Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Reliability assessment”

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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Qualifications of Bonding Process of Temperature Sensors to Deep-Space Missions

A process has been examined for bonding a platinum resistance thermometer (PRT) onto potential aerospace materials such as flat aluminum surfaces and a flexible copper tube to simulate coaxial cables for flight applications. Primarily, PRTs were inserted into a silver-plated copper braid to avoid stresses on the sensor while the sensor was attached with the braid to the base material for long-duration, deep-space missions. A1-1145/graphite composite (planar substrate) and copper tube have been used in this study to assess the reliability of PRT bonding materials. A flexible copper tube was chosen to simulate the coaxial cable to attach PRTs. The substrate materials were cleaned with acetone wipes to remove oils and contaminants. Later, the surface was also cleaned with ethyl alcohol and was air-dried. The materials were gently abraded and then were cleaned again the same way as previously mentioned. Initially, shielded (silver plated copper braid) PRT (type X) test articles were fabricated and cleaned. The base antenna material was pretreated and shielded, and CV-2566 NuSil silicone was used to attach the shielded PRT to the base material. The test articles were cured at room temperature and humidity for seven days. The resistance of the PRTs was continuously monitored during the thermal cycling, and the test articles were inspected prior to, at various intermediate steps during, and at the end of the thermal cycling as well. All of the PRTs survived three times the expected mission life for the JUNO project. No adhesion problems were observed in the PRT sensor area, or under the shielded PRT. Furthermore, the PRT resistance accurately tracked the thermal cycling of the chamber.

Ramesham, Rajeshuni↗
NASA NTRS2013

Comparison Between NPP-VIIRS Aerosol Data Products and the MODIS AQUA Deep Blue Collection 6 Dataset Over Land

Aerosols are small particles suspended in the atmosphere and have a variety of natural and man-made sources. Knowledge of aerosol optical depth (AOD), which is a measure of the amount of aerosol in the atmosphere, and its change over time, is important for multiple reasons. These include climate change, air quality (pollution) monitoring, monitoring hazards such as dust storms and volcanic ash, monitoring smoke from biomass burning, determining potential energy yields from solar plants, determining visibility at sea, estimating fertilization of oceans and rainforests by transported mineral dust, understanding changes in weather brought upon by the interaction of aerosols and clouds, and more. The Suomi-NPP satellite was launched late in 2011. The Visible Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi-NPP is being used, among other things, to determine AOD. This study compares the VIIRS dataset to ground-based measurements of AOD, along with a state-of-the-art satellite AOD dataset (the new version of the Moderate Resolution Imaging Spectrometer Deep Blue algorithm) to assess its reliability. The Suomi-NPP satellite was launched late in 2011, carrying several instruments designed to continue the biogeophysical data records of current and previous satellite sensors. The Visible Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi-NPP is being used, among other things, to determine aerosol optical depth (AOD), and related activities since launch have been focused towards validating and understanding this new dataset through comparisons with other satellite and ground-based products. The operational VIIRS AOD product is compared over land with AOD derived from Moderate Resolution Imaging Spectrometer (MODIS) observations using the Deep Blue (DB) algorithm from the forthcoming Collection 6 of MODIS data

Sayer, Andrew M.↗
NASA NTRS2012

Intercomparison of the LASCO-C2, SECCHI-COR1, SECCHI-COR2, and Mk4 Coronagraphs

In order to assess the reliability and consistency of white-light coronagraph measurements, we report on quantitative comparisons between polarized brightness [pB] and total brightness [B] images taken by the following white-light coronagraphs: LASCO-C2 on SOHO, SECCHI-COR1 and -COR2 on STEREO, and the ground-based MLSO-Mk4. The data for this comparison were taken on 16 April 2007, when both STEREO spacecraft were within 3.1 deg. of Earth’s heliographic longitude, affording essentially the same view of the Sun for all of the instruments. Due to the difficulties of estimating stray-light backgrounds in COR1 and COR2, only Mk4 and C2 produce reliable coronal-hole values (but not at overlapping heights), and these cannot be validated without rocket flights or ground-based eclipse measurements. Generally, the agreement between all of the instruments’ pB values is within the uncertainties in bright streamer structures, implying that measurements of bright CMEs also should be trustworthy. Dominant sources of uncertainty and stray light are discussed, as is the design of future coronagraphs from the perspective of the experiences with these instruments.

