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Comparison of Remote Sensing and Fixed-Site Monitoring Approaches for Examining Air Pollution and Health in a National Study Population

Satellite remote sensing (RS) has emerged as a cutting edge approach for estimating ground level ambient air pollution. Previous studies have reported a high correlation between ground level PM2.5 and NO2 estimated by RS and measurements collected at regulatory monitoring sites. The current study examined associations between air pollution and adverse respiratory and allergic health outcomes using multi-year averages of NO2 and PM2.5 from RS and from regulatory monitoring. RS estimates were derived using satellite measurements from OMI, MODIS, and MISR instruments. Regulatory monitoring data were obtained from Canada's National Air Pollution Surveillance Network. Self-reported prevalence of doctor-diagnosed asthma, current asthma, allergies, and chronic bronchitis were obtained from the Canadian Community Health Survey (a national sample of individuals 12 years of age and older). Multi-year ambient pollutant averages were assigned to each study participant based on their six digit postal code at the time of health survey, and were used as a marker for long-term exposure to air pollution. RS derived estimates of NO2 and PM2.5 were associated with 6e10% increases in respiratory and allergic health outcomes per interquartile range (3.97 mg m3 for PM2.5 and 1.03 ppb for NO2) among adults (aged 20e64) in the national study population. Risk estimates for air pollution and respiratory/ allergic health outcomes based on RS were similar to risk estimates based on regulatory monitoring for areas where regulatory monitoring data were available (within 40 km of a regulatory monitoring station). RS derived estimates of air pollution were also associated with adverse health outcomes among participants residing outside the catchment area of the regulatory monitoring network (p < 0.05).

validation↗

Converter Compressor Building, SWMU 089, Hot Spot Areas 1, 2, and 5 Operations, Maintenance, and Monitoring Report, Kennedy Space Center, Florida

This Operations, Maintenance, and Monitoring Report (OMMR) presents the findings, observations, and results from operation of the air sparging (AS) interim measure (IM) for Hot Spot (HS) Areas 1, 2, and 5 at the Converter Compressor Building (CCB) located at Kennedy Space Center (KSC), Florida. The objective of the IM at CCB HS Areas 1, 2, and 5 is to decrease concentrations of volatile organic compounds (VOCs) in groundwater in the treatment zones via AS to levels that will enable a transition to a monitored natural attenuation (MNA) phase. This OMMR presents system operations and maintenance (O&M) information and performance monitoring results since full-scale O&M began in June 2014 (2 months after initial system startup in April 2014), including quarterly performance monitoring events in July and October 2014 and January and May 2015. Based on the results to date, the AS system is operating as designed and is meeting the performance criteria and IM objective. The performance monitoring network is adequately constructed for assessment of IM performance at CCB HS Areas 1, 2, and 5. At the March 2014 KSC Remediation Team (KSCRT) Meeting, team consensus was reached for the design prepared for expansion of the system to treat the HS 4 area, and at the November 2014 KSCRT Meeting, team consensus was reached that HS 3 was adequately delineated horizontally and vertically and for selection of AS for the remedial approach for HS 3. At the July 2015 KSCRT meeting, team consensus was reached to continue IM operations in all zones until HSs 3 and 4 is operational, once HS 3 and 4 zones are operational discontinue operations in HS 1, 2, and 5 zones where concentrations are less than GCTLs to observe whether rebounding conditions occur. Team consensus was also reached to continue quarterly performance monitoring to determine whether operational zones achieve GCTLs and to continue annual IGWM of CCB-MW0012, CCBMW0013, and CCB-MW0056, located south of the treatment area. The next performance monitoring event is scheduled for July 2015.

