Results for “fence” — Page 18

NASA NTRS2017

Safely Enabling UAS Operations in Low-Altitude Airspace

NASA is developing a system to safely enable low altitude unmanned aerial system (UAS) operations. The system is referred to as UAS Traffic Management (UTM). The UTM will safely enable a variety of business models and multiple operations in the same airspace. The UTM will provide services such as airspace configuration and geo-fencing, weather and wind integration, demand-capacity imbalance management, and separation management, and contingency management. The UTM research and development has been conducted in collaboration with many in industry, academia, and government. The UTM system will evolve through four builds. Each build will be collaboratively tested with partners. The final prototype will be available for persistent daily use of UAS operations beyond line of sight.

low-altitude airspace↗

NASA NTRS2017

Safely Enabling UAS Operations in Low-Altitude Airspace

NASA is developing a system to safely enable low altitude unmanned aerial system (UAS) operations. The system is referred to as UAS Traffic Management (UTM). The UTM will safely enable a variety of business models and multiple operations in the same airspace. The UTM will provide services such as airspace configuration and geo-fencing, weather and wind integration, demand-capacity imbalance management, and separation management, and contingency management. The UTM research and development has been conducted in collaboration with many in industry, academia, and government. The UTM system will evolve through four builds. Each build will be collaboratively tested with partners. The final prototype will be available for persistent daily use of UAS operations beyond line of sight.

low-altitude airspace↗

NASA NTRS2019

NASA CA Operations Devolution: Status Update

What is Devolution? Devolution is a spreading of CA (Conjunction Assessment) operations responsibilities to mission FOTs (Flight Operations Teams): Permits efficiencies in handling the increased workload caused by Space Fence and large constellations; Missions given more flexibility in choosing specific approach to CA requirements that resonates best with their particular needs; CARA (Conjunction Assessment Risk Analysis) retains Agency oversight through an established NASA Standard - will establish requirements for devolved CA preparations, processing, and operations conduct. Devolution is a PROPOSED paradigm under consideration by SMD (Space Missions Directorate): Number of activities required before Agency-level decision can be rendered; Agency requirements established via approved CA Standard; Operational experience testimony from two separate pilot programs; After these activities complete, decision will be made whether devolution is a feasible option for missions; CARA is recommending devolution to exist as an option for missions.

conjunction↗

NASA NTRS2018

A Geofence Violation Prevention Mechanism for Small UAS

The ability to safely confine the trajectories of small UAS to a specific geographical area is a key enabler for capabilities that require operating in close proximity to populated areas as well as other users of the airspace. These capabilities require highly reliable geofencing algorithms. In particular, these algorithms must promptly alert imminent breaches of keep-in/keep-out geofences by considering factors such as the vehicle speed and uncertainties in the state of the aircraft. This paper presents a novel approach to the prevention of geofence boundary violation based on closure rate constraints. These constraints are incorporated into a control framework to effectively prevent fence breaches. Simulation results illustrating an example use case of this framework are presented.

Balachandran, Swee↗

NASA NTRS2018

Airborne Trajectory Management for Urban Air Mobility

Urban Air Mobility (UAM) has captured the imagination of the public and the aviation industry for someday soon moving people and goods through and around metropolitan areas using Unmanned Aircraft Systems (UAS) that are electrically powered, environmentally friendly, and autonomously operated. Significant investment and rapid development of vehicles for this activity is taking place, with package delivery services already beginning in some areas. However, the ability to manage thousands of these vehicles safely in a congested urban area presents a challenge unprecedented in air traffic management. Initial studies of this problem led by NASA under the UAS Traffic Management (UTM) initiative have primarily focused on geo-fencing and centralized reservation of airspace for individual flights. This paper proposes an extension of UTM using a de-centralized approach employing airborne surveillance, self-separation, and a minimized “design separation” approach to permit the optimization and safety of each flight in very high traffic densities and close proximities. The concept employs Airborne Trajectory Management (ABTM) principles and a novel new concept for variable separation criteria to manage the angular velocity of a passing vehicle, thus eliminating the "startle factor" and perceived hazard of very close operations. ABTM also accomplishes most of the services required for safe planning and execution of normal flights and recovery from abnormal or emergency operations while accommodating conventional piloted flights using the current air traffic control paradigm. The environment for UAM operations is described along with the proposed means for autonomous, tactical separation of the vehicles. Sample geometries of traffic conflicts and resolutions are shown and the airspace definitions, rules for flight within them, and additions and exemptions to the rules for these flights are listed and explained.

