Human performance control monitoring system Interim report no. 1, 21 Dec. 1964 - 30 Sep. 1965
Theoretical studies on human performance and control monitoring systems
DECISION MAKING↗
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Holographic method of monitoring the performance of a large telescope mirror
Holographic monitoring method for astronomical telescope mirror
Erickson, K. E.↗
Evaluation of the Air Quality Monitor's Performance on the International Space Station
The Air Quality Monitor (AQM) was flown to the International Space Station (ISS) as an experiment to evaluate its potential to replace the aging Volatile Organic Analyzer (VOA), which ceased operations in August 2009. The AQM (Figure 1) is a small gas chromatography/differential mobility spectrometer (GC/DMS) manufactured by Sionex. Data was presented at last year s ISIMS conference that detailed the preparation of the AQM for flight, including instrument calibration. Furthermore, initial AQM data was compared to VOA results from simultaneous runs of the two instruments. Although comparison with VOA data provided a measure of confidence in the AQM performance, it is the comparison with results from simultaneously acquired air samples (grab sample containers-GSCs) that will define the success (or failure) of the AQM performance. This paper will update the progress in the AQM investigation by comparing AQM data to results from the analyses of GSC samples, returned from ISS. Additionally, a couple of example will illustrate the AQM s ability to detect disruptions in the spacecraft s air quality. Discussion will also focus upon a few unexpected issues that have arisen and how these will be a addressed in the final operational unit now being built.
Limero, Thomas↗
Assessment of Baseline Monitoring Data for the Remote-Handled Low-Level Waste Disposal Facility at Idaho National Laboratory
The purpose of this document is to summarize environmental monitoring data collected at the Remote-Handled Low-Level Waste (RHLLW) Disposal Facility during the first four years of facility operations (FY 2019 through FY 2022). This summary provides a “baseline” condition for the facility, which can be used to distinguish contaminant releases from the RHLLW Disposal Facility from pre existing contamination as well as potential future releases from other sources (i.e., upgradient aquifer sources), as specified in the facility monitoring plan. Sufficient data has been collected over the first four years of operation of the RHLLW Disposal Facility to establish baseline conditions for future compliance monitoring of aquifer wells and performance monitoring of vadose zone lysimeters. Except for seven elevated tritium measurements from lysimeter HFEF-South believed to have been impacted by waste disposals, all data was deemed appropriate for establishing baseline concentrations. Monitoring of the aquifer detected indicator analytes gross alpha and gross beta and target analytes tritium and C-14. There were a few C-14 detections prior to an increase in the required detection level (RDL) after the first round of sampling. I-129 and Tc-99 were not detected above RDLs in aquifer samples. Lysimeter samples detected indicator analytes gross alpha and gross beta and target analyte tritium. Target analytes C-14, I-129, and Tc-99 were not detected above RDLs in lysimeter samples. Except for tritium, baseline concentrations of indicator and target analytes measured during the first four years of RHLLW facility operations are expected to represent conditions through the expected 20 year operating period of the facility. Elevated tritium in the aquifer, a result of past discharges of tritium at upgradient facilities, showed a decline over the first four years of operations, and levels are expected to continue to decline with time as a result of dilution and decay. Current tritium levels in lysimeter samples may be elevated due to tritium in the water applied during construction and infiltration testing of the facility. As a result, tritium concentrations in lysimeters may decline with time as a result of dilution and decay. Statistical measures (i.e., mean, standard deviation, and 99% upper confidence level [UCL]) were calculated for all detected analytes using the four years of concentration data. These measures will be used to evaluate future monitoring results and to demonstrate the facility is performing, or not performing, as established in the facility performance assessment (PA). Future monitoring results will also be combined with the baseline data in this report to further establish temporal trends and natural variability in the measurements. Based on the data collected during the baseline period, it is recommended the gross alpha action level for performance monitoring increase from 10 to 20 pCi/L due to several baseline measurements exceeding the preliminary action level of 10. An action level of 20 pCi/L is slightly greater than the 99% UCL, is protective of the aquifer, and would reduce unnecessary sampling. It is also recommended that tritium be added to the lysimeter analyte list for post-baseline period monitoring. Tritium, while not a dose concern, is a good tracer that can provide valuable information on water flow in and around the RHLLW Disposal Facility. Recommendations for a tritium action level are provided if considered necessary.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
YUCSA: A CLIPS expert database system to monitor academic performance
The York University CLIPS Student Administrator (YUCSA), an expert database system implemented in C Language Integrated Processing System (CLIPS), for monitoring the academic performance of undergraduate students at York University, is discussed. The expert system component in the system has already been implemented for two major departments, and it is under testing and enhancement for more departments. Also, more elaborate user interfaces are under development. We describe the design and implementation of the system, problems encountered, and immediate future plans. The system has excellent maintainability and it is very efficient, taking less than one minute to complete an assessment of one student.
