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At least 127 records · Page 7

An agentic artificially intelligent X-ray scientist

Executing experimental tasks in both normal research laboratories and large-scale scientific facilities often requires extensive human supervision and remains a key challenge on the path to fully autonomous, artificial intelligence (AI)-driven science. Here we demonstrate a large language model-driven agent that autonomously performs X-ray sample alignment on a synchrotron beamline by planning actions, executing instrumental commands, interpreting observations and iterating towards experimental goals. Based on existing large language models with structured tool-use via the model context protocol, our AI X-ray scientist was guided and tested using an in-house-built virtual experimental setup that mirrors a six-circle diffractometer at an operational synchrotron beamline. The agentic workflow developed in the virtual environment was directly deployed on a real beamline, where it correctly identified reference reflections and determined the orientation matrix, an essential first step in any type of single-crystal scattering experiment. Our AI X-ray scientist responded effectively to unexpected experimental conditions, demonstrating adaptive problem-solving and readiness for addressing practical experimental situations. Our study provides a step towards autonomous operation across diverse experimental environments at large-scale scattering facilities.

Chen, Zhantao (ORCID:0000000319543868)↗

Space shuttle maintenance program planning document

A means for developing a space shuttle maintenance program which will be acceptable to the development centers, the operators (KSC and AF), and the manufacturer is presented. The general organization and decision processes for determining the essential scheduled maintenance requirements for the space shuttle orbiter are outlined. The development of initial scheduled maintenance programs is discussed. The remaining maintenance, that is non-scheduled or non-routine maintenance, is directed by the findings of the scheduled maintenance program and the normal operation of the shuttle. The remaining maintenance consists of maintenance actions to correct discrepancies noted during scheduled maintenance tasks, nonscheduled maintenance, normal operation, or condition monitoring.

Brown, D. V.↗

The case for digital twins in metal additive manufacturing

The digital twin (DT) is a relatively new concept that is finding increased acceptance in industry. A DT is generally considered as comprising a physical entity, its virtual replica, and two-way digital data communications in-between. Its primary purpose is to leverage the process intelligence captured within digital models—or usually their faster-solving surrogates—towards generating increased value from the physical entities. The surrogate models are created using machine learning based on data obtained from the field, experiments and digital models, which may be physics-based or statistics-based. Anomaly detection and correction, and diagnostic closed-loop process control are examples of how a process DT can be deployed. In the manufacturing industry, its use can achieve improvements in product quality and process productivity. Metal additive manufacturing (AM) stands to gain tremendously from the use of DTs. This is because the AM process is inherently chaotic, resulting in poor repeatability. However, a DT acting in a supervisory role can inject certainty into the process by actively keeping it within bounds through real-time control commands. Closed-loop feedforward control is achieved by observing the process through sensors that monitor critical parameters and, if there are any deviations from their respective optimal ranges, suitable corrective actions are triggered. The type of corrective action (e.g. a change in laser power or a modification to the scanning speed) and its magnitude are determined by interrogating the surrogate models. Because of their artificial intelligence (AI)-endowed predictive capabilities, which allow them to foresee a future state of the physical twin (e.g. the AM process), DTs proactively take context-sensitive preventative steps, whereas traditional closed-loop feedback control is usually reactive. Apart from assisting a build process in real-time, a DT can help with planning the build of a part by pinpointing the optimum processing window relevant to the desired outcome. Again, the surrogate models are consulted to obtain the required information. In this article, we explain how the application of DTs to the metal AM process can significantly widen its application space by making the process more repeatable (through quality assurance) and cheaper (by getting builds right the first time).

36 MATERIALS SCIENCE↗

StarPlan: A model-based diagnostic system for spacecraft

The Sunnyvale Division of Ford Aerospace created a model-based reasoning capability for diagnosing faults in space systems. The approach employs reasoning about a model of the domain (as it is designed to operate) to explain differences between expected and actual telemetry; i.e., to identify the root cause of the discrepancy (at an appropriate level of detail) and determine necessary corrective action. A development environment, named Paragon, was implemented to support both model-building and reasoning. The major benefit of the model-based approach is the capability for the intelligent system to handle faults that were not anticipated by a human expert. The feasibility of this approach for diagnosing problems in a spacecraft was demonstrated in a prototype system, named StarPlan. Reasoning modules within StarPlan detect anomalous telemetry, establish goals for returning the telemetry to nominal values, and create a command plan for attaining the goals. Before commands are implemented, their effects are simulated to assure convergence toward the goal. After the commands are issued, the telemetry is monitored to assure that the plan is successful. These features of StarPlan, along with associated concerns, issues and future directions, are discussed.

Heher, Dennis↗

Robot learning and error correction

A model of robot learning is described that associates previously unknown perceptions with the sensed known consequences of robot actions. For these actions, both the categories of outcomes and the corresponding sensory patterns are incorporated in a knowledge base by the system designer. Thus the robot is able to predict the outcome of an action and compare the expectation with the experience. New knowledge about what to expect in the world may then be incorporated by the robot in a pre-existing structure whether it detects accordance or discrepancy between a predicted consequence and experience. Errors committed during plan execution are detected by the same type of comparison process and learning may be applied to avoiding the errors.