Converter Compressor Building↗

The Swift-BAT Hard X-Ray Transient Monitor

The Swift/Burst Alert Telescope (BAT) hard X-ray transient monitor provides near real-time coverage of the X-ray sky in the energy range 15-50 keV. The BAT observes 88% of the sky each day with a detection sensitivity of 5.3 mCrab for a full-day observation and a time resolution as fine as 64 s. The three main purposes of the monitor are (1) the discovery of new transient X-ray sources, (2) the detection of outbursts or other changes in the flux of known X-ray sources, and (3) the generation of light curves of more than 900 sources spanning over eight years. The primary interface for the BAT transient monitor is a public Web site. Between 2005 February 12 and 2013 April 30, 245 sources have been detected in the monitor, 146 of them persistent and 99 detected only in outburst. Among these sources, 17 were previously unknown and were discovered in the transient monitor. In this paper, we discuss the methodology and the data processing and filtering for the BAT transient monitor and review its sensitivity and exposure.We provide a summary of the source detections and classify them according to the variability of their light curves. Finally, we review all new BAT monitor discoveries. For the new sources that are previously unpublished, we present basic data analysis and interpretations.

black hole physics↗

Recommendations for Using Noise Monitors to Estimate Noise Exposure During X-59 Community Tests

A low fidelity simulation approach is used to explore how to place and use noise monitors during X-59 QueSST community tests, where people’s annoyance to the noise produced by the X-59 aircraft will be gathered. Several recommendations are provided including: 1) the desired number of sparsely spaced noise monitor sites within the survey area, 2) whether to group and average measurements across multiple noise monitors located at a site, 3) what spacing should be used if grouped noise monitors are used, 4) an approach to mitigate ambient noise contamination at the measurement sites, 5) a method to combine empirical and predicted dose estimates to provide a single dose estimate for respondents, and 6) assessing how changes in turbulence intensity and array configuration affect dose uncertainty. To make these recommendations, the error that is expected when fitting contrived, smoothly varying sonic boom “reference exposure surfaces” is studied when a spatially sparse and scattered set of samples is used as responses for the fit. The reference exposure surfaces mimic the sonic boom exposure at ground level that might be expected in the X-59 survey area in the absence of atmospheric turbulence, ambient noise, and other localized effects. The spatial extent of these surfaces varies and is representative of the different survey area sizes that might be expected during future X-59 community overflight tests. These contrived reference surfaces are sampled, and those reference samples are then perturbed to mimic atmospheric turbulence, ambient noise and other localized effects that might affect noise monitor measurements within overflown communities. Two different surface fitting methods are investigated when fitting these perturbed samples to approximate the reference surface. The first method uses interpolation between the perturbed data at the scattered sites to compute the fit. The second method fits a polynomial surface model to the perturbed data using ordinary least squares regression analysis. For both fitting methods, the root mean square fit error is computed from the pointwise difference between the fit surface and the reference surface as the count and configuration of the sites is varied while also averaging the error across many different realizations of both the smooth variation of the reference exposure surface and the random, localized perturbations at the sample sites. Different site configurations are compared using this error statistic to make the recommendations noted above. Additionally, the two fitting approaches (interpolation vs linear regression) are compared based on the fit error observed in these simulations. These analyses, comparisons, and recommendations should inform future decisions on the noise monitor placement and the methods used to analyze the noise monitor data that is collected during X-59 community overflights.

sonic boom↗

Microbial Monitoring of New Cleanrooms Used to Curate Astrobiologically Relevant Asteroid Samples from Bennu and Ryugu

