Results for “Structural error” — Page 36

NASA NTRS1983

Balloon-borne pressure sensor performance evaluation utilizing tracking radars

The pressure sensors on balloon-borne sondes relate the sonde measurements to height above the Earth's surface through the hypsometric equation. It is crucial that sondes used to explore the vertical structure of the atmosphere do not contribute significant height errors to their measurements of atmospheric constituent concentrations and properties. A series of radiosonde flights was conducted. In most cases, each flight consisted of two sondes attached to a single balloon and each flight was tracked by a highly accurate C-band radar. For the first 19 radiosonde flights, the standard aneroid cell baroswitch assembly used was the pressure sensor. The last 26 radiosondes were equipped with a premium grade aneroid cell baroswitch assembly sensor and with a hypsometer. It is shown that both aneroid cell baroswitch sensors become increasingly inaccurate with altitude. The hypsometer radar differences are not strongly dependent upon altitude and it is found that the standard deviation of the differences at 35 km is 0.179 km.

Norcross, G. A.↗

NASA NTRS1984

Severe storm electricity

Successful ground truth support of U-2 overflights was been accomplished. Data have been reduced for 4 June 1984 and some of the results have been integrated into some of MSFC's efforts. Staccato lightning (multiply branched, single stroke flash with no continuing current) is prevalent within the rainfree region around the main storm updraft and this is believed to be important, i.e., staccato flashes might be an important indicator of severe storm electrification. Results from data analysis from two stations appear to indicate that charge center heights can be estimated from a combination of intercept data with data from the fixed laboratory at NSSL. An excellent data base has been provided for determining the sight errors and efficiency of NSSL's LLP system. Cloud structures, observable in a low radar reflectivity region and on a scale smaller than is currently resolved by radar, which appear to be related to electrical activity are studied.

Arnold, R. T.↗

NASA NTRS1987

A modern control theory based algorithm for control of the NASA/JPL 70-meter antenna axis servos

A digital computer-based state variable controller was designed and applied to the 70-m antenna axis servos. The general equations and structure of the algorithm and provisions for alternate position error feedback modes to accommodate intertarget slew, encoder referenced tracking, and precision tracking modes are descibed. Development of the discrete time domain control model and computation of estimator and control gain parameters based on closed loop pole placement criteria are discussed. The new algorithm was successfully implemented and tested in the 70-m antenna at Deep Space Network station 63 in Spain.

Hill, R. E.↗

NASA NTRS1991

Effect of rain on Ku-band scatterometer wind measurements

The impact of precipitation on scatterometer wind measurements is investigated. A model is developed which includes the effects of rain attenuation, rain backscatter, and storm horizontal structure. Rain attenuation is found to be the dominant error source at low radar incidence angles and high wind speeds. Volume backscatter from the rain-loaded atmosphere, however, is found to dominate for high incidence angles and low wind speeds.

Spencer, Michael↗

NASA NTRS1992

Lumped mass modelling for the dynamic analysis of aircraft structures

Aircraft structures may be modelled by lumping the masses at particular strategic points and the flexibility or stiffness of the structure is obtained with reference to these points. Equivalent moments of inertia for the section at these positions are determined. The lumped masses are calculated based on the assumption that each point will represent the mass spread on one half of the space on each side. Then these parameters are used in the differential equation of motion and the eigen characteristics are determined. A comparison is made with results obtained by other established methods. The lumped mass approach in the dynamic analysis of complicated structures provides an easier means of predicting the dynamic characteristics of these structures. It involves less computer time and avoids computational errors that are inherent in the numerical solution of complicated systems.

Abu-Saba, Elias G.↗

NASA NTRS1991

Optimal control/structure integrated design of a flexible space platform with articulated appendages

A complete set of closed form symbolic equations are developed for a 2-D model of a system comprised of a flexible platform with articulated appendages. The system considered has a flexible two link manipulator, with joint compliance, at one end of the flexible platform and an articulated antenna on the other end. The model is formulated using a Lagrangian approach which incorporates homogeneous transformation matrices, similar to those typically seen in the robotics literature, for the kinematic representation. The integrated control/structure design strategy considered emphasizes rapid system response and minimal structural weight. Constraints are included to keep antenna pointing error to a minimum, and at the same time achieve accurate end point positioning of the manipulator with minimal oscillations.

Kelkar, Atul G.↗

NASA NTRS1993

Design decisions from the history of the EUVE science payload

Some of the design issues that arose during the development of the EUVE science payload and solutions to the problems involved are examined. In particular, attention is given to the use of parallel and serial busses, the selection of the the ROM approach for software storage and execution, implementation of memory error detection and correction, and the selection of command structures. The early design decisions paid off in the timely delivery of the scientific payload and in the successful completion of the survey phase of the EUVE science mission.