Friedman, L.↗

Usability of an Updated Version of the Supplemental Data Service Provider-Consolidated Dashboard for Supporting Uncrewed Aircraft System Traffic Management

The Supplemental Data Service Provider-Consolidated Dashboard (SDSP-CD) is a preflight planning user interface (UI) that serves to aid operators when drafting routes for small uncrewed aircraft systems (sUASs). The primary function of the SDSP-CD is to identify hazards that an sUAS may encounter along a proposed flight path and assess the severity of these risks. A usability study was conducted on an updated version of the SDSP-CD to determine if the most recent iterations made to the system improved objective performance and subjective user experience. There are two main components of the SDSP-CD interface: (1) the dashboard and (2) the interactive map. The dashboard provides users with hazard and vehicle limitations for each sUAS in their fleet while the map contains a graphical representation of each vehicle’s route, hazard details, and geographic information. A series of preflight risk-assessment questions and tasks were developed to examine how participants interact with the updated version of the SDSP-CD. Additionally, a new service that measures vertiport congestion was developed and included as one of the services that was tested. In the present study, participants were trained to use the SDSP-CD and then completed two simulated scenarios during which they performed a variety of tasks, responded to questions, and completed surveys. The two scenarios developed for the present study were the Package Delivery and Hurricane Preparation scenarios. The Package Delivery scenario involved a fleet of four sUASs delivering low-stakes items (e.g., lunches and snacks) to people in a fictitious city. The Hurricane Preparation scenario involved a fleet of 11 sUASs delivering a range of supplies (from medicine to boardgames) to employees stranded at an office park due to road closures caused by an impending hurricane. Participants assumed the role of a fleet manager during both scenarios and were responsible for managing the sUASs in their fleet. Questions included those with objectively correct responses, open-ended strategy responses, and subjective user experience feedback. It was found that participants were largely successful at using the SDSP-CD interface to answer questions with objectively correct responses. Additionally, participants were able to use reasoning and logic based on the information available in the SDSP-CD to determine the cause of various risks and what actions they would consider taking. Finally, although participants reported that there were elements of the UI that could be improved, overall feedback pertaining to user experience suggested that the SDSP-CD concept is viable.

usability testing↗

Integrating Theory and Practice: Applying the Quality Improvement Paradigm to Product Line Engineering

My assertion is that not only are product lines a relevant research topic, but that the tools used by empirical software engineering researchers can address observed practical problems. Our experience at NASA has been there are often externally proposed solutions available, but that we have had difficulties applying them in our particular context. We have also focused on return on investment issues when evaluating product lines, and while these are important, one can not attain objective data on success or failure until several applications from a product family have been deployed. The use of the Quality Improvement Paradigm (QIP) can address these issues: (1) Planning an adoption path from an organization's current state to a product line approach; (2) Constructing a development process to fit the organization's adoption path; (3) Evaluation of product line development processes as the project is being developed. The QIP consists of the following six steps: (1) Characterize the project and its environment; (2) Set quantifiable goals for successful project performance; (3) Choose the appropriate process models, supporting methods, and tools for the project; (4) Execute the process, analyze interim results, and provide real-time feedback for corrective action; (5) Analyze the results of completed projects and recommend improvements; and (6) Package the lessons learned as updated and refined process models. A figure shows the QIP in detail. The iterative nature of the QIP supports an incremental development approach to product lines, and the project learning and feedback provide the necessary early evaluations.

Stark, Michael↗

AEGIS: Autonomous Entity Global Intelligence System for Urban Air Mobility

This paper presents a global intelligence system that synthesizes aerial vehicles’ real-time physical data, planned actions, and historical behavior into engineered data frames representing the collective state of the airspace and suitable for efficient machine learning consumption. These data frames are then learnt by a deep neural net to build a prediction model that estimates the expected evolution path of the current state, thereby identifying potential future conflicts. This approach lends itself to an automated early warning system that the aerial vehicles can implement onboard with a suitable edge computing module more efficiently and effectively than non-AI methods, and eventually take preventive or corrective measures towards self/collaborative resolution of the issues. Contrary to a centralized early warning system where all vehicles’ task-space eventually converges to a global optimum state, the presented distributed global intelligence system brings in a balance between local utility functions of each vehicle and the global operating framework. This contributes to effectively handle the potential massive scaling in urban air mobility in the near future.

