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NASA NTRS1981

Flight test results for the F-8 digital fly-by-wire aircraft control sensor analytic redundancy management technique

This paper reviews the formulation and flight test results of an algorithm to detect and isolate the first failure of any one of twelve duplex control sensor signals being monitored. The technique uses like-signal differences for fault detection while relying upon analytic redundancy relationships among unlike quantities to isolate the faulty sensor. The fault isolation logic utilizes the modified sequential probability ratio test, which explicitly accommodates the inevitable irreducible low frequency errors present in the analytic redundancy residuals. In addition, the algorithm uses sensor output selftest, which takes advantage of the duplex sensor structure by immediately removing a highly erratic sensor from control calculations and analytic redundancy relationships while awaiting a definitive fault isolation decision via analytic redundancy. This study represents a proof of concept demonstration of a methodology that can be applied to duplex or higher flight control sensor configurations and, in addition, can monitor the health of one simplex signal per analytic redundancy relationship.

Deckert, J. C.↗

NASA NTRS1983

Analytic redundance management for flight control sensors

The formulation and flight test results of an algorithm to detect and isolate the first failure of any one of 12 duplex control sensor signals (24 in all) being monitored are reviewed. The technique uses like signal differences for fault detection while relying upon analytic redundancy relationships among unlike quantities to isolate the faulty sensor. The fault isolation logic utilizes the modified sequential probability ratio test, which explicitly accommodates the inevitable, irreducible low frequency errors present in the analytic redundancy residuals. In addition, the algorithm used sensor output selftest, which takes advantage of the duplex sensor structure by immediately removing a hard failed sensor from control calculations and analytic redundancy relationships while awaiting a definitive fault isolation decision via analytic redundancy. This study represents a proof of concept demonstration of a methodology that is applied to duplex or higher flight control sensor configurations and, in addition, can monitor the health of one simplex signal per analytic redundancy relationship.

Deckert, J. C.↗

NASA NTRS1984

Comparison of an analytical approximation for particle motion in a current sheet with precise numerical calculations

Approximate analytic solutions exist for particle motion in a one-dimensional current sheet with a constant normal magnetic field component. These solutions are tested against precise numerical calculations, and a range of validity of the analytic solutions is inferred. For example, in the geomagnetic tail neutral sheet, for a dawn-dusk electric field of 0.1-1 mV/m, lobe field of 10-40 nT, and sheet thickness of 1000 km, the analytic solutions serve as a good predictor of particle motion when the normal magnetic field component is less than 3 or 4 nT. By using the analytic solutions, initial distribution functions are mapped into final (accelerated) distributions, and the analytic mappings are compared with numerical mappings.

Speiser, T. W.↗

NASA NTRS1989

Error analysis for semi-analytic displacement derivatives with respect to shape and sizing variables

Sensitivity analysis is fundamental to the solution of structural optimization problems. Consequently, much research has focused on the efficient computation of static displacement derivatives. As originally developed, these methods relied on analytical representations for the derivatives of the structural stiffness matrix (K) with respect to the design variables (b sub i). To extend these methods for use with complex finite element formulations and facilitate their implementation into structural optimization programs using the general finite element method analysis codes, the semi-analytic method was developed. In this method the matrix the derivative of K/the derivative b sub i is approximated by finite difference. Although it is well known that the accuracy of the semi-analytic method is dependent on the finite difference parameter, recent work has suggested that more fundamental inaccuracies exist in the method when used for shape optimization. Another study has argued qualitatively that these errors are related to nonuniform errors in the stiffness matrix derivatives. The accuracy of the semi-analytic method is investigated. A general framework was developed for the error analysis and then it is shown analytically that the errors in the method are entirely accounted for by errors in delta K/delta b sub i. Furthermore, it is demonstrated that acceptable accuracy in the derivatives can be obtained through careful selection of the finite difference parameter.

Fenyes, Peter A.↗

NASA NTRS1991

Experimental and analytical studies of flow through a ventral and axial exhaust nozzle system for STOVL aircraft

Flow through a combined ventral and axial exhaust nozzle system was studied experimentally and analytically. The work is part of an ongoing propulsion technology effort at NASA Lewis Research Center for short takeoff, vertical landing (STOVL) aircraft. The experimental investigation was done on the NASA Lewis Powered Lift Facility. The experiment consisted of performance testing over a range of tailpipe pressure ratios from 1 to 3.2 and flow visualization. The analytical investigation consisted of modeling the same configuration and solving for the flow using the PARC3D computational fluid dynamics program. The comparison of experimental and analytical results was very good. The ventral nozzle performance coefficients obtained from both the experimental and analytical studies agreed within 1.2 percent. The net horizontal thrust of the nozzle system contained a significant reverse thrust component created by the flow overturning in the ventral duct. This component resulted in a low net horizontal thrust coefficient. The experimental and analytical studies showed very good agreement in the internal flow patterns.