Marchant, W.↗

NASA NTRS1996

Multidisciplinary Design Of Hot Composite Structures

Unified computer code developed to implement multidisciplinary approach to design and analysis of composite-material structures that must withstand high temperatures. Code modular: includes executive module communicating with and coordinating other modules performing calculations pertaining to traditionally separate disciplines like those of acoustics, structural vibrations, structural loads, and thermal effects. Essential feature, finite-element numerical simulation of relevant physical phenomena according to applicable disciplines. Same finite-element mesh used in thermal, vibrational, and structural analyses; minimizing data-preparation time and eliminating errors incurred in transforming temperatures from one finite-element mesh to another.

Chamis, Christos C.↗

NASA NTRS1997

An investigation into the milliarcsecond attitude control errors of Hubble Space Telescope

An analysis of the fine pointing errors of the Hubble Space Telescope (HST), in the range from 1 to 15 milliarcsecs, is reported on. The emphasis is on the study of the performance characteristics of the pointing control system, fine guidance sensors and the optical telescope assembly, which produce relative attitude and astrometric measurement errors. Since the first servicing mission in December 1993, the HST relative short term position stability is of the order of 3 milliarcsecs RMS when averaged over 1 min intervals. At this level of accuracy, longer term systematic attitude errors in this range can have a noticeable impact on the telescope's observations. The various error sources are described, including: internal temperature effects; spacecraft structure temperature effects; calibration procedures, and computational inaccuracies.

Bradley, A. J.↗

NASA NTRS2004

Performance and Reliability Optimization for Aerospace Systems subject to Uncertainty and Degradation

This report summarizes work performed by the Space Systems Laboratory (SSL) for NASA Langley Research Center in the field of performance optimization for systems subject to uncertainty. The objective of the research is to develop design methods and tools to the aerospace vehicle design process which take into account lifecycle uncertainties. It recognizes that uncertainty between the predictions of integrated models and data collected from the system in its operational environment is unavoidable. Given the presence of uncertainty, the goal of this work is to develop means of identifying critical sources of uncertainty, and to combine these with the analytical tools used with integrated modeling. In this manner, system uncertainty analysis becomes part of the design process, and can motivate redesign. The specific program objectives were: 1. To incorporate uncertainty modeling, propagation and analysis into the integrated (controls, structures, payloads, disturbances, etc.) design process to derive the error bars associated with performance predictions. 2. To apply modern optimization tools to guide in the expenditure of funds in a way that most cost-effectively improves the lifecycle productivity of the system by enhancing the subsystem reliability and redundancy. The results from the second program objective are described. This report describes the work and results for the first objective: uncertainty modeling, propagation, and synthesis with integrated modeling.

Miller, David W.↗

NASA NTRS1994

Handbook for Dynamic Data Acquisition and Analysis - IES Recommended Practices 012.1

The original motivation for this Handbook came from personnel of The Aerospace Corporation (TAC), who are technical advisors to the Air Force Space and Missile Systems Center. Over the preceding two decades, TAC has observed a seemingly endless series of errors and anomalies in the acquisition and analysis of structural dynamic and aeroacoustic data.

Shock vibration acoustic noise↗

NASA NTRS2012

International Space Station 2A Array Modal Analysis

On December 9th 2009, the International Space Station (ISS) 2A solar array mast experienced prolonged longeron shadowing during a Soyuz undocking. Analytical reconstruction of induced thermal and dynamic structural loads showed an exceedance of the mast buckling limit. Possible structural damage to the solar array mast could have occurred during this event. A Low fidelity video survey of the 2A mast showed no obvious damage of the mast longerons or battens. The decision was made to conduct an on-orbit dynamic test of the 2A array on December 18th, 2009. The test included thruster pluming on the array while photogrammetry data was recorded. The test was similar to other Dedicated Thruster Firings (DTFs) that were performed to measure structural frequency and damping of a solar array. Results of the DTF indicated lower frequency mast modes than model predictions, thus leading to speculation of mast damage. A detailed nonlinear analysis was performed on the 2A array model to assess possible solutions to modal differences. The setup of the parametric nonlinear trade study included the use of a detailed array model and the reduced mass and stiffness matrices of the entire ISS being applied to the array interface. The study revealed that the array attachment structure is nonlinear and thus was the source of error in the model prediction of mast modes. In addition, a detailed study was performed to determine mast mode sensitivity to mast longeron damage. This sensitivity study was performed to assess if the ISS program has sufficient instrumentation for mast damage detection.

Laible, Michael↗

NASA NTRS1993

Summary of

A 325-page Guidelines document [1], whose objectives are to increase the accuracy and reduce the errors and variability commonly found in the measurement of structural shock and vibration and of acoustic and aerodynamic noise, wea recently submitted to the Air Force Space and Missile Systems Center.

scope↗

NASA NTRSDate not supplied

Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions

Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.

J Lemery↗

NASA NTRS2024

Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions

Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.

