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At least 55 records · Page 3

Predicting Large‐Scale Systematic Missing Pipe Attributes in Water Distribution Networks

Water distribution network (WDN) models are an essential tool used by water utilities for hydraulic analysis. Unfortunately, missing data and insufficient resources often make creating and maintaining these models unfeasible. Existing methods to address missing pipe properties, like sequential imputation for missing values and reconstruction using graph metrics, are designed to accommodate random patterns of missing information and require a significant percentage of the system's attributes to be known. However, these data completeness assumptions do not always align with real‐world scenarios where large sections of the WDN model have missing data. To address this challenge, this study proposes a data‐driven approach for estimating pipe diameter when considering different spatial patterns and degrees of data completeness (i.e., 0%–90%). Using data from 16 WDNs in Kentucky, this study compares the use of machine learning (ML) using topological and geospatial features against an existing deterministic approach. Results demonstrate that WDN models with pipe diameters predicted by the proposed ML method had comparable hydraulic performance to the ground truth models. Moreover, results showed that ML method performance varies between WDNs of differing topological classification. Insights from this study help advance the ability to leverage partial data to create and maintain WDN models amid uncertainty and inadequate resources.

Poff, Jason W. [Oregon State Univ., Corvallis, OR ↗

Missing observations in multiyear rotation sampling designs

Because Multiyear estimation of at-harvest stratum crop proportions is more efficient than single year estimation, the behavior of multiyear estimators in the presence of missing acquisitions was studied. Only the (worst) case when a segment proportion cannot be estimated for the entire year is considered. The effect of these missing segments on the variance of the at-harvest stratum crop proportion estimator is considered when missing segments are not replaced, and when missing segments are replaced by segments not sampled in previous years. The principle recommendations are to replace missing segments according to some specified strategy, and to use a sequential procedure for selecting a sampling design; i.e., choose an optimal two year design and then, based on the observed two year design after segment losses have been taken into account, choose the best possible three year design having the observed two year parent design.

Gbur, E. E.↗

The missing impact craters on Venus

The size-frequency pattern of the 842 impact craters on Venus measured to date can be well described (across four standard deviation units) as a single log normal distribution with a mean crater diameter of 14.5 km. This result was predicted in 1991 on examination of the initial Magellan analysis. If this observed distribution is close to the real distribution, the 'missing' 90 percent of the small craters and the 'anomalous' lack of surface splotches may thus be neither missing nor anomalous. I think that the missing craters and missing splotches can be satisfactorily explained by accepting that the observed distribution approximates the real one, that it is not craters that are missing but the impactors. What you see is what you got. The implication that Venus crossing impactors would have the same type of log normal distribution is consistent with recently described distribution for terrestrial craters and Earth crossing asteroids.

Speidel, D. H.↗

Exposure of Polymer Film Thermal Control Materials on the Materials International Space Station Experiment (MISSE)

Seventy-nine samples of polymer film thermal control (PFTC) materials have been provided by the National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) for exposure to the low Earth orbit environment on the exterior of the International Space Station (ISS) as part of the Materials International Space Station Experiment (MISSE). MISSE is a materials flight experiment sponsored by the Air Force Research Lab/Materials Lab and NASA. This paper will describe background, objectives, and configurations for the GRC PFTC samples for MISSE. These samples include polyimides, fluorinated polyimides, and Teflon fluorinated ethylene propylene (FEP) with and without second-surface metallizing layers and/or surface coatings. Also included are polyphenylene benzobisoxazole (PBO) and a polyarylene ether benzimidazole (TOR-LM). On August 16, 2001, astronauts installed passive experiment carriers (PECs) on the exterior of the ISS in which were located twenty-eight of the GRC PFTC samples for 1-year space exposure. MISSE PECs for 3-year exposure, which will contain fifty-one GRC PFTC samples, will be installed on the ISS at a later date. Once returned from the ISS, MISSE GRC PFTC samples will be examined for changes in optical and mechanical properties and atomic oxygen (AO) erosion. Additional sapphire witness samples located on the AO exposed trays will be examined for deposition of contaminants.