Esker, Barbara S.↗

NASA NTRS1991

Experimental and analytical studies of flow through a ventral and axial exhaust nozzle system for STOVL aircraft

Esker, Barbara S.↗

NASA NTRS1994

A simple analytical aerodynamic model of Langley Winged-Cone Aerospace Plane concept

A simple three DOF analytical aerodynamic model of the Langley Winged-Coned Aerospace Plane concept is presented in a form suitable for simulation, trajectory optimization, and guidance and control studies. The analytical model is especially suitable for methods based on variational calculus. Analytical expressions are presented for lift, drag, and pitching moment coefficients from subsonic to hypersonic Mach numbers and angles of attack up to +/- 20 deg. This analytical model has break points at Mach numbers of 1.0, 1.4, 4.0, and 6.0. Across these Mach number break points, the lift, drag, and pitching moment coefficients are made continuous but their derivatives are not. There are no break points in angle of attack. The effect of control surface deflection is not considered. The present analytical model compares well with the APAS calculations and wind tunnel test data for most angles of attack and Mach numbers.

Pamadi, Bandu N.↗

NASA NTRS1994

Theoretical investigation of wave-vector-dependent analytical and numerical formulations of the interband impact-ionization transition rate for electrons in bulk silicon and GaAs

The electron interband impact-ionization rate for both silicon and gallium arsenide is calculated using an ensemble Monte Carlo simulation with the expressed purpose of comparing different formulations of the interband ionization transition rate. Specifically, three different treatments of the transition rate are examined: the traditional Keldysh formula, a new k-dependent analytical formulation first derived by W. Quade, E. Scholl, and M. Rudan (1993), and a more exact, numerical method of Y. Wang and K. F. Brennan (1994). Although the completely numerical formulation contains no adjustable parameters and as such provides a very reliable result, it is highly computationally intensive. Alternatively, the Keldysh formular, although inherently simple and computationally efficient, fails to include the k dependence as well as the details of the energy band structure. The k-dependent analytical formulation of Quade and co-workers overcomes the limitations of both of these models but at the expense of some new parameterization. It is found that the k-dependent analytical method of Quade and co-workers produces very similar results to those obtained with the completely numerical model for some quantities. Specifically, both models predict that the effective threshold for impact ionization in GaAs and silicon is quite soft, that the majority of ionization events originate from the second conduction band in both materials, and that the transition rate is k dependent. Therefore, it is concluded that the k-dependent analytical model can qualitatively reproduce results similar to those obtained with the numerical model yet with far greater computational efficiency. Nevertheless, there exist some important drawbacks to the k-dependent analytical model of Quade and co-workers: These are that it does not accurately reproduce the quantum yield data for bulk silicon, it requires determination of a new parameter, related physically to the overlap intergrals of the Bloch state which can only be adjusted by comparison to experiment, and fails to account for any wave-vector dependence of the overlap integrals. As such the transition rate may be overestimated at those points for which 'near vertical,' small change in k, transitions occur.

Kolnik, Jan↗

NASA NTRS1994

Theoretical Investigation of Wave-Vector-Dependent Analytical and Numerical Formulations of the Interband Impact-Ionization Transition Rate for Electron in Bulk Silicon and GaAs