Introduction: NASA has constructed two new cleanrooms to house materials from the OSRIS-REx and Hayabusa2 missions to the asteroids Ryugu (162173) and Bennu (101955), respectively. In accordance with standard astromaterials curation practices, these cleanrooms will be monitored for particulate contamination and maintained to ISO 5 equivalent standards1. Since the samples in these collections are expected to contain prebiotic organic compounds that may help explain the origin of life on Earth, these labs will also be monitored for organic and biological contamination2. Samples from Ryugu arrived on Earth in December, 2020. After basic characterization in Japan, NASA received a subset of these samples at the astromaterials curation facility in Houston in December of 2021. OSIRIS-REx is expected to return samples in September, 2023. Here we present preliminary microbial monitoring results from monthly monitoring of these new labs and the connected microtomy and staging areas that support them, as they are being commissioned. We also compare these results to baseline values for other astromaterials curation labs. We will also briefly describe additional cleaning efforts employed to reduce the bioburden in these new cleanrooms. Methods: Microbial samples were collected from surfaces using a dry macrofoam swab (Puritan Brand 2518051PFRNDFD). Swabs were also opened in the lab but not touched to any surfaces to function as negative controls. Samples and controls were processed inside a class II biosafety cabinet to avoid inadvertent cross contamination. The swabs were suspended in 15 ml of PBS (Phosphate Buffered Saline) and vortexed for 20 seconds to remove cells from the swab surface. The PBS was used to inoculate Petri dishes filled with TSA (Tryptic Soy Agar), Blood Agar, or Reasoners 2 agar to check for microbial growth. Each plate was inoculated with 0.1 ml of PBS. The TSA and blood agar plates were incubated at 35˚C and the Reasoners 2 agar plates were incubated at 25˚C for seven days. Petri dishes filled with Potato dextrose agar, Saboraud dextrose agar, or Saboraud dextrose agar with 0.1 mg/ml of chloramphenicol, an antibiotic, were used to check for fungal growth. These plates were inoculated with 0.3 ml of PBS and incubated at 30˚C. The remaining PBS was frozen at -80 ˚C for DNA sequencing. After incubation, isolates were counted and reisolated for identification. Isolates were identified using the VITEK23 system or by sequencing a portion of the 16S rRNA gene for bacteria or the ribosomal internal transcribed spacer (ITS) for fungi. Sequencing was performed with an ABI 3500 Sanger sequencer. Results: During our initial sampling, six of the seven sites sampled (86%) displayed bacterial or fungal growth. Samples collected from the staging areas and microtomy labs are not included in this calculation since those areas are maintained at a lower ISO 7 equivalent cleanliness standard. A month later, only three of the seven sites (43%) displayed bacterial growth. No fungal growth was detected in the second sampling. Since new equipment had been introduced to the Hayabusa2 lab since the first round of sampling, an additional three sampling sites were included in the second round of sampling. None of these sites displayed microbial growth. These sites will be included in all future sampling efforts. Bacterial isolates have been identified from the following genera at multiple time points: Micrococcus, Staphylococcus, and Bacillus. Isolates from the genera: Microbacterium, Nocardioides, Methylocystis, and Microvirga were identified in the initial sampling, but were not present at later time points. Identification of fungal isolates is in progress. Results are summarized in Table 1. Discussion: The recovery rate or percentage of positive samples4 was initially 86%, which is higher than the median recovery rate for comparable ISO 5 equivalent curation labs like Stardust (33%), Hayabusa (33%), and Cosmic Dust (50%). However, after a month of operation, the recovery rate for these same sites decreased to 43%, which is similar to what we observe in comparable curation cleanrooms with no microbial control requirements. Adding in the new sampling sites further decreases the recovery rate to 30%. With the reduction in recovery rate, we also observed a decrease in microbial diversity. At the first time point, we observed at least 10 different bacterial species and at least two different fungi. This is a higher diversity than the median values for comparable ISO 5 equivalent labs (2-4 isolates per sampling event). After the second sampling, we observed at least 4 bacterial species and no fungi, which is more consistent with comparable labs. We expect the recovery rate and diversity in both labs to continue to decrease as routine operation continues. We will use ultrapure hydrogen peroxide to disinfect equipment and work areas prior to opening any sample containers. Most of the bacterial and fungal isolates were detected on samples from the cleanroom floors. This is consistent with baseline results from other curation labs. Organisms from the genera Bacillus, Staphylococcus, and Micrococcus that were repeatedly detected are common in cleanrooms and on human skin5,6. These organisms are generally thought to be introduced when people enter the cleanroom. Microbacterium, Nocardioides, and Microvirga have also previously been identified in astromaterials cleanrooms, but not as frequently as Bacillus, Staphylococcus, and Micrococcus. Methylocystis is a novel genus in the astromaterials cleanrooms, but it was identified with low accuracy (93% match in the sequenced region of the 16S rRNA gene) and further work is needed to confirm this identification. Microbacterium is a diverse genus with isolates identified from terrestrial and aquatic sediments. Some species of Microbacterium are capable of degrading complex organic compounds found in crude oil. The presence of these bacteria in the OSIRIS REx and Hayabusa2 cleanrooms should be closely monitored. Methylocystis is a genus of methanotrophic bacteria capable of oxidizing methane. If this identification proves to be correct and it is detected again, it should be closely monitored as well. Under nominal operating conditions, samples should not ever encounter the cleanroom floor or other high traffic areas. If we observe an increase in the bioburden in sensitive work areas that appears to be influenced by organism transfer from high traffic areas like the floors, we can employ additional hydrogen peroxide treatments to disinfect high traffic areas. Routine microbial monitoring of these labs will ensure that NASA’s astromaterials collections remain pristine and useful for scientific study. Table 1. Sampling Locations and Colony Counts Bacterial CFUa Fungal CFU Bacterial CFU Fungal CFU Lab - Location 11/2/2021 11/2/2021 12/13/2021 12/13/2021 H2b-Floor 4 8 1 0 H2-staging pass through 3 0 0 0 H2-microtomy pass through TNTCc 0 0 0 H2 Microscope 1 NA NA 0 0 H2 Microscope 2 NA NA 0 0 H2-Table NA NA 0 0 OREXd- microtomy pass through 0 0 6 0 OREX – Anteroom pass through 0 0 0 0 OREX – Floor 1 2 0 0 OREX Witness Foil Table 3 0 1 0 Staging-Floor 16 0 15 0 Microtomy-Floor 3 0 2 0 a: CFU = Colony Forming Unit b: H2 = Hayabusa2 Lab c: TNTC = too numerous to count d: OREX = OSIRIS-REx Lab References: 1. ISO 14644-1:2015 - Cleanrooms and associated controlled environments -- Part 1: Classification of air cleanliness by particle concentration. 37 (2015). 2. McCubbin, F. M. et al. Space Sci Rev 215, (2019). 3. Pincus, D. H. Encyclopedia of Rapid Microbiological Methods (2005). 4. The United States Pharmacopeial Convention. USP General Chapter <1116> 17, 784–794 (2013). 5. Sheraba, N. S., Yassin, A. S. & Amin, M. BMC Research Notes 3, 278 (2010). 6. Utescher, C. L. de A., Franzolin, M. R., Trabulsi, L. R. & Gambale, V. Brazilian Journal of Microbiology 38, 710–716 (2007).