Dever, Joyce↗

THE MATERIALS ON INTERNATIONAL SPACE STATION EXPERIMENT (MISSE): FIRST RESULTS FROM MSFC INVESTIGATIONS

Marshall Space Flight Center worked with the Air Force Research Laboratory, Naval Research Laboratory, Langley Research Center, Glenn Research Center, the Jet Propulsion Laboratory, Johnson Space Center, Boeing, Lockheed Martin, TRW, the Aerospace Corporation, Triton Systems, AZ Technology, Alion (formerly IITRI), ENTECH, and L'Garde to bring together the first external materials exposure experiment on International Space Station (ISS). MISSE re-uses hardware from the MEEP flown on the Russian space station Mir. MISSE has returned a treasure trove of materials data that will be useful not only for ISS but also for programs as diverse as the new Crew Exploration Vehicle, the James Webb Telescope, the Lunar Surface Access Module, the Robotic Lunar Exploration Program, High Altitude Airships, and solar sails. MISSE-1 and -2 (Figure 1) were attached to the Quest airlock on ISS for 4 years and were retrieved during STS-114. MISSE-3 and -4 were bumped fr-om STS-114 and are currently slated for deployment during STS-121. MISSE-5 (Figure 2) was deployed during STS-114.

Finckenor, Miria↗

Near-Miss Evaluation Bias as an Obstacle to Organizational Learning: Lessons from NASA

After the Shuttle Columbia catastrophe, the investigation board (CAIB) stated that NASA needs to develop a "learning culture", meaning a capability to learn from past failures by understanding the technical and organizational causes of these mistakes (CAIB report, 2003). While many organizations learn from obvious failures, we argue that it is harder for organizations to learn from near-miss events (i.e., situations where a failure does not occur but nearly did), because these near-misses are processed as successes. For the shuttle program, prior debris problems could have caused a similar failure as on the Columbia mission except that the large pieces missed the highly sensitive portions of the orbiter. This acceptance of foam debris was adopted as a normal occurrence by the shuttle program managers similar to the problems at the time of the Challenger Disaster (detailed in Vaughan, 1996). We extend that work to show that an outcome bias influences people's evaluation of project managers, such that managers of failed missions were perceived more poorly than managers who made the same decisions but whose mission ended in either success or a near-miss. The similarity of ratings between the near-miss and success condition imply that even when a problem occurs that is clearly linked to prior managerial decisions, if the project is not harmed because of good luck, that manager is not held accountable for faculty decision making and neither the individual manager nor the organization learn from the experience potentially increasing the likelihood of a failure in the future.

Dillon, Robin L.↗

MISSE PEACE Polymers Atomic Oxygen Erosion Results

Forty-one different polymer samples, collectively called the Polymer Erosion and Contamination Experiment (PEACE) Polymers, have been exposed to the low Earth orbit (LEO) environment on the exterior of the International Space Station (ISS) for nearly 4 years as part of Materials International Space Station Experiment 2 (MISSE 2). The objective of the PEACE Polymers experiment was to determine the atomic oxygen erosion yield of a wide variety of polymeric materials after long term exposure to the space environment. The polymers range from those commonly used for spacecraft applications, such as Teflon (DuPont) FEP, to more recently developed polymers, such as high temperature polyimide PMR (polymerization of monomer reactants). Additional polymers were included to explore erosion yield dependence upon chemical composition. The MISSE PEACE Polymers experiment was flown in MISSE Passive Experiment Carrier 2 (PEC 2), tray 1, on the exterior of the ISS Quest Airlock and was exposed to atomic oxygen along with solar and charged particle radiation. MISSE 2 was successfully retrieved during a space walk on July 30, 2005, during Discovery s STS-114 Return to Flight mission. Details on the specific polymers flown, flight sample fabrication, pre-flight and post-flight characterization techniques, and atomic oxygen fluence calculations are discussed along with a summary of the atomic oxygen erosion yield results. The MISSE 2 PEACE Polymers experiment is unique because it has the widest variety of polymers flown in LEO for a long duration and provides extremely valuable erosion yield data for spacecraft design purposes.

