Search NASA⌕ Search

SEARCH · Search NASA

Results for “Information Analytics”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Advanced Curation of Current and Future Extraterrestrial Samples

Curation of extraterrestrial samples is the critical interface between sample return missions and the international research community. Curation includes documentation, preservation, preparation, and distribution of samples. The current collections of extraterrestrial samples include: Lunar rocks / soils collected by the Apollo astronauts Meteorites, including samples of asteroids, the Moon, and Mars "Cosmic dust" (asteroid and comet particles) collected by high-altitude aircraft Solar wind atoms collected by the Genesis spacecraft Comet particles collected by the Stardust spacecraft Interstellar dust collected by the Stardust spacecraft Asteroid particles collected by the Hayabusa spacecraft These samples were formed in environments strikingly different from that on Earth. Terrestrial contamination can destroy much of the scientific significance of many extraterrestrial materials. In order to preserve the research value of these precious samples, contamination must be minimized, understood, and documented. In addition the samples must be preserved - as far as possible - from physical and chemical alteration. In 2011 NASA selected the OSIRIS-REx mission, designed to return samples from the primitive asteroid 1999 RQ36 (Bennu). JAXA will sample C-class asteroid 1999 JU3 with the Hayabusa-2 mission. ESA is considering the near-Earth asteroid sample return mission Marco Polo-R. The Decadal Survey listed the first lander in a Mars sample return campaign as its highest priority flagship-class mission, with sample return from the South Pole-Aitken basin and the surface of a comet among additional top priorities. The latest NASA budget proposal includes a mission to capture a 5-10 m asteroid and return it to the vicinity of the Moon as a target for future sampling. Samples, tools, containers, and contamination witness materials from any of these missions carry unique requirements for acquisition and curation. Some of these requirements represent significant advances over methods currently used. New analytical and screening techniques will increase the value of current sample collections. Improved web-based tools will make information on all samples more accessible to researchers and the public. Advanced curation of current and future extraterrestrial samples includes: Contamination Control - inorganic / organic Temperature of preservation - subfreezing / cryogenic Non-destructive preliminary examination - X-ray tomography / XRF mapping / Raman mapping Microscopic samples - handling / sectioning / transport Special samples - unopened lunar cores Informatics - online catalogs / community-based characterization.

Allen, Carlton C.↗
NASA NTRS2016

Retrieval of Macro- and Micro-Physical Properties of Oceanic Hydrosols from Polarimetric Observations

Remote sensing has mainly relied on measurements of scalar radiance and its spectral and angular features to retrieve micro- and macro-physical properties of aerosols/hydrosols. However, it is recognized that measurements that include the polarimetric characteristics of light provide more intrinsic information about particulate scattering. To take advantage of this, we used vector radiative transfer (VRT) simulations and developed an analytical relationship to retrieve the macro and micro-physical properties of the oceanic hydrosols. Specifically, we investigated the relationship between the observed degree of linear polarization (DoLP) and the ratio of attenuation-to- absorption coefficients (c/a) in water, from which the scattering coefficient can be readily computed (b equals c minus a), after retrieving a. This relationship was parameterized for various scattering geometries, including sensor zenith/azimuth angles relative to the Sun's principal plane, and for varying Sun zenith angles. An inversion method was also developed for the retrieval of the microphysical properties of hydrosols, such as the bulk refractive index and the particle size distribution. The DoLP vs c/a relationship was tested and validated against in-situ measurements of underwater light polarization obtained by a custom-built polarimeter and measurements of the coefficients a and c, obtained using an in-water WET (Western Environmental Technologies) Labs ac-s (attenuation coefficients In-Situ Spectrophotometer) instrument package. These measurements confirmed the validity of the approach, with retrievals of attenuation coefficients showing a high coefficient of determination depending on the wavelength. We also performed a sensitivity analysis of the DoLP at the Top of Atmosphere (TOA) over coastal waters showing the possibility of polarimetric remote sensing application for ocean color.