Medical Operations↗

DOE OSTI2018

Evaluating transition metal oxides within DFT-SCAN and SCAN + U frameworks for solar thermochemical applications

Using the strongly constrained and appropriately normed (SCAN) and SCAN+U approximations for describing electron exchange-correlation (XC) within density functional theory, we investigate the oxidation energetics, lattice constants, and electronic structure of binary Ce-, Mn-, and Fe-oxides, which are crucial ingredients for generating renewable fuels using two-step, oxide-based, solar thermochemical reactors. Unlike other common XC functionals, we find that SCAN does not over-bind the O 2 molecule, based on direct calculations of its bond energy and robust agreement between calculated formation enthalpies of main group oxides versus experiments. However, in the case of transition-metal oxides (TMOs), SCAN systematically overestimates (i.e., yields too negative) oxidation enthalpies due to remaining self-interaction errors in the description of their ground-state electronic structure. Adding a Hubbard U term to the transition-metal centers, where the magnitude of U is determined from experimental oxidation enthalpies, significantly improves the qualitative agreement and marginally improves the quantitative agreement of SCAN+U-calculated electronic structure and lattice parameters, respectively, with experiments. Importantly, SCAN predicts the wrong ground-state structure for a few oxides, namely, Ce 2 O 3 , Mn 2 O 3 , and Fe 3 O 4 , while SCAN+U predicts the right polymorph for all systems considered in this work. Furthermore, the SCAN+U framework, with an appropriately determined U, will be required to accurately describe ground-state properties and yield qualitatively consistent electronic properties for most transition-metal and rare earth oxides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2012

High-Data-Rate Quadrax Cable Microwave Characterization at the NASA Glenn Structural Dynamics Laboratory

An experiment was performed to determine the degradation in the bit-error-rate (BER) in the high-data-rate cables chosen for the Orion Service Module due to extreme launch conditions of vibrations with a magnitude of 60g. The cable type chosen for the Orion Service Module was no. 8 quadrax cable. The increase in electrical noise induced on these no. 8 quadrax cables was measured at the NASA Glenn vibration facility in the Structural Dynamics Laboratory. The intensity of the vibrations was set at 32g, which was the maximum available level at the facility. The cable lengths used during measurements were 1, 4, and 8 m. The noise measurements were done in an analog fashion using a performance network analyzer (PNA) by recording the standard deviation of the transmission scattering parameter S(sub 21) over the frequency range of 100 to 900 MHz. The standard deviation of S(sub 210 was measured before, during, and after the vibration of the cables at the vibration facility. We observed an increase in noise by a factor of 2 to 6. From these measurements we estimated the increase expected in the BER for a cable length of 25 m and concluded that these findings are large enough that the noise increase due to vibration must be taken in to account for the design of the communication system for a BER of 10(exp -8).

Theofylaktos, Onoufrios↗

DOE OSTI2019

OPERATIONAL TOPOLOGY ESTIMATION OF THREE PHASE UNBALANCED POWER DISTRIBUTION SYSTEMS WITH OUTAGES

Distribution grid, in general, is constructionally loopy but a radially operated network. Opening and closing of suitable tie-switches allows transition from one radial topology to another. Tie-switches ensure reliability and provide restoration paths when faults (outages) occur. The estimation of the system's current operational topology is a precursor to implementing any optimal control actions (during normal operation) or restorative actions (during outage condition). The existing literature in topology detection suffers with several limitations including: (1) computationally intensive nonlinear formulations that are not scalable for large distribution systems, (2) methods requiring exhaustive search for the correct topology by enumerating the complete topological search space, and (3) approaches requiring large volumes of time-series measurements and are not applicable for estimating continuously changing operational topology. Furthermore, the existing literature on distribution grid topology estimation cannot be extended to estimate the operational topology during outage conditions. For operational topology estimation during outages, our objective is to estimate both energized radial feeder and the outaged sections. Starting with a radial topology, these methods identify outaged feeder sections and hence, are inapplicable when the current radial operational topology is not known. In this work, we present a mathematical programming approach to estimate the operational topology of a three-phase unbalanced power distribution system under both outage and normal operating conditions. The aforementioned limitations of existing literature were countered by modeling the problem as a mixed-integer linear programming (MILP) problem which minimizes the errors in available measurements while satisfying the power flow and structural constraints of the system. Specically, a minimum weighted least absolute value estimator is proposed that uses the instantaneous line flow measurements, historical/ forecasted load data, and ping measurements from a limited set of smart meters and solves an MILP to identify the operational topology based on a linearized three-phase unbalanced power flow model. The proposed approach is tested on IEEE 123-bus feeder and 1069 bus multi-feeder test system and the numerical results prove the applicability of the proposed method to large three phase unbalanced grids with high errors in measurements. It is observed that the approach performs well even at high percentages of measurement errors.

GANDLURU NAGA, ANANDINI↗