A B Regberg↗

Insights From Routine Microbiological Monitoring of Air in Astromaterials Curation Cleanrooms

NASA maintains nine separate cleanrooms at the Johnson Space Center to curate and preserve astromaterials samples. Routine microbial monitoring of the surfaces in these cleanrooms began in 20181. Until recently, materials compatibility requirements prevented monitoring airborne biological particles in all but one of these cleanrooms. New astromaterials collections from carbon rich asteroids are more susceptible to biological degradation than previous collections. Therefore, it is important to monitor the bioburden in the air and on surfaces in these labs. Establishing a comprehensive microbial monitoring program will help inform the monitoring and curation plans for Mars sample return which will include samples that are extremely biologically sensitive. In April of 2022 we began routinely collecting air samples in seven of the nine curation cleanrooms (Meteorite ISO 7 equivalent, Lunar ISO 6 equivalent, Stardust, Hayabusa2, OSIRIS-REx ISO 5 equivalent, and Genesis ISO 4 equivalent) using a sampling device that collects airborne biological particles on an electret filter instead conventional sampler that collect cells in a liquid media or onto organic rich Petri dishes. Electret is a generic term for electrostatically charged media. The charge on these materials increases particle trapping when compared to non-charged filters of similar thickness. N95 respirators also use electret filters. This dry sample collection method allows us to meet materials requirements for all the curation labs and reduces the risk of inadvertently introducing contamination as part of our monitoring effort. This method also allows us to preserve a portion of each sample for DNA extraction and next generation sequencing. DNA sequencing helps us to characterize the portion of the cleanroom microbiome that we cannot culture. We will present the results of our first 8 months of monitoring, compare these results to particle counts in the labs and to measurements made directly onto Petri dishes when possible. We will also make recommendations for modifications to the sampling method to improve sampling efficiency and preserve diversity.