PACE↗
NASA NTRS2019

Space Research Project Management Can Benefit from Engineering Technology Selection Methods

Many engineering methods have been developed to help management select technology for a system design or further research. The simplest way to compare technologies is to use a checklist containing all the more or less important selection criteria, so that nothing is overlooked. The criteria usually include cost, safety, reliability and maintainability, and potential problems such as noise generation and microgravity sensitivity. The next step typically is to weight and score all the criteria. The process of weighting and scoring is helpful in bringing out different priorities and reaching a shared point of view. Group technology selection methods are designed to highlight initial disagreements and produce a shared consensus. Often a frank discussion led by management rather than decision analysts can be more effective. The final selection depends on management and engineering judgment and may include programmatic and organizational factors that are beyond the engineering checklist. The objective of engineering technology selection methods is to provide engineering information to assist management in making sound decisions. Project management and technology selection are assumed to use rational engineering analytic methods, but they often do not. The reason is that human insight, intuition, and “gut feel,” rather than logic, more frequently determine our decisions. Project selection and management are strongly influenced by nonrational psychological influences, which can produce unjustified confidence and determination. Nevertheless, there is a strong need for space projects to do rational project analysis and selection. Demonstrating a rational spirit is necessary for a scientific and technical organization. Professional ethics at its best requires an open, honest, and fair process, without damaging politics. Rational analysis can help improve good projects and avoid selecting bad ones. A sanity check using rational analysis guided by a checklist can help avoid egregious and damaging errors.

Jones, Harry W.↗
NASA NTRS2010

Combining Model-Based and Feature-Driven Diagnosis Approaches - A Case Study on Electromechanical Actuators

Model-based diagnosis typically uses analytical redundancy to compare predictions from a model against observations from the system being diagnosed. However this approach does not work very well when it is not feasible to create analytic relations describing all the observed data, e.g., for vibration data which is usually sampled at very high rates and requires very detailed finite element models to describe its behavior. In such cases, features (in time and frequency domains) that contain diagnostic information are extracted from the data. Since this is a computationally intensive process, it is not efficient to extract all the features all the time. In this paper we present an approach that combines the analytic model-based and feature-driven diagnosis approaches. The analytic approach is used to reduce the set of possible faults and then features are chosen to best distinguish among the remaining faults. We describe an implementation of this approach on the Flyable Electro-mechanical Actuator (FLEA) test bed.

Narasimhan, Sriram↗
NASA NTRSDate not supplied

Clinical Decision Support Project

As NASA plans for exploration missions into deep space, significant challenges are realized due to the distance from Earth. Beside the effects of microgravity and radiation exposure, the astronauts face the additional constraints of isolation, lack of resupply, increasingly difficult evacuation, and delayed and disrupted communication with ground-based medical care providers. These constraints require a paradigm shift from current medical care where crews rely on the real-time communications with ground-based medical care providers toward Earth-independent medical operations for astronaut medical care. Medical expertise and decision-making are ground-based for current International Space Station and planned Lunar missions. However, a deep space exploration crew will need to autonomously perform the detection, diagnosis, treatment, and prevention of medical conditions. One approach to provide Earth-independent medical operations is to augment the requisite knowledge, skills, and abilities (KSAs) of a time-constrained crew—operating under stressful conditions, combatting fatigue, and facing a potential medical crisis—with a robust clinical decision support system (CDSS). The CDSS is envisioned as an integrated, software-based tool deployed on a laptop computer or handheld device. The CDSS will assist the crew and ground support when interacting with knowledge/data bases (e.g. records, pharmacy, schedule), instrumentation (e.g. imaging, physiological monitoring devices), and habitat (e.g. wellness system, task performance system) and vehicle systems (e.g. environmental system, communication system). In addition, the human interface will employ a context-based approach that accounts for the crew’s situation. Thus, extraneous and clinically/operationally non-relevant information are reduced to avoid an increase in cognitive load. The framework of an ideal spaceflight CDSS is to include core and advanced analytical features that maintain a flexible platform for integrating new technology in the future. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) is expanding the boundaries of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit by actively identifying and testing next-generation medical care and crew health maintenance technologies. The Clinical Decision Support (CDS) project addressed ap Medical-701 within the Inflight Medical Conditions risk: “We need to increase inflight medical capabilities and identify new capabilities that (a) maximize benefit and/or (b) reduce “costs” on human system/mission/vehicle resources.” Though mass, volume, and power will face increasing constraints, the projected computational capabilities of spacecraft systems will increase exponentially as information technology advances in this decade and beyond. Hence, data, software, and computational resources will play an essential and synergistic role in maintaining crew health, wellness, and performance in deep space missions. The focus of the CDS project was to develop recommended requirements for an in-vehicle CDSS that acts as a ‘virtual assistant’ for delivering optimal health, performance, and medical care during exploration missions. In fiscal year 2022 (FY22), the CDS project was chartered to baseline and/or revise all CDS project related documentation and update the CDS project model to include the revised CDSS Concept of Operations, revised systems-based modeling language (SysML) activity diagrams, and baseline requirements. The focus of this presentation will be an overview of the CDS products and CDS model content.