Toptsis, Anestis A.↗
Object-oriented Approach to High-level Network Monitoring and Management
An absolute prerequisite for the management of large investigating methods to build high-level monitoring computer networks is the ability to measure their systems that are built on top of existing monitoring performance. Unless we monitor a system, we cannot tools. Due to the heterogeneous nature of the hope to manage and control its performance. In this underlying systems at NASA Langley Research Center, paper, we describe a network monitoring system that we use an object-oriented approach for the design, we are currently designing and implementing. Keeping, first, we use UML (Unified Modeling Language) to in mind the complexity of the task and the required model users' requirements. Second, we identify the flexibility for future changes, we use an object-oriented existing capabilities of the underlying monitoring design methodology. The system is built using the system. Third, we try to map the former with the latter. APIs offered by the HP OpenView system.
Mukkamala, Ravi↗
Launch Complex 39B, SWMU 009 Air Sparging System Expansion Implementation Work Plan Kennedy Space Center, Florida
This Implementation Work Plan (IWP) for expansion of the Air Sparging (AS) system at Launch Complex 39B (LC39B), presents the design and coordination specifics to expand the existing AS Interim Measure (IM) at LC39B located at Kennedy Space Center (KSC), Florida. The existing AS system at LC39B was installed in 2017 and included 279 AS wells. LC39B has been designated as Solid Waste Management Unit (SWMU) 009 under the KSC Resource Conservation and Recovery Act (RCRA) Corrective Action Program. Expansion of the AS IM will include installation of an additional five AS wells to depths of approximately 13 and 17 feet below land surface (bls) to remediate contaminated groundwater identified northwest of the launch pad, near the liquid oxygen (LOX) tank. The expansion will target concentrations of cis-1,2-dichloroethene (cDCE) and vinyl chloride (VC) greater than Florida Department of Environmental Protection (FDEP) Natural Attenuation Default Concentrations (NADCs) that were identified during direct push technology (DPT) sampling events between 2019-2022 in shallow intervals between 8 and 16 feet bls. The objective for this expansion is to remediate contaminated groundwater within the treatment zone to below NADCs to support transition to monitored natural attenuation (MNA) through a long-term monitoring (LTM) program. This expansion will treat approximately 0.07-acres of residual groundwater contamination. The IWP design for this expansion will utilize the existing AS system trailer that is already onsite and operating. The five new AS expansion wells will be integrated into the existing Zone Z4 distribution manifold to deliver compressed air to the new AS wells. To deliver airflow, three existing lateral lines will be split in the field at a lateral split junction point (using 2-way or 3-way splits). Each split lateral will supply air to AS wells at the same depth interval to minimize preferential pathways. The trenching layout for the new AS wells was developed to minimize ground disturbance due to the amount of utilities in the area. One new monitoring well will also be installed and added to LC39B’s performance monitoring program to evaluate the effectiveness of the AS system expansion. This well will be sampled on a semi-annual basis for volatile organic compounds, with results evaluated to determine if system adjustments may be required. The main components of this IWP were presented to the KSC Remediation Team (KSCRT) at the October 2022 Meeting (Meeting 2210-M05). DPT delineation data from the LOX area were also presented, which included some inferred boundaries due to physical restrictions of the LOX tank and associated concrete pad and infrastructure. Planned monitoring well sampling in this area will help determine if back-diffusion may be occurring from beneath the pad. Additionally, based on potential petroleum odors and staining identified at two DPT locations during the January 2022 DPT event in the 10-16 feet bls range, a KSCRT action item was assigned during the October 2022 meeting to collect soil samples for petroleum compounds if similar odors or staining are identified during IM implementation. Construction completion and performance monitoring will be incorporated into LC39B’s groundwater monitoring reports, which are currently submitted on an annual basis to FDEP to document operation and maintenance activities and results from the AS IM.