Cotton, William↗

NASA NTRS2019

Predicting Satellite Close Approaches Using Statistical Parameters in the Context of Artificial Intelligence

In order to ensure a sustainable use of low earth orbit in particular and near Earth space in general, reliable and effective close approach prediction be-tween space objects is key. Only this allows for efficient and timely colli-sion avoidance. Space Situational Awareness (SSA) for commercial and government missions will be facing the rapidly growing amount of small and potentially less agile satellites as well as debris in the near earth realm, such as the increase in CubeSat launches and upcoming large constellations. At the same time, space object detection capabilities are expected to increase significantly, allowing for the reliable detection of smaller objects, e.g. when the Air Force Space Fence radar becomes operational. In combination, the space object catalog is expected to increase tremendously in size. In this paper, we introduce an investigative approach based on the latest capabili-ties in artificial intelligence in fostering the potential for fast and accurate close approach predictions. We consider the study of statistical and infor-mation theory parameters in contrast and complementary to the classical probability of collision computation alone, in order to determine the feasi-bility of reliably predicting close approaches.

Mashiku, A.↗

NASA NTRS2019

Predicting Satellite Close Approaches Using Statistical Parameters in the Context of Artificial Intelligence

In order to ensure a sustainable use of low earth orbit in particular and near Earth space in general, reliable and effective close approach prediction be-tween space objects is key. Only this allows for efficient and timely colli-sion avoidance. Space Situational Awareness (SSA) for commercial and government missions will be facing the rapidly growing amount of small and potentially less agile satellites as well as debris in the near earth realm, such as the increase in CubeSat launches and upcoming large constellations. At the same time, space object detection capabilities are expected to increase significantly, allowing for the reliable detection of smaller objects, e.g. when the Air Force Space Fence radar becomes operational. In combination, the space object catalog is expected to increase tremendously in size. In this paper, we introduce an investigative approach based on the latest capabili-ties in artificial intelligence in fostering the potential for fast and accurate close approach predictions. We consider the study of statistical and infor-mation theory parameters in contrast and complementary to the classical probability of collision computation alone, in order to determine the feasi-bility of reliably predicting close approaches.

Mashiku, Alinda↗

NASA NTRS2019

Bounding Methods for Heterogeneous Lidar-derived Navigational Geofences

Safe Unmanned Aerial Vehicle (UAV) operations near the ground require navigation methods that avoid fixed obstacles such as buildings, power lines and trees. Aerial lidar surveys of ground structures are available with the precision and accuracy to geolocate obstacles, but the high volume of raw survey data can exceed the compute power of onboard processors and the rendering ability of ground-based flight planning maps. Representing ground structures with bounding polyhedra instead of point clouds greatly reduces the data size and can enable effective obstacle avoidance, as long as the bounding geometry envelopes the structures with high spatial fidelity. This report describes in detail four methods to compute bounding geometries of ground obstacles from lidar point clouds. The four methods are: 1) 2.5D Maximum Elevation Box, 2) 2.5D Ground Map Extrusion, 3) 3D Bounding Cylinder, and 4) 3D Bounding Box. The methods are applied to five point cloud datasets from lidar surveys of UAV flight research sites in Georgia and Virginia with an average point spacing that ranges from 0.1m to 0.6m. The methods are assessed using survey areas with geometrically heterogeneous ground structures: buildings, vegetation, power lines, and sub-meter structures such as road signs and guy wires. The 2.5D Maximum Elevation Box method is useful for simple structures. The 2.5D Ground Map Extrusion method efficiently encloses vegetation, but requires handdrawn ground footprints. The 3D Bounding Cylinder method excels at enclosing linear structures such as power lines and fences. The 3D Bounding Box method excels at enclosing planar structures such as buildings. The methods are compared on the basis of data compression and boundary fidelity on selected areas. The 2.5D methods yield the highest data compression but the polyhedra produced by them enclose significant amounts of empty space. Boundary fidelity is superior for the 3D methods, though this fidelity comes at the cost of a roughly thirtyfold lower data compression ratio than the 2.5D Maximum Elevation Box method. A mix of these output geometries is proposed for autonomous UAV navigation with limited on-board computing. Both the accuracy and spatial detail of emerging satellite-based survey technology lower than that of aerial lidar scanning survey technology. Sub-meter structures and thin linear structures are not reliably mapped at present by satellite-based surveys.

