and person-to-person variability. It is also expected that this automated data-parsing tool can accelerate the data analysis phase of the test campaign, especially for large data files. This User’s Manual describes how the SMAnalytics software works and the method for its use.
Here, this study explores the increasing interest in leveraging nuclear power to meet the escalating energy demands of data centers in the United States (U.S.) by focusing on key factors that contribute to accelerated deployment. The study highlights the importance of N+1/N+2 power supplies (where N is the required number of units), outlines research and innovations in nuclear-integrated data center thermal management and demonstration plan. It also provides updates about status and costing of various reactor system designs. A summarized strengths, weaknesses, opportunities, and threats (SWOT) analysis shows the potential options for grid connectivity, reactors, and site selection. Suitable site discussions consider land and water availability, grid access, and optical fiber connectivity, and the study presents graded prospects for Department of Energy (DOE) sites with a specific example. Community engagement and partnerships are emphasized, particularly the roles of local government, federal agencies, utilities, and data center industry partners, which are crucial for accelerating deployment, business outreach, and approvals. The study provides actionable insights for stakeholders to accelerate the deployment of nuclear-powered data centers.
Data obtained from multiple flights of sensitive accelerometers on the Space Shuttle Orbiter during reentry have been used to develop an improved aerodynamic model for the Orbiter normal- and axial-force coefficients in hypersonic rarefied flow. The lack of simultaneous atmospheric density measurements was overcome in part by using the ratio of normal-to-axial acceleration, in which density cancels, as a constraint. Differences between the preflight model and the flight-acceleration-derived model in the continuum regime are attributed primarily to real gas effects. New insights are gained into the variation of the force coefficients in the transition between the continuum regime and free molecule flow.
The accelerating adoption of electric vehicles (EVs) poses challenges to the power grid, necessitating precise representation of mobility patterns for effective infrastructure upgrades. Traditional simulation-based charging demand estimation faces limitations in generating trip chains reflective of actual travel patterns without complex network modeling. Hence, an innovative agent-based trip chain generation model is introduced to overcome these challenges. Drawing from the National Household Travel Survey (NHTS) and the NextGen NHTS origin-destination add-on data for Clarke County, Georgia, this study proposes a simulation method capturing both temporal and spatial mobility patterns without relying on extensive network topology data. The resulting trip chains predict EV charging load at the Census Block Group level, validated with a 1.03 correlation to actual trip counts, affirming their reflective accuracy. Two charging scenarios, residential-only and charging-everywhere, reveal distinct demand profiles. The charging-everywhere scenario aligns closely with the trip profile, while the residential-only scenario exhibits an afternoon peak slightly surpassing the former. This study contributes a data-driven charging demand estimation methodology, offering critical insights for grid resiliency planning amid the evolving landscape of EV adoption.
Glacial acceleration is a main source of uncertainty in sea-level-change assessment. Measurement of ice-surface heights with a spatial and temporal resolution that not only allows elevation-change calculation, but also captures ice-surface morphology and its changes is required to aid in investigations of the geophysical processes associated with glacial acceleration.The Advanced Topographic Laser Altimeter System aboard NASAs future ICESat-2 Mission (launch 2017) will implement multibeam micropulse photon-counting lidar altimetry aimed at measuring ice-surface heights at 0.7-m along-track spacing. The instrument is designed to resolve spatial and temporal variability of rapidly changing glaciers and ice sheets and the Arctic sea ice. The new technology requires the development of a new mathematical algorithm for the retrieval of height information.We introduce the density-dimension algorithm (DDA) that utilizes the radial basis function to calculate a weighted density as a form of data aggregation in the photon cloud and considers density an additional dimension as an aid in auto-adaptive threshold determination. The auto-adaptive capability of the algorithm is necessary to separate returns from noise and signal photons under changing environmental conditions. The algorithm is evaluated using data collected with an ICESat-2 simulator instrument, the Slope Imaging Multi-polarization Photon-counting Lidar, over the heavily crevassed Giesecke Braer in Northwestern Greenland in summer 2015. Results demonstrate that ICESat-2 may be expected to provide ice-surface height measurements over crevassed glaciers and other complex ice surfaces. The DDA is generally applicable for the analysis of airborne and spaceborne micropulse photon-counting lidar data over complex and simple surfaces.