Decision Support↗
NASA NTRS1962

VISUAL CONTROL OF RENDEZVOUS

Space rendezvous involving human occupants will be required in many phases of space flight. In order that rendezvous capability be concurrent with other phases of manned space flight to insure that such tasks as the rotation and addition of crews for manned space station, supply of stations and launching complexes for deep-space probes, and the emergency rescue of personnel may be carried out, it is desirable to determine the ability of a human pilot to control the rendezvous maneuver. The National Aeronautics and Space Administration has conducted a study program to determine vehicle requirements and control techniques for a number of proposed methods for performing piloted space rendezvous. The final step in each phase of the rendezvous study program has been a simulation of the man-machine combination to test its feasibility. Initially, an analytical study was conducted to determine a range of conditions that would exist at the beginning of the terminal phase of rendezvous (ref. 1). Piloted systems were investigated for rendezvous control using these initial conditions. One such study of piloted rendezvous in which all the required control information was displayed to the simulator pilot on instruments is presented in reference 2. While the control of the rendezvous maneuver by use of the instrument display was shown to be feasible, the sufficiently accurate measurement of the necessary information to operate the instrument was realized to be a difficult problem. Consideration was therefore given to the possibility of maneuvering range and range rate required for the control of the rendezvous from visual sightings made during the initial control application. To provide this capability, an analytical study was made. This analytical study, presented in reference 3, derived three techniques for obtaining range and range rate visually and conducted a simplified preliminary situation to test the three analytical techniques. The study reported herein is a continuation of the simulation work begun in reference 3, and is aimed at determining the ability of a pilot to use visual information to reduce or eliminate the need for some or all of the data that would normally be displayed on instruments.

Rendezvous↗
NASA NTRS1978

Analytical techniques for the study of some parameters of multispectral scanner systems for remote sensing

The author has identified the following significant results. The concept of average mutual information in the received spectral random process about the spectral scene was developed. Techniques amenable to implementation on a digital computer were also developed to make the required average mutual information calculations. These techniques required identification of models for the spectral response process of scenes. Stochastic modeling techniques were adapted for use. These techniques were demonstrated on empirical data from wheat and vegetation scenes.