Deborah M. Wilson↗
Detecting Satellite Laser Ranging Station Data and Operational Anomalies with Machine Learning Isolation Forests at NASA's CDDIS
The International Laser Ranging Service (ILRS) is currently composed of 45 active satellite laser ranging (SLR) stations with several more set to join the network over the next several years. Station changes and histories are logged to files, but not always in real time. Sometimes these details are not added until long after changes have been made to the station –on occasion, years later. This in addition to unexpected hardware errors and other system issues that are not immediately detected impact the products generated by analysts. The ILRS Central Bureau (CB) and NASA’s Crustal Dynamics Data Information System (CDDIS) have worked to provide tools for station engineers to use. This includes the creation of station plots which contain temperature and pressure information along with LAser GEOdynamic Satellite (LAGEOS) and LAser RElativity Satellite (LARES) tracking information that enable the monitoring of station performance and todetermine whether the station has undergone any changes. As next steps, the CDDIS is working to enhance these station performance monitoring tools through machine learning. Isolation forest is an unsupervised machine learning algorithm commonly applied to anomaly detection. In this poster, the CDDIS details the steps taken to track anomalies within SLR station performance using isolation forest with LAGEOS and LARES satellite data.
Benjamin P Michael↗
In Situ Chemical Reduction Interim Measures Work Plan Hot Spot 3 Mobile Launcher Platform Rehabilitation Sites / Vehicle Assembly Building Area (SWMU 056) Kennedy Space Center, Florida
This document presents the design details of an In Situ Chemical Reduction (ISCR) Interim Measures Work Plan for Hot Spot 3 within Mobile Launcher Platform Rehabilitation Sites/Vehicle Assembly Building Area, Solid Waste Management Unit (SWMU) 056 (SWMU 056), located at the John F. Kennedy Space Center, Florida. The interim measures (IM) treatment zone encompasses an area identified as the High Concentration Plume (HCP), which is defined as the area with chlorinated volatile organic compound (CVOC) groundwater concentrations greater than their respective Natural Attenuation Default Concentration (NADC). The objective of the IM is to remove CVOC mass within the treatment area to levels that facilitate a transition to natural attenuation monitoring. The IM design consists of the selected ISCR amendment, Provect-IR, which is a mixture of solid reagents in a single product that promotes enhanced reductive dechlorination and ISCR. ProvectIR includes natural antimethanogenic compounds; multiple hydrophilic, nutrient-rich organic carbon sources; zero valent iron; chemical oxygen scavengers; and vitamin and mineral sources. The proposed treatment area for this IM encompasses less than 1 acre and includes three vertical treatment intervals to reach the NADC plumes that vary per CVOC and depth: 4 to 10 feet below land surface (bls), 10 to 18 feet bls, and 42 to 52 feet bls. The amendment will be distributed through 16 injection points (IP01 through IP16) using dosing rates ranging from 0.4% to 0.6% of soil mass within the treatment interval and a 15% or 20% slurry strength. Dosage rates and slurry strength are based on groundwater geochemistry, soil characteristics, and contaminant concentrations. To aid in the evaluation of the ISCR IM performance, six performance monitoring wells will be installed following injections and sampled semiannually. CVOC parameters will be sampled until concentrations reduce to below their NADC. Underground Injection Control parameters will be sampled until concentrations decrease to background levels or to levels that meet respective groundwater standards. Sampling frequency will be evaluated annually and modified as needed. The path forward for the ISCR IM implementation includes preparing the IM Implementation Work Plan, ISCR injections, monitoring well installation, performance monitoring, and reporting.