deGroh, Kim, K.↗

Analysis of International Space Station Vehicle Materials on MISSE 6

The International Space Station Materials and Processes team has multiple material samples on MISSE 6, 7 and 8 to observe Low Earth Orbit (LEO) environmental effects on Space Station materials. Optical properties, thickness/mass loss, surface elemental analysis, visual and microscopic analysis for surface change are some of the techniques employed in this investigation. Results for the following MISSE 6 samples materials will be presented: deionized water sealed anodized aluminum; Hyzod(tm) polycarbonate used to temporarily protect ISS windows; Russian quartz window material; Beta Cloth with Teflon(tm) reformulated without perfluorooctanoic acid (PFOA), and electroless nickel. Discussion for current and future MISSE materials experiments will be presented. MISSE 7 samples are: more deionized water sealed anodized aluminum, including Photofoil(tm); indium tin oxide (ITO) over-coated Kapton(tm) used as thermo-optical surfaces; mechanically scribed tin-plated beryllium-copper samples for "tin pest" growth (alpha/beta transformation); and beta cloth backed with a black coating rather than aluminization. MISSE 8 samples are: exposed "scrim cloth" (fiberglass weave) from the ISS solar array wing material, protective fiberglass tapes and sleeve materials, and optical witness samples to monitor contamination.

Finckenor, Miria↗

MISSE in the Materials and Processes Technical Information System (MAPTIS )

Materials International Space Station Experiment (MISSE) data is now being collected and distributed through the Materials and Processes Technical Information System (MAPTIS) at Marshall Space Flight Center in Huntsville, Alabama. MISSE data has been instrumental in many programs and continues to be an important source of data for the space community. To facilitate great access to the MISSE data the International Space Station (ISS) program office and MAPTIS are working to gather this data into a central location. The MISSE database contains information about materials, samples, and flights along with pictures, pdfs, excel files, word documents, and other files types. Major capabilities of the system are: access control, browsing, searching, reports, and record comparison. The search capabilities will search within any searchable files so even if the desired meta-data has not been associated data can still be retrieved. Other functionality will continue to be added to the MISSE database as the Athena Platform is expanded

Burns, DeWitt↗

Atomic Oxygen Erosion Data from the MISSE 2-8 Missions

Polymers and other oxidizable materials on the exterior of spacecraft in the low Earth orbit (LEO) space environment can be eroded from reaction with atomic oxygen (AO). Therefore, in order to design durable spacecraft it is important to know the extent of erosion that will occur during a mission. This can be determined by knowing the LEO AO erosion yield, E(sub y) (volume loss per incident oxygen atom), of materials susceptible to AO reaction. In addition, recent flight experiments have shown that the AO E(sub y) can vary with the AO fluence and/or solar exposure. Therefore obtaining AO E(sub y) data for materials flown on various spaceflight missions is important. NASA Glenn Research Center has flown numerous experiments as part of the Materials International Space Station Experiment (MISSE) missions on the exterior of the International Space Station to characterize the LEO E(sub y) of polymers, composites, protective coatings, and other spacecraft materials. This report provides a summary of the erosion data for ram samples from six Glenn polymer experiments flown as part of MISSE 2, 4, 6, 7, and 8. A total of 71 types of materials with 111 E(sub y) values are provided. The E(sub y) values for uncoated polymers range from 3.81×10(exp –27) cu cm/atom for DC 93-500 silicone exposed to an AO fluence of 4.62×10(exp 21) atoms/sq cm on MISSE 8 to 9.14×10(exp –24) cu cm/atom for polyoxymethylene (POM) exposed to an AO fluence of 8.43×10(exp 21) atoms/sq cm on MISSE 2. One polymer, Triton oxygen resistant, low modulus (TOR(TM) LM), experienced mass gain when exposed to an AO fluence of 2.15×10(exp 21) atoms/sq cm on MISSE 4. In many cases the same material was flown on numerous missions so that trends for E(sub y) versus AO fluence and/or solar exposure can be determined, along with temperature effects.