Coronagraph↗
NASA NTRS2013

Prediction of Seasonal Climate-induced Variations in Global Food Production

Consumers, including the poor in many countries, are increasingly dependent on food imports and are therefore exposed to variations in yields, production, and export prices in the major food-producing regions of the world. National governments and commercial entities are paying increased attention to the cropping forecasts of major food-exporting countries as well as to their own domestic food production. Given the increased volatility of food markets and the rising incidence of climatic extremes affecting food production, food price spikes may increase in prevalence in future years. Here we present a global assessment of the reliability of crop failure hindcasts for major crops at two lead times derived by linking ensemble seasonal climatic forecasts with statistical crop models. We assessed the reliability of hindcasts (i.e., retrospective forecasts for the past) of crop yield loss relative to the previous year for two lead times. Pre-season yield predictions employ climatic forecasts and have lead times of approximately 3 to 5 months for providing information regarding variations in yields for the coming cropping season. Within-season yield predictions use climatic forecasts with lead times of 1 to 3 months. Pre-season predictions can be of value to national governments and commercial concerns, complemented by subsequent updates from within-season predictions. The latter incorporate information on the most recent climatic data for the upcoming period of reproductive growth. In addition to such predictions, hindcasts using observations from satellites were performed to demonstrate the upper limit of the reliability of crop forecasting.

variations↗
NASA NTRS2012

High Temperature Ultrasonic Transducers : Material Selection and Testing

The task of my two-months internship was to test different materials to be used to build an high temperature transducer, to develop some prototypes and to test their performance, to assess the reliability of commercial product rated for such a temperature, as well as to collaborate in developing the signal processing code to measure the condensed water levels.

health monitoring steam pipes↗
NASA NTRS2011

Integrating Machine Learning into a Crowdsourced Model for Earthquake-Induced Damage Assessment

On January 12th, 2010, a catastrophic 7.0M earthquake devastated the country of Haiti. In the aftermath of an earthquake, it is important to rapidly assess damaged areas in order to mobilize the appropriate resources. The Haiti damage assessment effort introduced a promising model that uses crowdsourcing to map damaged areas in freely available remotely-sensed data. This paper proposes the application of machine learning methods to improve this model. Specifically, we apply work on learning from multiple, imperfect experts to the assessment of volunteer reliability, and propose the use of image segmentation to automate the detection of damaged areas. We wrap both tasks in an active learning framework in order to shift volunteer effort from mapping a full catalog of images to the generation of high-quality training data. We hypothesize that the integration of machine learning into this model improves its reliability, maintains the speed of damage assessment, and allows the model to scale to higher data volumes.