Moore, Andrew J.↗

NASA NTRS2020

Drop Size Distribution Measurements in Outer Rainbands of Hurricane Dorian at the NASA Wallops Precipitation-Research Facility

Hurricane rainbands are very efficient rain producers, but details on drop size distributions are still lacking. This study focuses on the rainbands of hurricane Dorian as they traversed the densely instrumented NASA precipitation-research facility at Wallops Island, VA, over a period of 8 h. Drop size distribution (DSD) was measured using a high-resolution meteorological particle spectrometer (MPS) and 2D video disdrometer, both located inside a double-fence wind shield. The shape of the DSD was examined using double-moment normalization, and compared with similar shapes from semiarid and subtropical sites. Dorian rainbands had a superexponential shape at small normalized diameter values similar to those of the other sites. NASA’s S-band polarimetric radar performed range height-indicator (RHI) scans over the disdrometer site, showing some remarkable signatures in the melting layer (bright-band reflectivity peaks of 55 dBZ, a dip in the copolar correlation to 0.85 indicative of 12–15 mm wet snow, and a staggering reflectivity gradient above the 0 °C level of −10 dB/km, indicative of heavy aggregation). In the rain layer at heights < 2.5 km, polarimetric signatures indicated drop break-up as the dominant process, but drops as large as 5 mm were detected during the intense bright-band period.

Merhala Thurai↗

NASA NTRS2019

Satellite Conjunction Assessment Risk Analysis for "Dilution Region" Events: Issues and Operational Approaches

An important activity within Space Traffic Management is the detection and prevention of possible on-orbit collisions between space objects. The principal parameter for assessing collision likelihood is the probability of collision, which is widely accepted among conjunction assessment practitioners; but it possesses a known deficiency in that it can produce a false sense of safety when the orbital position uncertainties for the conjuncting objects are high. The probability of collision is said to be “diluted” in such a situation and to understate the possible risk; certain approaches have been recommended by researchers to provide (largely conservative) risk estimates and remediation methodologies in these cases. The present analysis explores two of the main proposals for quantifying and remediating possible risk in the dilution region and quantifies their operational implications. These implications with regard to imputed additional workload are considerable, especially in anticipating the conjunction event levels expected with the deployment of the USAF Space Fence radar. This effort has been undertaken as part of a larger enterprise that seeks to clarify the philosophical and statistical underpinnings of the conjunction risk assessment process. The analysis presented herein argues that a form of hypothesis testing is implicitly used in conjunction assessment risk analysis, and that there are a number of conceptual and practical reasons for constructing the associated null hypothesis to counsel against a satellite conjunction remediation action. In short, it is concluded that, for the purposes of determining whether a conjunction remediation action should be pursued, dilution-region probabilities of collision should be treated no differently from those produced under other circumstances.

Probability of collision↗

NASA NTRS2023

Experimental Investigation of Block-TPS Fence/Gap Roughness Effects on Transition Onset and Turbulent Heating at Mach 6

An experimental investigation of boundary-layer transition and convective surface heating on wind tunnel models that simulated aeroshells comprised of multiple blocks of thermal protection system (TPS) material has been performed. Two representative entry vehicle geometries, a sphere-cone aeroshell and a sphere-cone aeroshell, were considered. Multiple cast ceramic models of each geometry were fabricated with varying fence heights or gap depths to represent gap fillers that either protrude above, or are recessed below, the TPS blocks due to differential ablation during reentry. Wind tunnel testing was performed at Mach 6 over a range of Reynolds numbers sufficient to produce laminar, transitional, and turbulent flow. Convective surface heating and boundary-layer transition onset data were obtained using global phosphor thermography. The experimental heating data are presented herein, as are comparisons to laminar and turbulent smooth-wall heat transfer distributions from computational flow field simulations.