A. B. Regberg↗

Components Refurbishment and Chemical Analysis Facility, Hot Spot 1 Solid Waste Management Unit #041 Year 4 Annual Performance Monitoring Report Kennedy Space Center, Florida

This Year 4 Annual Performance Monitoring Report (PMR) presents the operations, maintenance, and monitoring activities for the Hydraulic Containment System (HCS) Interim Measure (IM) at the Components Refurbishment and Chemical Analysis (CRCA) facility located at John F. Kennedy Space Center (KSC), Florida. The primary objective of the HCS is to attain hydraulic control of the dissolved-phase chlorinated volatile organic compound (CVOC) plume, with the secondary objective to reduce concentrations of CVOCs in the high-concentration plume to support transition to monitored natural attenuation (MNA). CRCA has been designated Solid Waste Management Unit 041 under the KSC Resource Conservation and Recovery Act Corrective Action Program. The timeframe for activities documented in this Year 4 PMR extends from November 2022 through September 2023. Baseline sampling activities were completed in June 2019, and full-scale startup of the HCS IM was completed in July-August 2019. The operational runtime of the HCS for the Year 4 reporting period was approximately 94%, with the majority of downtime attributed to associated groundwater sampling events, maintenance, and Hurricane Nicole. Almost five million gallons of groundwater were treated during Year 4 of HCS operations, and concentrations of the site’s contaminants of concern (trans-1,2-dichloroethene and vinyl chloride) have been reduced by over 99%. This PMR describes the activities that were performed during Year 4 to operate and monitor the HCS IM, which includes three extraction wells, seven injection wells, and conveyance piping to a modular structure containing the control panel and an air stripper. Influent and effluent sampling results from the air stripper show that the system is operating as designed and is reducing concentrations of contaminants of concern to below detection limits. In addition to HCS operation, this PMR also discusses performance monitoring that has been implemented to assess progress of the HCS IM and overall plume conditions through scheduled groundwater (quarterly and semi-annual) and sub-slab soil gas (quarterly) sampling and analysis. Two ambient air samples were also collected on a quarterly basis in the vicinity of the modular structure and the paved driveway east of the Solvent Reclamation Area during routine operation and maintenance (O&M) activities to ensure safe breathing zone air quality for on-site personnel. All sub-slab soil gas and ambient air sampling conducted during the Year 4 operational period showed results below applicable regulatory air screening limits. Predictions made during the Year 2 groundwater model updates were in close correlation to post Year 4 plume conditions. A supplemental DPT study conducted in 2022 and 2023. This study indicated that low-concentration plume conditions, where concentrations exceed State of Florida Groundwater Cleanup Target Levels, expanded westward to Kennedy Parkway North and northward to the vicinity of the railroad tracks. Based on these results, recommendations were made to install 14 wells to monitor the downgradient and boundary conditions of the expanded LCP. The contents of this Year 4 PMR were presented during the November 2023 KSC Remediation Team meeting, where Team consensus was reached on several items including continued O&M of the HCS, and continued monitoring of groundwater, ambient air, and sub-slab soil gas. Sampling for per- and polyfluoroalkyl substances at CRCA is ongoing and will be submitted under separate cover.

K. Alex Murphy↗

Launch Complex 39A, SWMU 008 2023 Long-Term Monitoring Report Kennedy Space Center, Florida