Erosion↗

Ground Testing of the MISSE-16 Materials

The harsh space environment imposes very stringent requirements upon spacecraft materials, especially those located on exterior surfaces of space objects in low Earth orbit (LEO). As humankind moves from space exploration to space commercialization, these materials may have to last for 15–20 years without considerable degradation of their optical, electrical, mechanical, and thermal properties. Operational requirements dictate that these materials continue to function according to expectations. Hence, we must understand the effects of the space environment on materials currently in use as well as on untested materials. For the years, the Materials International Space Station Experiment Flight Facility (MISSE-FF) have flown many different materials to investigate the effect of LEO space weather exposure on the performance and durability of materials and devices. The MISSE-16 scientific team members plan to launch fifteen different novel and well-characterized spacecraft-relevant materials to the LEO environment for a duration of six months during the MISSE-16 mission. Changes in spectral reflectivity will be measured throughout the mission as the samples are exposed to the space environment. The same chemical damage the produces changes in optical reflectance also causes changes in numerous other physical properties such as electrical conductivity, mechanical strength, and chemical reactivity. Correlation of the changes in each of these properties as a function of radiation type, flux, and fluence allows various material properties to be inferred from one experimentally tractable measurement: color change. Flying identical test fixtures on the ram, zenith, and wake positions of the MISSE-FF, collecting spectrally resolved images of the materials, and concomitantly measuring the ambient space environment allows deconvolution of the material effects which occur as a result of exposure to neutral atomic oxygen (AO), unfiltered solar ultraviolet (UV) radiation, and electrons. The flight experiment will function as a ground truth reference for our team’s ongoing laboratory-based space weather-material interactions experiments. Comparison of the MISSE-16 data with extensive testing of “flight-duplicate” samples under simulated space weather conditions will enable development of chemical models for prediction of material degradation. This paper discusses preliminary results from the ground test campaign including measurements of UV/VIS/IR reflectance spectra, bidirectional reflectance distribution function (BRDF), surface potential decay, and surface morphology under electron and AO exposure.

Elena A. Plis↗

Salvaging Data Records with Missing Data: Data Imputation using the Multivariate t Distribution

When doing multivariate data analysis, one commonobstacle is the presence of incomplete observations, i.e., observationsfor which one or more key fields are blank. Missing datais often countered by deleting entire observations that containmissing data. The negative effects of deleting entire observationsare multiple: deleting observations reduces sample size andcan also result in biased inferences even if data is missing atrandom. In addition, knowledge contained within incompleteobservations is knowledge lost when they are deleted– and theeffort spent collecting that knowledge is effort wasted. Data imputationmethods, or methods of statistically “filling-in” missingdata, can help combat small sample sizes by using the existinginformation in partially complete observations with the end goalof producing less biased and higher confidence inferences. Whena sample from a multivariate normal population is only partiallycomplete, and the missing data meets appropriate assumptions(missing at random), robust data imputation of the missing datacan be implemented with monotone data augmentation (MDA)using the multivariate t distribution.Missing data imputation is applied to data from the NASA InstrumentCost Model (NICM) using the MDA algorithm underthe assumption of having a multivariate t distribution with fixeddegrees of freedom. A sensitivity analysis to the degrees offreedom parameter is presented to demonstrate robustness ofthe multivariate t distribution when dealing with small samplesas compared to the multivariate normal distribution.

DiNicola, Michael↗

Designing Trajectories Resilient to Missed Thrust Events Using Expected Thrust Fraction

With the adoption of efficient low-thrust propulsion methods, the probability of a missed thrust event occurring has become a significant concern for short and long- duration missions. If the missed thrust events take place during a critical portion of the trajectory, the mission can be compromised. Therefore, it is essential to de- velop trajectories that are resilient to missed thrust events. This paper investigates the use of expected thrust fraction, which embeds the stochastic nature of missed thrust events into a deterministic optimal control problem. The performance of trajectories designed using expected thrust fraction is compared with traditionally designed trajectories to measure changes in resiliency to missed thrust events. In this investigation, trajectories designed using expected thrust fraction arrive with a median lateness half that of traditionally designed trajectories. Using expected thrust fraction can help astrodynamicists mitigate risks posed by the use of low- thrust propulsion.