Wiswell, E. R.↗
NASA NTRSDate not supplied

End-To-End Uncertainty Quantification with Analytical Derivatives for Design Under Uncertainty

Uncertainty quantification (UQ) is a rapidly growing and evolving discipline, especially within the aerospace community. Performing analysis with UQ can provide decision makers with a wealth of information about a candidate design. However, the value of UQ is fully realized when the information gained during UQ analysis is leveraged in a feedback loop of a design optimization process, often referred to as design under uncertainty. Although design under uncertainty can be a powerful risk mitigation technique, there are a number of roadblocks that prevent its implementation. Two primary factors are computational costs and added complexity of the analysis. High fidelity simulations on the order tens of uncertain variables quickly become computationally infeasible. Also, implementing UQ into an existing multidisciplinary design and optimization (MDO) process often requires extensive knowledge of the UQ methods and careful treatment of the problem formulation. The objective of this work is to address these two primary roadblocks and enable practitioners to efficiently perform design under uncertainty with limited knowledge of the UQ discipline. Methods outlined in this paper demonstrate MDO incorporating UQ into the design process, leveraging an analytic derivative tool chain through the entire optimization. The proposed approach leverages machine learning techniques to generate a differentiable confidence interval output from polynomial chaos models. This technique, coupled with the incorporation of analytical derivatives through the Polynomial Chaos Expansion (PCE) process, eliminates the need to estimate derivatives which are usually obtained from finite difference, complex step, or similar methods. Developing a differentiable confidence interval allows mixed uncertainty problems (both epistemic and aleatory) to be modeled. Without such modeling, these problems cannot accurately predict objective functions containing statistical quantities such as mean and variance. The addition of analytic derivatives to a polynomial chaos-based UQ method decreases the computational costs of performing design under uncertainty by orders of magnitude in comparison with methods such as complex step. The method and codes developed are modular in nature and are a drop-in solution for design under uncertainty within existing MDO problems. A low-fidelity analytical multidisciplinary optimization under uncertainty for a wing design in OpenMDAO is detailed in this paper. This demonstration case will include both objective functions and constraints which are influenced by uncertain parameters.

Ben D Phillips↗
NASA NTRSDate not supplied

End-To-End Uncertainty Quantification with Analytical Derivatives for Design Under Uncertainty

Uncertainty quantification (UQ) is a rapidly growing and evolving discipline, especially within the aerospace community. Performing analysis with UQ can provide decision makers with a wealth of information about a candidate design. However, the value of UQ is fully realized when the information gained during UQ analysis is leveraged in a feedback loop of a design optimization process, often referred to as design under uncertainty. Although design under uncertainty can be a powerful risk mitigation technique, there are a number of roadblocks that prevent its implementation. Two primary factors are computational costs and added complexity of the analysis. High fidelity simulations on the order tens of uncertain variables quickly become computationally infeasible. Also, implementing UQ into an existing multidisciplinary design and optimization (MDO) process often requires extensive knowledge of the UQ methods and careful treatment of the problem formulation. The objective of this work is to address these two primary roadblocks and enable practitioners to efficiently perform design under uncertainty with limited knowledge of the UQ discipline. Methods outlined in this paper demonstrate MDO incorporating UQ into the design process, leveraging an analytic derivative tool chain through the entire optimization. The proposed approach leverages machine learning techniques to generate a differentiable confidence interval output from polynomial chaos models. This technique, coupled with the incorporation of analytical derivatives through the Polynomial Chaos Expansion (PCE) process, eliminates the need to estimate derivatives which are usually obtained from finite difference, complex step, or similar methods. Developing a differentiable confidence interval allows mixed uncertainty problems (both epistemic and aleatory) to be modeled. Without such modeling, these problems cannot accurately predict objective functions containing statistical quantities such as mean and variance. The addition of analytic derivatives to a polynomial chaos-based UQ method decreases the computational costs of performing design under uncertainty by orders of magnitude in comparison with methods such as complex step. The method and codes developed are modular in nature and are a drop-in solution for design under uncertainty within existing MDO problems. A low-fidelity analytical multidisciplinary optimization under uncertainty for a wing design in OpenMDAO is detailed in this paper. This demonstration case will include both objective functions and constraints which are influenced by uncertain parameters.