The 2023 Long-Term Monitoring (LTM) Report (LTMR) presents the annual and semi-annual groundwater monitoring results for Launch Complex 39A (LC39A), Solid Waste Management Unit (SWMU) 008, at Kennedy Space Center (KSC), Florida. The reporting period covered under this LTMR is from January to December 2023, and represents the first year of site-wide monitoring following Air Sparge (AS) system shutdown at the end of 2022. AS system operation at LC39A began operation in 2015. The AS system consisted of a total of 173 AS wells ranging in depth from 11 to 37 feet below land surface. The overall remedial objective for the AS Interim Measure was to actively decrease concentrations of COCs to less than their respective Florida Department of Environmental Protection Natural Attenuation Default Concentrations, so that LC39A can transition into an LTM program. This objective was achieved in 2022, with 2023 marking Year 1 of the LTM program to monitor the residual groundwater plume. VOC results indicate that COC concentrations have continued to decrease or stabilize, with no rebound observed since AS system shutdown. Vinyl chloride was the only COC detected above its GCTL, with the highest concentration detected at 8.0 μg/L. PFAS results detected 15 different PFAS compounds (out of 32 analyzed) between the six monitoring wells sampled. Two PFAS compounds, perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA), currently have FDEP Provisional GCTLs of 70 nanograms per liter (ng/L). PFOS was detected in one of the six samples above the FDEP Provisional GCTL at a concentration of 200 ng/L. PFOA was not detected above the FDEP Provisional GCTL in any of the six samples. PFOS and PFOA also currently have United States Environmental Protection Agency (USEPA) Maximum Contaminant Levels (MCLs) of 4 ng/L. PFOS was detected in all six samples above the USEPA MCL. PFOA was detected in three of the six samples above the USEPA MCL. Three other PFAS compounds, perfluorohexanesulfonic acid (PFHxS), perfluoro-n-nonanoic acid (PFNA), and hexafluoropropylene oxide dimer acid (GenX), currently have USEPA MCLs of 10 ng/L. PFHxS, PFNA, and GenX were not detected at concentrations greater than their respective USEPA MCLs in any of the six wells. Additional PFAS sampling will occur as part of a PFAS Site Assessment to be conducted in the future. Based on Year 1 LC39A LTM results, recommendations for 2024 are to continue with the second year of LTM in 2024 with the same monitoring well network as Year 1 (18 wells). The three wells that were on a semi-annual schedule will transition to an annual schedule to align with the remaining wells. The next annual event is scheduled for May 2024. The three wells that were found to be inadvertently destroyed will be properly abandoned and a replacement well in the vicinity of former monitoring well 21ST-MW0030I will be installed. This new well will be added to the LTM sampling plan upon installation.

Deborah M. Wilson↗

Monitoring for neuroprotection. New technologies for the new millennium

Monitoring for neuroprotection, like surgery, has placed on emphasis on minimal or non-invasiveness. Monitoring of parameters that truly reflect the degree of injury to the nervous system is another goal. Thus, two themes for the coming decade in neuromonitoring will be: (1) less-invasive monitoring; and (2) parameters that more closely reflect the etiological factors in ischemic or other neuroinjury. In this paper, we review neuromonitoring techniques and devices that can be used readily in the operating room or intensive care unit setting. Those that require transport of the patient to a special facility (e.g., for computed tomography or magnetic resonance imaging/spectroscopy) and those that have been in standard practice for neuromonitoring (e.g., electrophysiological monitoring--EEG, evoked potentials) are not considered. The two techniques considered in detail are (1) continuous multiparameter local brain tissue monitoring with microprobes, and (2) non-invasive continuous local brain tissue oxygenation monitoring by near infrared spectroscopy. Both techniques have been cleared by the Food and Drug Administration (FDA) for clinical use. The rationale for their use, the nature of the devices, and clinical results to date are reviewed. It is expected that both techniques will gain wide acceptance during the coming decade; further advances in neuromonitoring that can be expected further into the twenty-first century are also discussed.

Review↗

Runtime Monitoring with R2U2 for Aircraft Systems with Neural Networks

R2U2 (Realizable, Responsive, Unobtrusive Unit) is a hardware-supported tool and framework for real-time system monitoring and software health management of cyber-physical systems. During system operation, R2U2 continuously monitors properties about safety, performance, and security of the vehicle and its vital components and can perform diagnostic reasoning. Efficient observers for past-time and future-time Metric Temporal Logic, fast reasoners for Bayesian Networks, and model-based prognostics algorithms are key components of R2U2 and designed for minimal computational footprint. R2U2 has been implemented in software supporting ROS, NASA's cFS/cFE, and Simulink and as an FPGA configuration. The synergistic combination of monitors and observers in R2U2 makes it possible to design powerful models for system runtime monitoring, diagnostics, software health management, prognostics, and security monitoring. In this presentation, I will give a detailed overview of the R2U2 architecture and its features and will discuss the application of R2U2 for safety-monitoring of a neural-network based autonomous centerline tracking system (ACT) for autonomous aircraft.