crowdsourcing↗
NASA NTRS2015

Free-Energy Calculations. A Mathematical Perspective

Ion channels are pore-forming assemblies of transmembrane proteins that mediate and regulate ion transport through cell walls. They are ubiquitous to all life forms. In humans and other higher organisms they play the central role in conducting nerve impulses. They are also essential to cardiac processes, muscle contraction and epithelial transport. Ion channels from lower organisms can act as toxins or antimicrobial agents, and in a number of cases are involved in infectious diseases. Because of their important and diverse biological functions they are frequent targets of drug action. Also, simple natural or synthetic channels find numerous applications in biotechnology. For these reasons, studies of ion channels are at the forefront of biophysics, structural biology and cellular biology. In the last decade, the increased availability of X-ray structures has greatly advanced our understanding of ion channels. However, their mechanism of action remains elusive. This is because, in order to assist controlled ion transport, ion channels are dynamic by nature, but X-ray crystallography captures the channel in a single, sometimes non-native state. To explain how ion channels work, X-ray structures have to be supplemented with dynamic information. In principle, molecular dynamics (MD) simulations can aid in providing this information, as this is precisely what MD has been designed to do. However, MD simulations suffer from their own problems, such as inability to access sufficiently long time scales or limited accuracy of force fields. To assess the reliability of MD simulations it is only natural to turn to the main function of channels - conducting ions - and compare calculated ionic conductance with electrophysiological data, mainly single channel recordings, obtained under similar conditions. If this comparison is satisfactory it would greatly increase our confidence that both the structures and our computational methodologies are sufficiently accurate. Channel conductance, defined as the ratio of ionic current through the channel to applied voltage, can be calculated in MD simulations by way of applying an external electric field to the system and counting the number of ions that traverse the channel per unit time. If the current is small, a voltage significantly higher than the experimental one needs to be applied to collect sufficient statistics of ion crossing events. Then, the calculated conductance has to be extrapolated to the experimental voltage using procedures of unknown accuracy. Instead, we propose an alternative approach that applies if ion transport through channels can be described with sufficient accuracy by the one-dimensional diffusion equation in the potential given by the free energy profile and applied voltage. Then, it is possible to test the assumptions of the equation, recover the full voltage/current dependence, determine the reliability of the calculated conductance and reconstruct the underlying (equilibrium) free energy profile, all from MD simulations at a single voltage. We will present the underlying theory, model calculations that test this theory and simulations on ion conductance through a channel that has been extensively studied experimentally. To our knowledge this is the first case in which the complete, experimentally measured dependence of the current on applied voltage has been reconstructed from MD simulations.

free energy↗
NASA NTRS2017

Organic Molecules On the Surfaces of Iapetus and Phoebe

Absorption bands of both aliphatic and aromatic organic molecules are found in the reflectance spectra of Saturn satellites Iapetus, Phoebe, and Hyperion obtained with the Cassini Visible-Infrared Mapping Spectrometer (VIMS). The VIMS data do not fully resolve the individual bands of C-H functional groups specific to particular molecules, but instead show absorption envelopes representing blended clusters of the bands of aromatic (approximately 3.28 microns) and aliphatic (approximately 3.4 microns) hydrocarbons known in spectra of interstellar dust. In Cruikshank et al. (2014), we matched components of the unresolved hydrocarbon band envelopes with clusters of bands of a range of functional groups in specific types of organic compounds (e.g., normal and N-substituted polycyclic aromatic hydrocarbons, olefins, cycloalkanes, and molecules with lone-pair interactions of N and O with CH3+). In the work reported here, we revisit the spectra of Iapetus and Phoebe using VIMS data processed with improved radiometric and wavelength calibration (denoted RC19). The band envelopes of both aromatic and aliphatic hydrocarbons are now more clearly defined, corroborating the provisional assignment of specific classes of molecules in Cruikshank et al. 2014, but permitting a more reliable quantitative assessment of the relative contributions of those classes, and a revision to the earlier estimate of the ratio of the abundances of aromatic to aliphatic molecules.

Phoeb↗
NASA NTRS2018

NC Space Grant Report

During the summer of 2018 I supported the Safety & Mission Assurance Directorate (SMA) and Operations Support Division (QA-20) at Stennis Space Center. The mission of the SMA team is to prove safety, risk, reliability, independent assessments, configuration management and quality assurance guidance, and services for all NASA Stennis Space Center (SSC) programs, facilities, and supporting infrastructure. The office actively participates and contributes to the Agency-level Safety & Mission Assurance (S&MA) effort. Over the course of the Summer I participated in three projects. Two of them were focused around Fault Tree Analysis (FTA) and the third focused on relief valves for their E-1 engine test stand.