Laipert, Frank E.↗

Clustering with Missing Values: No Imputation Required

Clustering algorithms can identify groups in large data sets, such as star catalogs and hyperspectral images. In general, clustering methods cannot analyze items that have missing data values. Common solutions either fill in the missing values (imputation) or ignore the missing data (marginalization). Imputed values are treated as just as reliable as the truly observed data, but they are only as good as the assumptions used to create them. In contrast, we present a method for encoding partially observed features as a set of supplemental soft constraints and introduce the KSC algorithm, which incorporates constraints into the clustering process. In experiments on artificial data and data from the Sloan Digital Sky Survey, we show that soft constraints are an effective way to enable clustering with missing values.

constraints↗

Automating MISSE Specimens Image Analysis

The Materials International Space Station Experiment (MISSE) Project consists of experiments focused on the investigation of the effects that occur through the exposure of materials specimens in the space environment. To determine if there is a change in a specimen, the data obtained from the MISSE high-resolution photographic images can be monitored. For this, a compilation of folders was created to provide an organizational system. Each mission was divided into the specific direction in space, materials specimen, and date the image was taken. This organization helps to identify how a specimen behaves as a function of time in the space environment. Once the images were classified, a qualitative process was first used to detect an evolution in the materials of MISSE-9 - MISSE-14.

MISSE ISS Materials↗

The effects of missing data on global ozone estimates

The effects of missing data and model truncation on estimates of the global mean, zonal distribution, and global distribution of ozone are considered. It is shown that missing data can introduce biased estimates with errors that are not accounted for in the accuracy calculations of empirical modeling techniques. Data-fill techniques are introduced and used for evaluating error bounds and constraining the estimate in areas of sparse and missing data. It is found that the accuracy of the global mean estimate is more dependent on data distribution than model size. Zonal features can be accurately described by 7th order models over regions of adequate data distribution. Data variance accounted for by higher order models appears to represent climatological features of columnar ozone rather than pure error. Data-fill techniques can prevent artificial feature generation in regions of sparse or missing data without degrading high order estimates over dense data regions.

Drewry, J. W.↗

Restoration of HST images with missing data

Missing data are a fairly common problem when restoring Hubble Space Telescope observations of extended sources. On Wide Field and Planetary Camera images cosmic ray hits and CCD hot spots are the prevalent causes of data losses, whereas on Faint Object Camera images data are lossed due to reseaux marks, blemishes, areas of saturation and the omnipresent frame edges. This contribution discusses a technique for 'filling in' missing data by statistical inference using information from the surrounding pixels. The major gain consists in minimizing adverse spill-over effects to the restoration in areas neighboring those where data are missing. When the mask delineating the support of 'missing data' is made dynamic, cosmic ray hits, etc. can be detected on the fly during restoration.

Adorf, Hans-Martin↗

Minimizing Cache Misses Using Minimum-Surface Bodies

A number of known techniques for improving cache performance in scientific computations involve the reordering of the iteration space. Some of these reorderings can be considered as coverings of the iteration space with the sets having good surface-to-volume ratio. Use of such sets reduces the number of cache misses in computations of local operators having the iteration space as a domain. First, we derive lower bounds which any algorithm must suffer while computing a local operator on a grid. Then we explore coverings of iteration spaces represented by structured and unstructured grids which allow us to approach these lower bounds. For structured grids we introduce a covering by successive minima tiles of the interference lattice of the grid. We show that the covering has low surface-to-volume ratio and present a computer experiment showing actual reduction of the cache misses achieved by using these tiles. For planar unstructured grids we show existence of a covering which reduces the number of cache misses to the level of structured grids. On the other hand, we present a triangulation of a 3-dimensional cube such that any local operator on the corresponding grid has significantly larger number of cache misses than a similar operator on a structured grid.

Frumkin, Michael↗