Ben Phillips↗
NASA NTRS2019

Analysis Ready Data in Analytics Optimized Data Stores for Analysis of Big Earth Data in the Cloud

Cloud computing offers the possibility of making the analysis of Big Data approachable for a wider community due to affordable access to computing power, an ecosystem of usable tools for parallel processing, and migration of many large datasets to archives in the cloud, allowing data-proximal computing. Generally, data analysis acceleration in the cloud comes from running multiple nodes in a split-combine-apply strategy. Data systems such as the Earth Observing System Data and Information System are in a position to "pre-split" the data by storing them in a data store that is optimized for data parallel computing, i.e., an Analytics-Optimized Data Store (AODS). A variety of approaches to AODS are possible, from highly scalable databases to scalable filesystems to data formats optimized for cloud access (e.g., zarr and cloud-optimized datasets), with the optimal choice dependent on both the types of analysis and the geospatial structure of the data. A key question is how much preprocessing of the data to do, both before splitting and as the first part of the apply step. Again, the geospatial structure of the data and the analysis type influence the decision, with the added complexity of the user type. Trans-disciplinary users who are not well-versed in the nuances of quality-filtering and georeferencing of remote sensing orbit/swath/scene data tend to ask for more highly processed data, relying on the data provider to make sensible decisions on preprocessing parameters. (This accounts for the popularity of "Level 3" gridded data, despite the lower spatial resolution it provides.) In this case, data can be preprocessed before the split, resulting in higher performance in the rest of the "apply" step, which can be transformative for use cases such as interactive data exploration at scale. Discipline researchers who are experienced with remote sensing data often prefer more flexibility in customizing the preprocessing data into Analysis Ready Data, resulting in more need for on-the-fly preprocessing.

Lynnes, Christopher↗
NASA NTRS1974

Generalized dynamic engine simulation techniques for the digital computer

Recently advanced simulation techniques have been developed for the digital computer and used as the basis for development of a generalized dynamic engine simulation computer program, called DYNGEN. This computer program can analyze the steady state and dynamic performance of many kinds of aircraft gas turbine engines. Without changes to the basic program DYNGEN can analyze one- or two-spool turbofan engines. The user must supply appropriate component performance maps and design-point information. Examples are presented to illustrate the capabilities of DYNGEN in the steady state and dynamic modes of operation. The analytical techniques used in DYNGEN are briefly discussed, and its accuracy is compared with a comparable simulation using the hybrid computer. The impact of DYNGEN and similar all-digital programs on future engine simulation philosophy is also discussed.

Sellers, J.↗
NASA NTRS1974

Generalized dynamic engine simulation techniques for the digital computer

Recently advanced simulation techniques have been developed for the digital computer and used as the basis for development of a generalized dynamic engine simulation computer program, called DYNGEN. This computer program can analyze the steady state and dynamic performance of many kinds of aircraft gas turbine engines. Without changes to the basic program, DYNGEN can analyze one- or two-spool turbofan engines. The user must supply appropriate component performance maps and design-point information. Examples are presented to illustrate the capabilities of DYNGEN in the steady state and dynamic modes of operation. The analytical techniques used in DYNGEN are briefly discussed, and its accuracy is compared with a comparable simulation using the hybrid computer. The impact of DYNGEN and similar all-digital programs on future engine simulation philosophy is also discussed.

Sellers, J.↗
NASA NTRS1975

Generalized dynamic engine simulation techniques for the digital computers

Recently advanced simulation techniques have been developed for the digital computer and used as the basis for development of a generalized dynamic engine simulation computer program, called DYNGEN. This computer program can analyze the steady state and dynamic performance of many kinds of aircraft gas turbine engines. Without changes to the basic program, DYNGEN can analyze one- or two-spool turbofan engines. The user must supply appropriate component performance maps and design point information. Examples are presented to illustrate the capabilities of DYNGEN in the steady state and dynamic modes of operation. The analytical techniques used in DYNGEN are briefly discussed, and its accuracy is compared with a comparable simulation using the hybrid computer. The impact of DYNGEN and similar digital programs on future engine simulation philosophy is also discussed.