Aerothermodynamics↗

NASA NTRSDate not supplied

An Overview of Ground-Based Radar and Optical Measurements Utilized By the Nasa Orbital Debris Program Office

For over 30 years, the NASA Orbital Debris Program Office (ODPO) has led the characterization of orbital debris (OD) too small to be tracked by the U.S. Space Surveillance Network (SSN), yet which may pose the greatest threat to human spaceflight and robotic missions. Measurements from specialized sensors, including ground-based radars and telescopes capable of detecting smaller objects, provide the foundation for developing statistical models to describe the current state and future evolution of the OD environment from low Earth orbit (LEO) to geosynchronous Earth orbit (GEO). Since 1990, the ODPO has partnered with the U.S. Department of Defense and the Massachusetts Institute of Technology Lincoln Laboratory (MIT/LL) to collect data using the Haystack Ultrawideband Satellite Imaging Radar (HUSIR) – formerly Haystack – to characterize OD in LEO with a sensitivity of approximately 5 mm at 1000 km altitude. In addition, since 1993, the Goldstone Orbital Debris Radar, operated by NASA’s Jet Propulsion Laboratory, has provided data on OD as small as approximately 2-3 mm for altitudes below 1000 km, some of the most sensitive ground-based measurements achievable at these altitudes. Recently, collaborations with the 18 th Space Control Squadron of the U.S. Space Force have also provided the ODPO with special datasets from the Space Fence to extend coverage below the historical SSN limit of 10 cm and to characterize individual breakup events in LEO. For GEO altitudes, the Eugene Stansbery Meter Class Autonomous Telescope (ES-MCAT), a joint NASA-Air Force Research Laboratory project that reached full operational capability in 2021, collects data on debris smaller than 1 m and provides coverage of debris in historically under-sampled high-altitude orbital regimes. This paper summarizes the radar and optical sensors utilized by the ODPO, their unique capabilities, and recent datasets and applications for statistical sampling of the dynamic OD environment.

Alyssa Manis↗

NASA NTRSDate not supplied

An Overview of NASA’s Newest Engineering Model, ORDEM 4.0

Since the mid-1990s, one of the most important products produced by the NASA Orbital Debris Program Office (ODPO) has been the Orbital Debris Engineering Model (ORDEM). This series of models distills down our knowledge of the orbital debris environment to compute debris fluxes on satellites in a given orbit. This information can be used by spacecraft and upper stage designers and operators to design missions for better protection against the debris environment. The current version of the model is ORDEM 3.2, but the ODPO is working on the next generation of ORDEM, to be designated ORDEM 4.0. ORDEM 4.0 will include many known features from previous models, such as the ability to input a spacecraft orbit and time and to compute the flux as a function of debris size, impact speed, impact direction, and debris material densities, as well as uncertainty information on the flux. ORDEM 4.0 will update debris populations using the most recent measurements, including radar observations by the Haystack Ultrawideband Satellite Imaging Radar (HUSIR), NASA’s Goldstone radar, data from the new Space Surveillance Network Space Fence, and observations of Geosynchronous Earth Orbits (GEO) using the Eugene Stansbery-Meter Class Autonomous Telescope (ES-MCAT). The latest in situ impact data from returned hardware surfaces will be used. In addition, ORDEM 4.0 will introduce a parameterized debris shape model based on laboratory hypervelocity impact tests, such as DebriSat. This will allow analysts to implement shape characteristics in their damage equations and more accurately predict impact damage risk by debris of different shapes and orientations. This paper provides an overview of some of the new features forthcoming in ORDEM 4.0 and a status report on its development.

Mark Matney↗

NASA NTRSDate not supplied

An Overview of Ground-Based Radar and Optical Measurements Utilized By the Nasa Orbital Debris Program Office