Randall K. Sillan↗
Monitoring Human Performance on Future Deep Space Missions Abstract
NASA and the commercial spacecraft community are working diligently to put the first woman on the moon in the 2024 timeframe. At the same time, NASA researchers are thinking about how to solve the even larger challenges that future deep space missions will bring. Space travel itself is difficult, but astronauts on deep space missions will face obstacles and unknowns never before experienced. In addition to the altered gravity and hostile/closed environment of a spacecraft, deep space crews will face increased radiation, isolation, and distance from Earth. During Extravehicular Activity (EVA, or “spacewalk”) operations, crew will experience increased physical and cognitive workload due to extended types, frequencies and durations of tasks performed on exploration missions in partial gravity environments. All of these stressors will impact crew physical and mental health and performance in difficult-to-anticipate ways. Crew autonomy may be one of the biggest challenges faced. Communication delays and blackouts will occur, and in those situations, the crew may not have access to the Mission Control Center (MCC). They may be forced to be solely dependent on each other and the available information onboard to stay alive, healthy, and achieve the mission. The only conceivable way to meet the challenges of Earth independence is to enable the crew to monitor their own health and performance -- preferably unobtrusively as they perform their duties. Technologies and techniques must be developed to aid the crew in these assessments. A deep space mission is expected to have relatively short periods of high cognitive demand, stress, and fatigue, alongside potentially long periods of cognitive underload during the transit, where boredom, loneliness, and depression can set in. Both ends of this spectrum are dangerous. Crew must be made aware when their task performance drops significantly, when their cognitive workload is too high, when they have lost situation awareness, or when they are too stressed or too fatigued to perform well. They must be able to identify these risks, and then mitigate them with countermeasures available onboard. A number of self-monitoring technologies are presently being explored by NASA to advance crew state determination capabilities. These range from real-time, physiological workload and situation awareness assessments, to crew health measurements determining physical and mental fitness for duty, to task performance metrics such as suit resource expenditures. For EVA tasks during surface exploration missions, biomedical information such as metabolic rate may be provided to crewmembers for situational awareness related to task performance efficiency. In addition, translation distances, hydration, nutrition, inspired CO2 exposure and other consumables usage rates may be useful input metrics for modeling individualized performance during tasks to inform crew or provide estimates of work efficiency. Oculomotor metrics such as gaze dwell time, pupilometry, and eye tracking collected in advanced helmet mounted displays could potentially be used to characterize crew situation awareness. This paper highlights some of these projects, and provides broader discussion about the need for advanced monitoring and smart technologies, as NASA takes the leap into the next generation of space exploration.
Kritina Holden↗
Monitoring Human Performance on Future Deep SpaceMissions
NASA and the commercial spacecraft community are working diligently to put the first woman on the moon in the 2024 timeframe. At the same time, NASA researchers are thinking about how to solve the even larger challenges that future deep space missions will bring – primary among them is crew autonomy. Deep space mission crews will face communication delays and blackouts, and in those situations, the crew may not have access to Mission Control Center (MCC) experts. They will be dependent on each other and the available information onboard to stay alive, healthy, and achieve the mission. The only conceivable way to meet the challenges of Earth independence is to enable the crew to monitor their own health and performance. A number of technologies are presently being explored by NASA to enable crew self-monitoring. This paper highlights select projects, and provides broader discussion about the need for advanced monitoring technologies
Kritina Anderson↗
Hybrid Analytics Solution to Improve Coal Power Plant Operations
This project focused on developing advanced methods for thermal performance monitoring of a coal-fueled power plant. The specific goal was to develop and demonstrate a new thermal performance monitoring approach using a hybrid model that integrates a physics-based heat balance model with a machine learning-based pattern recognition model. The hybrid model enables increased accuracy and scope of the thermal analysis and an improved ability to monitor and detect changes in plant operation. This new approach takes full advantage of the individual model capabilities and creates an important new set of capabilities not previously possible using the two types of models separately. Using the heat balance model, a rich set of derived parameters (virtual sensors) are calculated from the measured plant operating data at each time point. The combined measured and derived data values are used by machine learning algorithms to create pattern recognition models over the range of normal unit operation. To create the monitoring models, historical data from normal operation of the plant is first processed by the heat balance model to compute the derived parameter data. The result is a greatly expanded set of normal operating data that can be used as input to create the pattern recognition model. Once the models are calibrated for normal operation, the hybrid model is suitable for use in continuous online monitoring. During online monitoring, new plant operating data is processed first by the heat balance model and then by the pattern recognition model. Results from the pattern recognition model quantify the deviation of each measured or derived parameter from its expected value in normal operation. The hybrid models can detect abnormal changes in plant operating data with very high accuracy and sensitivity. When abnormal behavior is detected, alerts are generated automatically for evaluation by the plant monitoring staff. The new hybrid solution product was developed and verified in the performance of the project. The hybrid solution was tested first in a simulation environment that mimicked the plant data systems and infrastructure used by U.S. power generating plants and utilities. The hybrid solution was then deployed for real-time, online monitoring of an operating coal-fueled power plant at a field test site. Field testing demonstrated that all hybrid solution development objectives were accomplished. The project work was based on combining the capabilities of two existing software products to create the new hybrid solution product. One of these was the existing MapEx® heat balance product and the other was the existing SureSense® advanced pattern recognition product. Each of these separate products was assessed to be at a Technology Readiness Level (TRL) of 9 at the start of the effort. The hybrid solution product was assessed to be at a TRL of 2 at the start of the project based on early feasibility work by the project team. At completion of the field testing performed in the project, the hybrid solution product was assessed to be at a TRL of 7. The project team expects that the hybrid solution product will be deployed commercially and will achieve a TRL of 9 within one year after completion of the project.