Runtime Monitoring↗

The Effects of Training and Flight Director Use on Pilot Monitoring Performance: A Sensemaking Approach

The need for improved pilot monitoring and awareness has been widely recognized, and training is a possible intervention. Based on our sensemaking-model of monitoring, we identified key properties of monitoring flight path. We designed scenarios with associated behavioral markers that provide measures of monitoring performance and a short training module emphasizing our proactive, anticipatory view of monitoring. Nineteen first officers from a major US airline participated in the training study. Each pilot flew in a simulator pretest, participated in a training session, and flew in a simulator posttest. We found modest but significant improvements in monitoring. The study collected video, simulator, and eyetracking data and also manipulated whether the Flight Director was on or off. Limitations and future directions are discussed.

monitoring↗

Cognitive Engineering in Training: Monitoring and Pilot-Automation Coordination in Complex Environments

This paper reports our investigation of flight path monitoring in aviation. We interviewed experienced pilots to understand the knowledge and skills underlying effective monitoring and we developed an example learning environment to improve these skills. We explore how design of pilot training and learning, like the design of interfaces and of the underlying automation, benefits from cognitive engineering methods and perspective. In aviation, monitoring and managing flight path are critical activities. The influences on flight path are complex and come from the autoflight system, from control actions by the pilot, and from external factors, including weather and Air Traffic Control (ATC). Indeed, inadequate flight path monitoring is a current aviation concern as it has been implicated in accidents and incidents. Effective piloting depends on strategies for noticing, understanding, and anticipating these influences to monitor and manage flight path. Lack of such skills reduces pilots' ability to maintain safety margin and resilience. Although flightdeck automation is intended to aid pilot understanding and prediction, the Fight Management Systems (FMS) can mislead as well as aid the pilot's understanding and projection of what will happen. In dynamic conditions, FMS predictions may be based on old or incomplete information. Understanding such vulnerabilities is an important part of pilot-autoflight coordination. The learning environment we developed is designed to help pilots proactively monitor and manage flight path. We consider how a broad cognitive engineering approach might inform the "what" and "how" of learning in dynamic work domains.

pilot-monitoring↗

Powder Bed Fusion Laser Beam Metals Additive Manufacturing: Process Monitoring Approaches for Qualification and Certification

The use of in-situ process monitoring is of interest to lower the cost of inspection for the qualification of powder bed fusion laser beam metal (PBF-LB/M) additively manufactured (AM) parts. Precise monitoring of the PBF-LB/M AM build process constitutes a multi-scale and multi-discipline task. There are several significant challenges to the in-situ approach: the synchronization of sensor signals to process steps; the physical interpretation and classification of sensor signals; managing very large datasets; and comparing the inputs with the observed monitoring signals. At NASA Langley Research Center, a configurable architecture additive testbed has been developed to monitor the build process with synchronized sensors. The philosophy and method adopted for the synchronization of the cameras with laser power and position throughout a complex PBF-LB/M AM build will be described. The synchronized in-situ monitoring signals are compared with ex-situ nondestructive inspection, x-ray computed tomography (XCT). Such comparisons permit a better understanding of how the sequential process actions of LPBF-AM can affect build quality. The multi-scale and complex process of printing additively manufactured (AM) parts can have unexpected, but predictable, build conditions that result in material microstructure variability. This presentation will describe an additive manufacturing model-based process metric (AM-PM) computational method that is a fully parallel reduced order modeling approach developed to evaluate the evolution of AM processes. This method couples the known sequence of the AM process with a physically informed nearest neighbors’ calculation to map the conditions of a part-scale build. The result is a map of the build that is derived directly from build files or in-situ process monitoring sensors. The methodology of the approach will be described and mapped to the porosity observed from XCT for a complex PBF-LB/M build. Such comparative results develop understanding of how the sequential process actions can affect the PBF-LB/M AM build quality and microstructure variability.