The electron interband impact-ionization rate for both silicon and gallium arsenide is calculated using an ensemble Monte Carlo simulation with the expressed purpose of comparing different formulations of the interband ionization transition rate. Specifically, three different treatments of the transition rate are examined: the traditional Keldysh formula, a new k-dependent analytical formulation first derived by W. Quade, E Scholl, and M. Rudan, and a more exact, numerical method of Y. Wang and K. F. Brennan. Although the completely numerical formulation contains no adjustable parameters and as such provides a very reliable result, it is highly computationally intensive. Alternatively, the Keldysh formula, although inherently simple and computationally efficient, fails to include the k dependence as well as the details of the energy band structure. The k-dependent analytical formulation of Quade and co-workers overcomes the limitations of both of these models but at the expense of some new parameterization. It is found that the k-dependent analytical method of Quade and co-workers produces very similar results to those obtained with (he completely numerical model for some quantities. Specifically, both models predict that the effective threshold for impact ionization in GaAs and silicon is quite soft, that the majority of ionization events originate from the second conduction band in both materials, and that the transition rate is k dependent. Therefore, it is concluded that the k-dependent analytical model can qualitatively reproduce results similar to those obtained with the numerical model yet with far greater computational efficiency. Nevertheless, there exist some important drawbacks to the k-dependent analytical model of Quade and co-workers: These are that it does not accurately reproduce the quantum yield data for bulk silicon, it requires determination of a new parameter, related physically to (he overlap integrals of the Bloch state which can only be adjusted by comparison to experiment, and fails to account for any wave-vector dependence of the overlap integrals. As such [he transition rate may be overestimated at those points for which "near vertical," small change in k, transitions occur.

Kolnik, Jan↗

NASA NTRS2000

Sensor arrays for detecting analytes in fluids

A sensor array for detecting an analyte in a fluid, comprising at least first and second chemically sensitive resistors electrically connected to an electrical measuring apparatus, wherein each of the chemically sensitive resistors comprises a mixture of nonconductive material and a conductive material. Each resistor provides an electrical path through the mixture of nonconductive material and the conductive material. The resistors also provide a difference in resistance between the conductive elements when contacted with a fluid comprising an analyte at a first concentration, than when contacted with an analyte at a second different concentration. A broad range of analytes can be detected using the sensors of the present invention. Examples of such analytes include, but are not limited to, alkanes, alkenes, alkynes, dienes, alicyclic hydrocarbons, arenes, alcohols, ethers, ketones, aldehydes, carbonyls, carbanions, polynuclear aromatics, organic derivatives, biomolecules, sugars, isoprenes, isoprenoids and fatty acids. Moreover, applications for the sensors of the present invention include, but are not limited to, environmental toxicology, remediation, biomedicine, material quality control, food monitoring and agricultural monitoring.

Lewis, Nathan S.↗

NASA NTRS2002

Trace level detection of analytes using artificial olfactometry

The present invention provides a device for detecting the presence of an analyte, such as for example, a lightweight device, including: a sample chamber having a fluid inlet port for the influx of the analyte; a fluid concentrator in flow communication with the sample chamber wherein the fluid concentrator has an absorbent material capable of absorbing the analyte and capable of desorbing a concentrated analyte; and an array of sensors in fluid communication with the concentrated analyte to be released from the fluid concentrator.

Lewis, Nathan S.↗

NASA NTRS2015

Sample Acquisition and Analytical Chemistry Challenges to Verifying Compliance to Aviators Breathing Oxygen (ABO) Purity Specification

NASA has been developing and testing two different types of oxygen separation systems. One type of oxygen separation system uses pressure swing technology, the other type uses a solid electrolyte electrochemical oxygen separation cell. Both development systems have been subjected to long term testing, and performance testing under a variety of environmental and operational conditions. Testing these two systems revealed that measuring the product purity of oxygen, and determining if an oxygen separation device meets Aviator's Breathing Oxygen (ABO) specifications is a subtle and sometimes difficult analytical chemistry job. Verifying product purity of cryogenically produced oxygen presents a different set of analytical chemistry challenges. This presentation will describe some of the sample acquisition and analytical chemistry challenges presented by verifying oxygen produced by an oxygen separator - and verifying oxygen produced by cryogenic separation processes. The primary contaminant that causes gas samples to fail to meet ABO requirements is water. The maximum amount of water vapor allowed is 7 ppmv. The principal challenge of verifying oxygen produced by an oxygen separator is that it is produced relatively slowly, and at comparatively low temperatures. A short term failure that occurs for just a few minutes in the course of a 1 week run could cause an entire tank to be rejected. Continuous monitoring of oxygen purity and water vapor could identify problems as soon as they occur. Long term oxygen separator tests were instrumented with an oxygen analyzer and with an hygrometer: a GE Moisture Monitor Series 35. This hygrometer uses an aluminum oxide sensor. The user's manual does not report this, but long term exposure to pure oxygen causes the aluminum oxide sensor head to bias dry. Oxygen product that exceeded the 7 ppm specification was improperly accepted, because the sensor had biased. The bias is permanent - exposure to air does not cause the sensor to return to its original response - but the bias can be accounted for by recalibrating the sensor. After this issue was found, continuous measurements of water vapor in the oxygen product were made using an FTIR. The FTIR cell is relatively large, so response time is slow - but moisture measurements were repeatable and accurate. Verifying ABO compliance for oxygen produced by commercial cryogenic processes has a different set of sample acquisition and analytical chemistry challenges. Customers want analytical chemists to conserve as much as possible. Hygrometers are not exposed to hours of continuous flow of oxygen, so they don't bias, but small amounts of contamination in valves can cause a "fail". K bottles are periodically cleaned and recertified - after cleaning residual moisture can cause a "fail". Operators let bottle pressure drop to room pressure, introduce outside air into the bottle, and the subsequent fill will "fail". Outside storage of K‐bottles has allowed enough in‐leakage, so contents will "fail".