Sellers, J.↗
NASA NTRS1982

The initial conceptualization and design of a meteorological satellite

The meteorological satellite had its substantive origin in the analytical process that helped initiate America's military satellite program. Its impetus lay in the desire to acquire current meteorological information in large areas for which normal meteorological observational data were not available on a day-to-day basis. Serious consideration was given to the feasibility of reconnaissance from meteorological satellites. The conceptualization of a meteorological satellite is discussed along with the early research which gave substance to that concept.

Greenfield, S. M.↗
NASA NTRS1985

Application of FDI metrics to detection and isolation of sensor failures in turbine engines

This paper develops a framework for the design of failure detection and isolation (FDI) algorithms. Rather than trying to apply 'optimal' techniques in a top-down manner, the system redundancies are evaluated with respect to their ability to provide reliable FDI information. Previous work of Pattipati et al. (1984) and Weiss et al. (1984) defined a useful context and several useful analytical results, which provide a basis for the FDI design methodology developed here. A general decision structure which can take advantage of redundancy evaluation is presented, and examples of typical design considerations are discussed. The operation of the decision structure is then demonstrated for a sensor FDI application involving the F-100 jet engine.

Weiss, J. L.↗
NASA NTRS1986

Studies of asteroids and comets

About 3000 accurate positions of asteroids and comets were measured concentrating particularly on close-Earth approachers, but also targeting asteroids in need for follow-up observations because of unusual orbital characteristics or poor observational history. In 1985, 36 of the discoveries were numbered. Very accurate + or - 0.1 arcsec?) positional measurements were made of P/Halley on four nights in November and December 1985 in support of Giotto mission navigation. The asteroid orbit files were maintained, and ephemeris data for observational planning were supplied to colleagues worldwide. Considerable progress was made in understanding how information on asteroid shapes, surface albedo variegation, and rotational states can be derived from lightcurve and phase curve data. The analytical formulation was completed of a new asteroid magnitude system for the International Astronomical Union; the system was adopted at the New Delhi General Assembly by IAU Commission 20. Photographic photometry of about 10000 images of faint asteroids observed during the course of the United Kingdom Schmidt-CalTech Asteroid Survey in 1981 was continued, completing the microdensitometric scanning and all process of software development for data handling.

Bowell, E. L. G.↗
NASA NTRS1987

Aeroelastic effects in multirotor vehicles. Part 2: Methods of solution and results illustrating coupled rotor/body aeromechanical stability

This report is a sequel to the earlier report titled, Aeroelastic Effects in Multi-Rotor Vehicles with Application to Hybrid Heavy Lift System, Part 1: Formulation of Equations of Motion (NASA CR-3822). The trim and stability equations are presented for a twin rotor system with a buoyant envelope and an underslung load attached to a flexible supporting structure. These equations are specialized for the case of hovering flight. A stability analysis, for such a vehicle with 31 degrees of freedom, yields a total of 62 eigenvalues. A careful parametric study is performed to identify the various blade and vehicle modes, as well as the coupling between various modes. Finally, it is shown that the coupled rotor/vehicle stability analysis provides information on both the aeroelastic stability as well as complete vehicle dynamic stability. Also presented are the results of an analytical study aimed at predicting the aeromechanical stability of a single rotor helicopter in ground resonance. The theoretical results are found to be in good agreement with the experimental results, thereby validating the analytical model for the dynamics of the coupled rotor/support system.

Venkatesan, C.↗
NASA NTRS1992

On the Gibbs phenomenon 1: Recovering exponential accuracy from the Fourier partial sum of a non-periodic analytic function

It is well known that the Fourier series of an analytic or periodic function, truncated after 2N+1 terms, converges exponentially with N, even in the maximum norm, although the function is still analytic. This is known as the Gibbs phenomenon. Here, we show that the first 2N+1 Fourier coefficients contain enough information about the function, so that an exponentially convergent approximation (in the maximum norm) can be constructed.

Gottlieb, David↗