Torres, David↗
NASA NTRS2019

Application of High-Dimensional Fuzzy K-Means Cluster Analysis to CALIOP/CALIPSO Version 4.1 Cloud-Aerosol Discrimination

This study applies fuzzy k-means (FKM) cluster analyses to a subset of the parameters reported in the CALIPSO lidar level 2 data products in order to classify the layers detected as either clouds or aerosols. The results obtained are used to assess the reliability of the cloud–aerosol discrimination (CAD) scores reported in the version 4.1 release of the CALIPSO data products. FKM is an unsupervised learning algorithm, whereas the CALIPSO operational CAD algorithm (COCA) takes a highly supervised approach. Despite these substantial computational and architectural differences, our statistical analyses show that the FKM classifications agree with the COCA classifications for more than 94 % of the cases in the troposphere. This high degree of similarity is achieved because the lidar-measured signatures of the majority of the clouds and the aerosols are naturally distinct, and hence objective methods can independently and effectively separate the two classes in most cases. Classification differences most often occur in complex scenes (e.g., evaporating water cloud filaments embedded in dense aerosol) or when observing diffuse features that occur only intermittently (e.g., volcanic ash in the tropical tropopause layer). The two methods examined in this study establish overall classification correctness boundaries due to their differing algorithm uncertainties. In addition to comparing the outputs from the two algorithms, analysis of sampling, data training, performance measurements, fuzzy linear discriminants, defuzzification, error propagation, and key parameters in feature type discrimination with the FKM method are further discussed in order to better understand the utility and limits of the application of clustering algorithms to space lidar measurements. In general, we find that both FKM and COCA classification uncertainties are only minimally affected by noise in the CALIPSO measurements, though both algorithms can be challenged by especially complex scenes containing mixtures of discrete layer types. Our analysis results show that attenuated backscatter and color ratio are the driving factors that separate water clouds from aerosols; backscatter intensity, depolarization, and mid-layer altitude are most useful in discriminating between aerosols and ice clouds; and the joint distribution of backscatter intensity and depolarization ratio is critically important for distinguishing ice clouds from water clouds.

Zeng, Shan↗
NASA NTRSDate not supplied

Development and Initial Validation of HFBP-EM Short-Form Surveys

The Human Factors and Behavioral Performance Exploration Measures (HFBP-EM) suite includes self-report surveys designed to assess Behavioral Medicine (BMed) and Team risks for future exploration class missions. Survey data was collected during the Human Exploration Research Analog (HERA) Campaign 4 (C4), HERA Campaign 5 (C5), and during SIRIUS19 missions in the Russian Ground Based Experiment Complex, NEK. Crew time in spaceflight analogs and in spaceflight is typically limited. Extensive self-report surveys can be a significant burden to participants and are not operationally acceptable for spaceflight. The purpose of this project was to comprehensively assess the reliability and validity of the standard-length HFBP-EM surveys, identify acceptable short forms to administer during HERA C6, examine initial validation evidence for the proposed short form measures, and identify key measurement gaps in HFBP-EM coverage. In this presentation, we will report reliability and validity metrics of standard form data, describe the proposed new short forms, and present initial psychometric analyses supporting the use of these short forms.

S T Bell↗
NASA NTRSDate not supplied

Assessing Risk Due to Small Sample Size in Probability of Detection Analysis Using Tolerance Intervals

Small sample size (e.g.6-30) poses risk in results of probability of detection (POD) analysis using tolerance intervals. This method is also called as the limited sample or LS POD. The analysis is performed either during NDE procedure qualification or for assessment of reliability of an NDE procedure. The risk is primarily due to sampling error. Smaller samples are not likely to be random to the population or representative of the population. The small samples are likely to be biased. Biased samples have smaller standard deviation compared to the population. POD analysis with small biased sample can lead to overestimation of POD. Many sampling schemes are available in statistics to mitigate sampling risk. Primary objective of POD analysis is to determine a decision threshold from signal response measurements of a sample such that it is less than or equal to population decision threshold for 90% POD. Sampling error implies that this NDE reliability condition is violated. One of sampling types is called a representative sample. Representative samples reduce variance in POD estimates but also reduce magnitude of the error. Sampling sensitivity analysis for some sampling types is performed here using repetitive random sampling or Monte Carlo method. Six sampling types are considered for comparison. Some of the sampling types are similar to drawing a representative sample. LS POD model assumes random sampling. Therefore, random sampling is used as a basis for comparison with each sampling type. The sampling types used in the analysis are, A. Nominal and worst-case sampling, B. Worst-case sampling, C. Nominal case sampling, D. Random sampling, E. Random target, and sub-target sampling. F. Nominal target and sub-target sampling. Results of Monte Carlo simulation indicate that type F sampling can mitigate sampling risk and is also more practical to implement. Type A sampling may also mitigate the sampling risk, but it may be less practical to implement.