Graf, John↗

NASA NTRS2018

System and Method for Providing a Climate Data Analytic Services Application Programming Interface

A system, method and computer-readable storage devices for providing a climate data analytic services application programming interface. The system includes a programming library that enables client device software to invoke the capabilities of a climate data analytics system through requests to various services supported by the climate data analytics system, and also includes a client-side communications interface that enables the programming library's methods to interact with a climate data analytics system's server interface to obtain access to the capabilities of the system. In one implementation, the programming library is implemented in the Python programming language. The programming library can include basic utilities that call a single, server-side method implemented by one of the various services supported by the climate data analytics system, and extended utilities that call a series of basic utilities and/or other extended utilities that have been placed under programmatic control in order to create client-side convenience methods and workflows.

Schnase, John L.↗

NASA NTRS2019

Analytic Spacecraft Attitude and Rate Estimation Performance During Attitude Sensor Outages

Analytic expressions for spacecraft attitude and rate estimation performance of an attitude estimation filter in terms of sensor specifications are useful tools for spacecraft design. Farrenkopf (1978) famously found analytic expressions for steady-state pre-update and post-update attitude and gyro bias estimate error variances for an attitude estimation filter for a single-axis spacecraft with a Rate Output Gyro (ROG). Markley and Reynolds (2000) extended the analysis for a Rate-Integrating Gyro (RIG) with angle white noise. These expressions allow for the rapid evaluation of system performance during preliminary mission design phases. One contribution of this paper is the analytic calculation of the steady-state pre-update and post-update angular rate estimate uncertainty for both the ROG and RIG cases. The primary contribution of this paper is the extension of the results for both the ROG and the RIG cases to the situation of an attitude sensor outage. This situation arises frequently in practice; for example when a star sensor’s field of view is occluded, when a star sensor’s readings are unreliable during a thruster burn that vibrates the spacecraft, or during star sensor outages due to radiation upsets. Analytic expressions for the attitude estimate uncertainty, gyro bias estimate uncertainty, and angular rate estimate uncertainty are given in terms of the attitude sensor outage interval, the star tracker measurement noise, and gyro noise parameters. Validity of the analytic results is demonstrated via Monte Carlo simulation.

Galante, Joseph M.↗

NASA NTRS2019

Analytic Spacecraft Attitude and Rate Estimation Performance During Attitude Sensor Outages

Galante, Joseph M.↗

NASA NTRS2020

Machine Learning-Based Predictive Analytics for Aircraft Engine Conceptual Design

Big data and artificial intelligence/machine learning are transforming the global business environment. Data is now the most valuable asset for enterprises in every industry. Companies are using data-driven insights for competitive advantage. With that, the adoption of machine learning-based data analytics is rapidly taking hold across various industries, producing autonomous systems that support human decision-making. This work explored the application of machine learning to aircraft engine conceptual design. Supervised machine-learning algorithms for regression and classification were employed to study patterns in an existing, open-source database of production and research turbofan engines, and resulting in predictive analytics for use in predicting performance of new turbofan designs. Specifically, the author developed machine learning-based analytics to predict cruise thrust specific fuel consumption (TSFC) and core sizes of high-efficiency turbofan engines, using engine design parameters as the input. The predictive analytics were trained and deployed in Keras, an open-source neural networks application program interface (API) written in Python, with Google’s TensorFlow (an open source library for numerical computation) serving as the backend engine. The promising results of the predictive analytics show that machine-learning techniques merit further exploration for application in aircraft engine conceptual design.