For over 30 years, the NASA Orbital Debris Program Office (ODPO) has led the characterization of orbital debris (OD) too small to be tracked by the U.S. Space Surveillance Network (SSN), yet which may pose the greatest threat to human spaceflight and robotic missions. Measurements from specialized sensors, including ground-based radars and telescopes capable of detecting smaller objects, provide the foundation for developing statistical models to describe the current state and future evolution of the OD environment from low Earth orbit (LEO) to geosynchronous Earth orbit (GEO). Since 1990, the ODPO has partnered with the U.S. Department of Defense and the Massachusetts Institute of Technology Lincoln Laboratory (MIT/LL) to collect data using the Haystack Ultrawideband Satellite Imaging Radar (HUSIR) – formerly Haystack – to characterize OD in LEO with a sensitivity of approximately 5 mm at 1000 km altitude. In addition, since 1993, the Goldstone Orbital Debris Radar, operated by NASA’s Jet Propulsion Laboratory, has provided data on OD as small as approximately 2-3 mm for altitudes below 1000 km, some of the most sensitive ground-based measurements achievable at these altitudes. Recently, collaborations with the 18 th Space Control Squadron of the U.S. Space Force have also provided the ODPO with special datasets from the Space Fence to extend coverage below the historical SSN limit of 10 cm and to characterize individual breakup events in LEO. For GEO altitudes, the Eugene Stansbery Meter Class Autonomous Telescope (ES-MCAT), a joint NASA-Air Force Research Laboratory project that reached full operational capability in 2021, collects data on debris smaller than 1 m and provides coverage of debris in historically under-sampled high-altitude orbital regimes. This paper summarizes the radar and optical sensors utilized by the ODPO, their unique capabilities, and recent datasets and applications for statistical sampling of the dynamic OD environment.

Alyssa Manis↗

NASA NTRSDate not supplied

An Overview of NASA’s Newest Engineering Model, ORDEM 4.0

Since the mid-1990s, one of the most important products produced by the NASA Orbital Debris Program Office (ODPO) has been the Orbital Debris Engineering Model (ORDEM). This series of models distills down our knowledge of the orbital debris environment to compute debris fluxes on satellites in a given orbit. This information can be used by spacecraft and upper stage designers and operators to design missions for better protection against the debris environment. The current version of the model is ORDEM 3.2, but the ODPO is working on the next generation of ORDEM, to be designated ORDEM 4.0. ORDEM 4.0 will include many known features from previous models, such as the ability to input a spacecraft orbit and time and to compute the flux as a function of debris size, impact speed, impact direction, and debris material densities, as well as uncertainty information on the flux. ORDEM 4.0 will update debris populations using the most recent measurements, including radar observations by the Haystack Ultrawideband Satellite Imaging Radar (HUSIR), NASA’s Goldstone radar, data from the new Space Surveillance Network Space Fence, and observations of Geosynchronous Earth Orbits (GEO) using the Eugene Stansbery-Meter Class Autonomous Telescope (ES-MCAT). The latest in situ impact data from returned hardware surfaces will be used. In addition, ORDEM 4.0 will introduce a parameterized debris shape model based on laboratory hypervelocity impact tests, such as DebriSat. This will allow analysts to implement shape characteristics in their damage equations and more accurately predict impact damage risk by debris of different shapes and orientations. This paper provides an overview of some of the new features forthcoming in ORDEM 4.0 and a status report on its development.

Mark Matney↗

NASA NTRS2024

Idaho & Oregon Agriculture: Monitoring Vegetation Impacts of Livestock Management Practices Used to Reduce Predator Conflicts on Idaho and Oregon Grazing Allotments

The practice of night penning, which involves corralling livestock into a fenced, secure area overnight, aims to safeguard animals from predators. Although this method has proven successful in minimizing interactions between livestock and wildlife, the extent of its impact on vegetation communities is still being explored. This project examines the feasibility of using Net Primary Productivity (NPP) values from the Rangeland Analysis Platform (RAP) to quantify the impacts of night penning on rangeland vegetation communities. RAP provides spatially distributed values of vegetation composition, cover, and productivity, and is derived from imagery from Landsat 5, Landsat 7 & Landsat 8 at a 30m resolution for rangelands across the United States. Our DEVELOP team partnered with Alderspring Ranch, Krebs Livestock, and the U.S Department of Agriculture Animal & Plant Health Inspection Service (APHIS) to analyze the impacts of night penning on vegetation communities. We identified control sites that captured the topographic characteristics of night pen sites used by our partners. We then quantified and compared changes in annual NPP between night pen and control sites. Our analysis of RAP NPP data, using a control-treatment design did not find impacts of night penning on vegetation. However, this was a preliminary analysis, and does not conclusively quantify the impacts of night penning on rangeland vegetation. Our analysis indicated that RAP may be a feasible tool to study livestock management impacts on rangeland vegetation; however, future studies could further validate these findings through ground observations.