Ajay M Koshti↗
NASA NTRSDate not supplied

HIFiRE Flight 2 Unstart Reliability Analysis

The objective of this work was to assess the unstart reliability of the HIFiRE Flight 2 system. To do this, a quantification of margins and uncertainties framework was used for comparing model predictions of the predicted combustion induced shock location to the predicted last stable shock location within the isolator. Uncertainty sources included parametric uncertainty in the flight conditions, the heat release model, and turbulence modeling, as well as model verification errors. Additionally, an estimate of model-form uncertainty was established by comparing the model to measured ground test data. A computationally efficient non-intrusive polynomial chaos approach was used to propagate parametric uncertainty through the computational flu-ids dynamics models of both the ground test configuration and the flight vehicle. Compared to direct-connect ground test data, computational fluid dynamics predictions yielded about two duct heights of model-form uncertainty. This was applied to a prediction of flight vehicle unstart margin at the Mach 6.5 flight condition. Building up all of the computational model uncertainty, including parametric uncertainty, verification errors, and the determined model-form uncertainty, a 95% probability level based confidence ratio, or a ratio of total uncertainty to a statistical margin measure, was found to be 0.31 for the flight system.

Thomas K West↗
NASA NTRS2022

Tri-Agency Reliability Engineering Post: Mission Disposal and Extension Assessment Guidance Addendum

The intent of this addendum is to support the guidance document, Tri-Agency Reliability Engineering Guidance: Post Mission Disposal and Extension Assessment (https://ntrs.nasa.gov/citations/20210024973). It is intended to further assist spacefaring entities in assessing their designs and operational plans for extending missions and Post Mission Disposal (PMD) by providing an hypothetical mission example.

Digital transformation↗
NASA NTRS2012

Reliability Impacts in Life Support Architecture and Technology Selection

Quantitative assessments of system reliability and equivalent system mass (ESM) were made for different life support architectures based primarily on International Space Station technologies. The analysis was applied to a one-year deep-space mission. System reliability was increased by adding redundancy and spares, which added to the ESM. Results were thus obtained allowing a comparison of the ESM for each architecture at equivalent levels of reliability. Although the analysis contains numerous simplifications and uncertainties, the results suggest that achieving necessary reliabilities for deep-space missions will add substantially to the life support ESM and could influence the optimal degree of life support closure. Approaches for reducing reliability impacts were investigated and are discussed.

Lange Kevin E.↗
NASA NTRS2014

An Integrated Reliability and Physics-Based Risk Modeling Approach for Assessing Human Spaceflight Systems

This paper presents an integrated reliability and physics-based risk modeling approach for assessing human spaceflight systems. The approach is demonstrated using an example, end-to-end risk assessment of a generic-crewed space transportation system during a reference mission to the International Space Station. The behavior of the system is modeled using analysis techniques from multiple disciplines in order to properly capture the dynamic time- and state- dependent consequences of failures encountered in different mission phases. We discuss how to combine traditional reliability analyses with Monte Carlo simulation methods and physics-based engineering models to produce loss-of- mission and loss-of-crew risk estimates supporting risk-based decision-making and requirement verification. This approach facilitates risk-informed design by providing more realistic representation of system failures and interactions; identifying key risk-driving sensitivities, dependencies, and assumptions; and tracking multiple figures of merit within a single, responsive assessment framework that can readily incorporate evolving design information throughout system development.

Risk assessment↗