Laser Powder Bed Fusion↗

Seeing is Believing: Monitoring Future Time Temporal Logic

Runtime monitors for future-time unbounded temporal logics like RVLTL, LTL 3 and FLTL, have double-exponential (2^2^n) worst-case space complexity bounds in size of the input formula. The semantics of these logics require monitors to perform general satisfiability solving for LTL expressions, a well-studied problem whose computational complexity is NP-hard and PSPACE-complete. This paper introduces an unbounded future-time linear temporal logic defined over a lattice. We call our logic an incremental temporal logic as it can be viewed as incrementally constructing proofs about the trace. On this account, we view online runtime monitoring as a decision procedure for proofs systems about incrementally growing traces. We demonstrate that our incremental temporal logic allows monitor construction to void satisfiability solving while still soundly detecting when the property is violated in an online fashion. This enables asymptotic improvements in space complexity. As proof, we provide a procedure to construct monitors that utilize linear space and time in the size of the input formula, while remaining constant in the size of the input stream and suitable for online monitoring. We further demonstrate, through several examples, that our incremental temporal logic is straightforward to adopt and practical for runtime verification.

temporal logic↗

Feasibility of wake vortex monitoring systems for air terminals

Wake vortex monitoring systems, especially those using laser Doppler sensors, were investigated. The initial phases of the effort involved talking with potential users (air traffic controllers, pilots, etc.) of a wake vortex monitoring system to determine system requirements from the user's viewpoint. These discussions involved the volumes of airspace to be monitored for vortices, and potential methods of using the monitored vortex data once the data are available. A subsequent task led to determining a suitable mathematical model of the vortex phenomena and developing a mathematical model of the laser Doppler sensor for monitoring the vortex flow field. The mathematical models were used in combination to help evaluate the capability of laser Doppler instrumentation in monitoring vortex flow fields both in the near vicinity of the sensor (within 1 kilometer and at long ranges(10 kilometers).

Wilson, D. J.↗

Processing inferences derived from event-related potential measures in a monitoring task

Event-related potentials (ERPs) were recorded from the scalp of subjects as they monitored changing digital readouts for values that went 'out-of-bounds'. Workload was manipulated by varying the number of readouts that were monitored concurrently. The ERPs elicited by changes in the readouts showed long latency positivities that increased in amplitude, not only with the number of readouts monitored, but also with the number of monitored readouts that were 'in danger' of going out-of-bounds. No effects were found due to the number of nonmonitored readouts 'in danger'. This evidence indicates that subjects (1) selectively attended to the monitored readouts and (2) processed the monitored readouts differently as the readouts approached the out-of-bounds levels to which an overt response was required.

Horst, R. L.↗

Surface contamination monitoring by the measurement of scattering distribution functions

This paper describes the use of Bidirectional Scattering Distribution Functions (BSDF) to quantify surface degradation, thus providing an effective method for contamination monitoring. This approach to contamination monitoring is based on the use of witness surfaces (mirrors or glass slides) located next to the critical surfaces. Contaminant accretion can be monitored during all phases of spacecraft fabrication, assembly, and testing. The method can be applied in other areas of contamination control such as monitoring of clean room environments. The BSDF can also prove extremely useful in establishing contamination control requirements and acceptability criteria. This paper describes the apparatus adopted to perform BSDF measurements and discusses some practical aspects of data collection. The results obtained in contamination monitoring programs performed at the NASA Goddard Space Flight Center are presented. Some possible new applications of this monitoring technique are also addressed.

Carosso, Paola A.↗

GPS integrity monitoring and multipath error distributions

The ability to perform integrity monitoring of a differential Global Positioning System (DGPS) precision approach system is dependent upon the form of monitor used and the various noise sources acting on the reference station, the monitor, and the approaching aircraft. This paper focuses on how multipath and assumptions about its probability density function (pdf) affect the availability of the integrity monitoring function. Also discussed is a technique specified as code/carrier integrity monitoring which can be used to greatly improve integrity monitoring availability over methods employing conventional C/A-code operations.

Skidmore, Trent A.↗