01 COAL, LIGNITE, AND PEAT↗
Monitoring Plan for the Idaho National Laboratory Remote Handled Low Level Waste Disposal Facility
This monitoring plan for Idaho National Laboratory’s Remote-Handled Low Level Waste Disposal Facility was developed to meet the requirements for monitoring low-level waste disposal facilities according to the U.S. Department of Energy (DOE) Order 435.1, “Radioactive Waste Management,” and the guidance provided in the associated technical standard “Disposal Authorization Statement and Tank Closure Documentation” (DOE-STD-5002-2017). The purpose of this monitoring plan is to document a monitoring strategy that includes (1) compliance monitoring activities to demonstrate compliance with regulatory standards/limits and (2) performance monitoring to build confidence the facility is performing as demonstrated in the facility performance assessment (PA) (DOE-ID 2018a), composite analysis (CA) (DOE ID 2012), and CA addendum (DOE-ID 2018b). The de minimus impact to the aquifer predicted by the PA suggests that aquifer compliance monitoring should be augmented with performance monitoring of the drainage course materials and sedimentary interbeds in the vadose zone beneath the facility to provide a more effective means of identifying performance deviations. The monitoring approach delineated in this document was informed by the systems evaluation of natural and engineered facility features presented in the PA, an assessment of aquifer baseline conditions (INL 2017d), the dose analysis conducted in support of the PA and CA, and monitoring data collected during the first four years of facility operations (baseline monitoring phase) (INL 2023b). This plan provides monitoring locations, sampling frequencies, and sampling methods; recommendations for data evaluation; and a description of the monitoring plan implementation. Collected data will be used to demonstrate facility compliance and to identify conditions that are not consistent with the key assumptions made by the PA and CA.
12 - MGMT OF RADIOACTIVE AND NON-RADIOACTIVE WASTE↗
Display/control requirements for VTOL aircraft
Quantative metrics were determined for system control performance, workload for control, monitoring performance, and workload for monitoring. Pilot tasks were allocated for navigation and guidance of automated commercial V/STOL aircraft in all weather conditions using an optimal control model of the human operator to determine display elements and design.
Hoffman, W. C.↗
Distributed Large Data-Object Environments: End-to-End Performance Analysis of High Speed Distributed Storage Systems in Wide Area ATM Networks
We have developed and deployed a distributed-parallel storage system (DPSS) in several high speed asynchronous transfer mode (ATM) wide area networks (WAN) testbeds to support several different types of data-intensive applications. Architecturally, the DPSS is a network striped disk array, but is fairly unique in that its implementation allows applications complete freedom to determine optimal data layout, replication and/or coding redundancy strategy, security policy, and dynamic reconfiguration. In conjunction with the DPSS, we have developed a 'top-to-bottom, end-to-end' performance monitoring and analysis methodology that has allowed us to characterize all aspects of the DPSS operating in high speed ATM networks. In particular, we have run a variety of performance monitoring experiments involving the DPSS in the MAGIC testbed, which is a large scale, high speed, ATM network and we describe our experience using the monitoring methodology to identify and correct problems that limit the performance of high speed distributed applications. Finally, the DPSS is part of an overall architecture for using high speed, WAN's for enabling the routine, location independent use of large data-objects. Since this is part of the motivation for a distributed storage system, we describe this architecture.