deep-learning↗

NASA NTRS2019

A Web of Data Analytics Services

Cloud Computing has become the ubiquitous approach to our Big Data challenge. However, one will quickly discover that moving (a.k.a. forklifting) existing on-premise data analytics solutions to the Cloud doesn’t always translate to costing saving and performance boost. The Cloud’s elasticity, its availability, and its wide selection of computing options and selections of costing models making Cloud an attractive environment to tackle our Big Data challenge. The fact is Cloud, on its own, is not the silver bullet to our daunting challenge need for analyze and derive scientific inferences through vast collections of multi-sensor measurements. We would like to have all scientific data in one easy to access environment, but getting the world of scientific data in one analytic system is immensely difficult to achieve. This paper describes the data analytics web architecture NASA is developing by infusing instances of Integrated Data Analytics systems next to the data. The goal is to minimize unnecessary data movement through collection of data access and analytics webservices for researchers to interact with and analyze measurements without have to download data to their local computer. These services are RESTful and provisioned by the data centers with the help from subject matter and science experts. These services encapsulate the physical computing infrastructure, which could local computing cluster, on-premise or public Cloud environment.

Huang, Thomas↗

NASA NTRSDate not supplied

Analytical Needs in a Sample Receiving Facility: Input from the MSR Operation Definition Team

The return of scientifically selected samples from Mars would provide a rare opportunity forinvestigation with the full range of the latest technology available, but to take full advantageof this opportunity, it is important to plan ahead to ensure the pristine nature of the samplesupon arrival within the Earth environment until scientific investigations can begin.The NASA/ESA science community-driven MSR Science Planning Group – Phase 2 (MSPG2)delivered recommendations and guidance regarding curation (1) and science (2, 3) activities tobe performed on the samples under containment. High-level requirements for the infrastruc-ture were also developed by MSPG2 (4). In order to prepare infrastructure-targeted input forthe ESA and NASA facility studies planned in the 2022-2023 timeframe, the agency-led MSROperational Scenarios Definition Team (MOSDT) was assembled to conceptualize the sampleoperations that will inform future architecture teams. Emphasis was placed on the respon-sibility of MOSDT to use community-defined requirements and to represent the view of the international scientific community.All necessary and sufficient instruments and analytical needs described in MSPG2 were inte-grated in MOSDT main deliverable, the operational workflow (see Hays et al, this conference).In MSPG2, notional instruments were split between curation analytical needs, and objective-driven (time-sensitive and sterilization-sensitive) science analytical needs. In MOSDT, whilethe first phases of curation, “pre-Basic Characterization” and “Basic Characterization” wererather streamlined and separate from other analytical needs, “Preliminary Examination” and“Science” instruments were not always physically segregated. In addition to the necessary andsufficient instruments described by MSPG2, the MOSDT recommended additional supportequipment for sterilization, cleanliness and contamination monitoring.It was sometimes necessary for the MOSDT to rely on assumptions to integrate instruments inthe activity workflow. In general, the assumptions were very conservative to limit contaminationand cross-contamination risks. It is expected that future work to refine limits of contaminationwill enable optimization of instrumentation.The community was consulted during the course of the MOSDT work. This abstract’s aimis two-fold: on one hand, inform the scientific community and overall MSR stakeholders, tobring their attention on the analytical needs currently considered as necessary and sufficient;on the other hand, to solicit feedback from a larger community audience to optimize and refineanalytical needs during the next phases of MSR ground-segment preparation.Disclaimer: The decision to implement Mars Sample Return will not be finalized until NASA’scompletion of the program’s National Environmental Policy Act (NEPA) process. This docu-ment is being made available for informational purposes only.[1] Tait et al. (2021) Preliminary planning for Mars Sample Return (MSR) curation activities ina Sample Receiving Facility (SRF). Astrobiology in press, doi:10.1089/ast.2021.0105. [2] Toscaet al. (2021) Time-sensitive aspects of Mars Sample Return (MSR) science. Astrobiologyin press, doi:10.1089/ast.2021.0115. [3] Velbel et al. (2021) Planning implications relatedto sterilization-sensitive science investigations associated with Mars Sample Return (MSR).Astrobiology in press, doi:10.1089/ast.2021.0113. [4] Carrier et al. (2021) Science and curationconsiderations for the design of a Mars Sample Return (MSR) Sample Receiving Facility (SRF).Astrobiology in press, doi:10.1089/ast.2021.0110.

Mars Sample Return↗