Rangeland Analysis Platform (RAP)↗

NASA NTRSDate not supplied

Monitoring Vegetation Impacts of Night Penning in Idaho and Oregon Grazing Allotments Using Remote Sensing

The practice of night penning, which involves corralling livestock into a fenced, secure area overnight, aims to safeguard animals from predators. Although this method has proven successful in minimizing interactions between livestock and wildlife, the extent of its impact on vegetation communities is still being explored. In this study, we used the Rangeland Analysis Platform (RAP), which aggregates spatially distributed values of vegetation composition, cover, and productivity from the Landsat missions, to quantify the effects of night penning on rangeland vegetation communities. We identified control sites that had similar topographic characteristics to night pen sites used by ranchers in Idaho and Oregon. We then quantified and compared changes in annual net primary productivity (NPP) between night pen and control sites. Our study found that RAP NPP data did not show a noticeable difference between control sites and night penning sites. When analyzed quantitatively, night pen sites showed variability in NPP before and after night penning; however, there were few discernible differences between night pen sites and control sites, suggesting that climate conditions can have more of an effect on NPP measurements compared to land management decisions. In the summer of 2024, field crews from the Natural Resource Ecology Laboratory collected biomass data from these rangeland sites, and this will be used to compare and validate RAP products while continuing to investigate the effects of night penning.

Truman Anarella↗

NASA NTRS2024

Launch Complex 39B, SWMU 009, 2023 Performance Monitoring and Air Sparge Expansion Construction Completion Report, Kennedy Space Center, Florida