Johnston, William↗
Know Your Enemy - Implementation of Bioremediation within a Suspected DNAPL Source Zone Following High-Resolution Site Characterization at Contractors Road Heavy Equipment Area, Kennedy Space Center, Florida
The National Aeronautics and Space Administration (NASA), Kennedy Space Center (KSC), has adopted high-resolution site characterization (HRSC) sampling techniques during baseline sampling prior to implementation of remedies to confirm and refine the conceptual site model (CSM). HRSC sampling was performed at Contractors Road Heavy Equipment Area (CRHE) prior to bioremediation implementation to verify the extent of the trichloroethene (TCE) dense non-aqueous phase liquid (DNAPL) source area (defined as the area with TCE concentrations above 1% solubility) and its daughter product dissolved plume that had been identified during previous HRSC events. The results of HRSC pre-bioremediation implementation sampling suggested that the TCE source area was larger than originally identified during initial site characterization activities, leading to a design refinement to improve electron donor distribution and increase the likelihood of achieving remedial objectives. Approach/Activities: HRSC was conducted from 2009 through 2014 to delineate the vertical and horizontal extent of chlorinated volatile organic compounds (CVOCs) in the groundwater. Approximately 2,340 samples were collected from 363 locations using direct push technology (DPT) groundwater sampling techniques. Samples were collected from up to 14 depth intervals at each location using a 4-foot sampling screen. This HRSC approach identified a narrow (approx. 5 to 30 feet wide), approximately 3,000 square foot TCE DNAPL source area (maximum detected TCE concentration of 160,000 micrograms per liter [micro-g/L] at DPT sampling location DPT0225). Prior to implementation of a bioremediation interim measure, HRSC baseline sampling was conducted using DPT groundwater sampling techniques. Concentrations of TCE were an order of magnitude lower than previous reported (12,000 micro-g/L maximum at DPT sampling location DPT0225) at locations sampled adjacent to previous sampling locations. To further evaluate the variability in concentrations observed additional sampling was conducted in 2016. The results identified higher concentrations than originally detected within the previously defined source area and the presence of source zone concentrations upgradient of the previously defined source area (maximum concentration observed 570,000 micro-g/L). The HRSC baseline sampling data allowed for a revision of the bioremediation design prior to implementation. Bioremediation was implemented within the eastern portion of the source area in November and December 2016 and quarterly performance monitoring was completed in March and June 2017. Reductions in CVOC concentrations from baseline were observed at all performance monitoring wells in the treatment area, and by June 2017, an approximate 95% CVOC mass reduction was observed based on monitoring well sampling results. Results/Lessons Learned: The results of this project suggest that, due to the complexity of DNAPL source zones, HRSC during pre-implementation baseline sampling in the TCE source zone was an essential strategy for verifying the treatment area and depth prior to remedy implementation. If the upgradient source zone mass was not identified prior to bioremediation implementation, the mass would have served as a long-term source for the dissolved plume.
Chrest, Anne↗
Aircraft Engine-Monitoring System And Display
Proposed Engine Health Monitoring System and Display (EHMSD) provides enhanced means for pilot to control and monitor performances of engines. Processes raw sensor data into information meaningful to pilot. Provides graphical information about performance capabilities, current performance, and operational conditions in components or subsystems of engines. Provides means to control engine thrust directly and innovative means to monitor performance of engine system rapidly and reliably. Features reduce pilot workload and increase operational safety.
Abbott, Terence S.↗
Supply Warehouse#3, SWMU 088 Operations, Maintenance, and Monitoring Report Kennedy Space Center, Florida
This document presents the findings, observations, and results associated with Operations, Maintenance, and Monitoring (OM&M) activities of Corrective Measures Implementation (CMI) activities conducted at Supply Warehouse #3 (SW3) located at John F. Kennedy Space Center (KSC), Florida from October 8, 2015, to September 12, 2016, and performance monitoring results for semi-annual sampling events conducted in March and September 2016. The primary objective of SW3 CMI is to actively decrease concentrations of trichloroethene (TCE) and vinyl chloride (VC) to less than Florida Department of Environmental Protection (FDEP) Natural Attenuation Default Concentrations (NADCs), and the secondary objective is to reduce TCE, cis-1,2-dichloroethene (cDCE), trans-1,2-dichloroethene (tDCE), 1,1-dichloroethene (11DCE), and VC concentrations to less than FDEP Groundwater Cleanup Target Levels (GCTLs). The SW3 facility has been designated Solid Waste Management Unit (SWMU) 088 under KSC's Resource Conservation and Recovery Act (RCRA) Corrective Action Program. Based on the results to date, the SW3 air sparging (AS) system is operating at or below the performance criteria as presented in the 2008 SW3 Corrective Measures Implementation (CMI) Work Plan and 2009 and 2012 CMI Work Plan Addenda. Since the start of AS system operations on December 19, 2012, through the September 2016 groundwater sampling event, TCE concentrations have decreased to less than the GCTL in all wells within the Active Remediation Zone (ARZ), and VC results remain less than NADC but greater than GCTL. Based on these results, team consensus was reached at the October 2016 KSC Remediation Team (KSCRT) meeting to continue AS system operations and semi-annual performance monitoring of volatile organic compounds in March 2017 at ten monitoring wells at select locations, and in September 2017 at four monitoring wells at select locations to reduce VC concentrations to below GCTL. Additionally, surface water samples will be collected at locations SW0001, SW0002, and SW0003 during both the March and September 2017 events. Team consensus was also reached at the October 2017 KSCRT meeting to continue with operation and maintenance (O&M) of the AS system at SW3.
REPORT↗