The 2023 Performance Monitoring and Construction Completion Report (PM-CCR) presents the findings, observations, and results for Air Sparging (AS) operations and expansion activities, as well as sitewide groundwater monitoring for Launch Complex 39B (LC39B), Solid Waste Management Unit (SWMU) 009, at Kennedy Space Center (KSC), Florida. The reporting period for activities covered under this PM-CCR is from January 1, 2023, to December 31, 2023. At LC39B, AS operations began in 2017 in the area west of the launch pad, in the liquid oxygen (LOX) tank area located northwest of the launch pad, and in an area outside of the perimeter fence to protect nearby Outstanding Florida Waters (OFW). The LC39B AS system was installed with 279 AS wells to depths ranging from 23 to 60 feet below land surface (bls), including the sump, correlating to top of screen depths ranging from 20 to 57 feet bls. In December 2022, a total of 22 AS wells were abandoned to support launch pad crane operations, and in November 2023, the system was expanded with five additional AS wells installed to 13 or 17 feet bls near the LOX tank. The remedial objective of the LC39B AS Interim Measure (IM) is to actively decrease concentrations of contaminants of concern (COCs) in groundwater, specifically trichloroethene (TCE), cis-1,2-Dichloroethene (cDCE), and vinyl chloride (VC), to less than their respective Natural Attenuation Default Concentrations (NADCs), so LC39B can transition into a Long-Term Monitoring (LTM) program. This PM-CCR presents the following information for LC39B: • AS system operations and maintenance (O&M) (Year 7 of operation) from January 2023 to December 2023, to include AS trailer relocation in March 2023 and subsequent replacement and re-start in June 2023. • Construction completion details for AS system expansion, which included installation of five new AS wells and one new monitoring well in November 2023. As part of expansion activities, soil samples were also collected for petroleum analysis; no exceedances were identified, and no further investigation for petroleum is warranted. • Performance monitoring results for groundwater sampling events conducted in May/June 2023 (30 wells) and November 2023 (31 wells) in the AS IM area and in the Low Concentration Plume (LCP) areas located north and east of the launch pad for volatile organic compound (VOC) analysis. • Sampling results for one monitoring well, LOX-IW0012S, which is sampled for aluminum on an annual basis (May/June 2023). This well was resampled in November 2023 for both total and dissolved aluminum. Due to a communication error with the laboratory, the May/June 2023 sample was analyzed for total aluminum only. • Groundwater sampling results for per- and polyfluoroalkyl substances (PFAS) collected from seven monitoring wells during the May/June 2023 event to further investigate the Former Sewage Treatment Plant #6 and Percolation Pond area, west of the launch pad. O&M and performance monitoring results show that the AS system at LC39B is operating as designed and meeting performance criteria. Overall runtime was 45 percent (%) during the reporting period (January to December), but the operational runtime was 78% during the timeframe when the system could run (June to December). The most significant downtime contributor was post-launch crane operations following the Artemis launch on November 16, 2022, which lasted until June 2023. During that timeframe, the AS trailer at LC39B was relocated to another KSC remediation site (Wilson Corners) and was subsequently replaced with the AS trailer from the Paint & Oil Locker (POL) remediation site at KSC to resume AS system operations. Performance monitoring results in the AS IM and LCP areas continue to show reduction in COC concentrations over time when compared to baseline levels. In 2023, only one monitoring well (MW0048) detected a COC exceeding its NADC (VC at 740 micrograms per liter [µg/L]), which marks the baseline result for this new well installed during system expansion. Across the rest of the site, VC concentrations have declined or remained stable during the 2023 sampling events. Excluding MW0048, the highest VC result in 2023 was during the May/June sampling event with a concentration of 63 µg/L at MW0032, which is located near MW0048 and the AS expansion area by the LOX tank. TCE was detected in select monitoring wells in the IM area in 2023, but only two locations exceeded the State of Florida Groundwater Cleanup Target Level (GCTL): MW0032 (21 µg/L in May/June 2023 and 9.1 µg/L in November 2023) and MW0036 (5.0 µg/L in November 2023). MW0036 is also located near the LOX tank, on the north side, where the AS system is still operational (Zone Z4). cDCE and trans-1,2-dichloroethene concentrations were less than laboratory method detection limits or their respective GCTLs in all wells sampled in 2023. Near the OFW located northwest of the launch complex, all COC concentrations were less than laboratory method detection limits from monitoring wells (MW0039, MW0040, and LOXTA0002S) sampled in 2023. Aluminum results from LOX-IW0012S, which has been sampled routinely since 2006, detected a total aluminum concentration of 3,900 µg/L during the May/June 2023 sampling event. Results from the November 2023 event detected 5,700 µg/L for total aluminum and 5,500 µg/L for dissolved aluminum. These concentrations slightly decreased from the previous year but remain relatively consistent with historical detections. Aluminum will continue to be sampled on an annual basis at this well as results still exceed the GCTL of 200 µg/L and the Upper Limit of the KSC Background Concentration of 280 µg/L. PFAS results detected nine different PFAS compounds (out of 32 analyzed) from seven wells sampled. Two PFAS compounds, perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA), currently have FDEP Provisional GCTLs of 70 nanograms per liter (ng/L). All seven samples collected resulted in concentrations less than the FDEP Provisional GCTLs for both PFAS compounds; no exceedances were observed. PFOS and PFOA also have assigned United States Environmental Protection Agency (USEPA) Maximum Contaminant Levels (MCLs) of 4 nanograms per liter (ng/L). None of the PFOS results exceeded the USEPA MCLs. PFOA was detected in two samples above the USEPA MCL at concentrations of 5.8 ng/L (ECS-IW0009I) and 5.5 ng/L (ECS-IW0009S). 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 seven wells. PFAS compounds without FDEP Provisional GCTLs or USEPA MCLs were screened against USEPA RSLs. No other detections exceeded their respective USEPA RSLs. Additional PFAS sampling will be conducted as part of a future PFAS Site Assessment. Based on O&M activities and performance monitoring, the following is recommended for LC39B: • Continue with Year 8 AS system operation within Zone Z4, which includes the AS expansion area. Zone Z3, which has been off since 2018, should remain off as no rebound has been observed. Zones Z1 and Z2, which were turned off at the end of 2022, will remain shut down as monitoring well results have consistently been below GCTLs or have low-level detections with stable or decreasing trends (Meeting Minute 2402-M10, Decision 2402-D30). • Continue with performance monitoring in 2024 with the same monitoring well network as 2023, except with the addition of MW0048 in both semi-annual events. Baseline concentrations for this well were collected during the November 2023 performance monitoring event. Semi-annual sampling should be planned for the May 2024 and November 2024 timeframes (Meeting Minute 2402-M10, Decision 2402-D31). • Continue sampling monitoring well, LOX-IW0012S, for aluminum (total and dissolved) on an annual basis in May 2024. It is also recommended to re-develop this well prior to the next sampling event (Meeting Minute 2402-M10, Decision 2402-D32). The above recommendations for LC39B were presented at the February 2024 KSCRT Meeting, with Team consensus reached on the path forward. The contents of this PM-CCR were also presented at this meeting.

Deborah M Wilson↗