Artificial Intelligence↗

Analysis of Improved Navigation Data for NASA Near Space Network (NSN) Direct-to-Earth (DTE) Ground Stations

Spacecraft navigation is a complex concept that requires a collaboration between network entities and constant corrective action to be successful in the highly variable environment. NASA’s Near Space Network (NSN), Direct-to-Earth (DTE) ground station team is constantly exploring methods to provide better service to NASA spacecraft, including providing radiometric tracking data, subject to cost constraints. Navigation teams, such as the Goddard Space Flight Center (GSFC) Flight Dynamics Facility (FDF), use the tracking data to perform orbit determination to assess where a spacecraft has been, identify where a spacecraft is now, and predict where a spacecraft will be in the future. As NASA plans for more missions beyond low Earth orbit (LEO), there is a need for improved navigation performance which can be directly achieved through improvements in the radiometric tracking data. NASA’s new DTE Ka-band antennas have finer autotrack angle resolution, and the availability of low-cost improved off-the-shelf ground station components, which are involved with producing navigation data. NASA formed a team to provide an assessment of the current NSN, DTE spacecraft navigation service (radiometric tracking) performance baseline with the end goal of defining needed future enhancements to meet the needs for spacecraft above LEO. The communications and navigation community is deriving new techniques in an effort to better service the navigation needs of spacecraft using ground station networks. This paper provides an overview Earth-orbit, direct-to-ground navigation techniques and performance, the development of specifications for new antennas, accuracy of data, spacecraft requirements, accuracy of orbit determination, history of challenges, and considerations for improvements. The discussions in this paper may assist ground station, spacecraft, and mission design teams advance navigation capabilities and more effectively meet requirements.

networks↗

Contractors Road Heavy Equipment Area (SWMU 055) 2022 Annual Groundwater Monitoring Report

This document presents a summary of activities completed at the Contractors Road Heavy Equipment (CRHE) Area, located at Kennedy Space Center (KSC), Florida, from June through December 2022. The activities conducted at the CRHE Area include: - Annual groundwater sampling activities associated with sitewide plume monitoring and Underground Injection Control (UIC) monitoring in the former bioremediation Interim Measures (IM) Hot Spot 1 (HS1) area; - Direct push technology (DPT) groundwater investigation; - Semiannual vapor intrusion (VI) evaluation activities. This facility is designated Solid Waste Management Unit (SWMU) Number 055 (SWMU 055) under KSC’s Resource Conservation and Recovery Act (RCRA) Corrective Action program. HydroGeoLogic, Inc. (HGL) prepared this report for the National Aeronautics and Space NASA) under contract number 80KSC019F0096/80KSC019D0012, Technical Directive-03. An Advance Data Package (ADP) presentation of the elements of this report received Team (KSCRT) agreement at the April 5, 2023, KSCRT meeting. The chlorinated volatile organic compound plume appears to be stable vertically and horizontally. Additional DPT groundwater sampling will be completed to support a remedial alternatives evaluation for potential means to expedite groundwater cleanup. There are per- and polyfluorinated alkyl substances in site groundwater, and assessment is planned in the future. Sub-slab soil gas monitoring results do not indicate any concerns with indoor vapor intrusion. Based on the 2022 annual groundwater sampling results, it is recommended that annual sampling continue to alternate with the wet and dry season, with the next sampling event planned for December 2023.

groundwater↗

Performance Assessment for the Disposal of Low-Level Waste in the 200 West Area Burial Grounds (Annual Status Report FY 2022)

This annual review provides the projected dose estimates of radionuclide inventories disposed in the active 200 West Area Low-Level Waste Burial Grounds (LLBGs) since September 26, 1988. These estimates are calculated using the original dose methodology developed in the performance assessment (PA) analysis (WHC-EP-0645). The estimates are compared with the performance objectives defined in U.S. Department of Energy requirements (DOE O 435.1 and its companion documents DOE M 435.1-1 and DOE-STD-5002-2017). All performance objectives are currently satisfied, and operational waste acceptance criteria (HNF-EP-0063) and waste acceptance practices continue to be sufficient to maintain compliance with performance objectives. Inventory estimates and associated dose estimates from future waste disposal actions are unchanged from previous years’ evaluations that indicate potential impacts well below performance objectives; therefore, future compliance with DOE O 435.1 is expected. Within the active burial grounds, low-level and mixed low-level waste currently may be disposed only in two lined trenches in the 218-W-5 Burial Ground (Trenches 31 and 34) until they are either filled or a decision is made to close these trenches. Some mixed low-level waste is also disposed at the Environmental Restoration Disposal Facility in the 200 West Area (which is covered under a separate PA). During this (fiscal year 2022) reporting period (October 1, 2021, through September 30, 2022), waste was disposed to the 200 West Area LLBGs. Continued groundwater monitoring of the 200 West Area LLBGs indicates no groundwater contamination due to LLBG waste. Current assumptions about future land use at the Hanford Site are consistent with PA analysis assumptions of a postclosure facility that will not be degraded by human activity. The LLBGs are in an area identified for waste management and containment of residual contamination (DOE/EIS-0391). The current closure plan for the LLBGs (DOE/RL-2000-70) estimates that the 200 West LLBGs will be closed in the 2050 timeframe. The Disposal Authorization Statement, other technical basis documents, and the radioactive waste management basis are of continued adequacy to meet the performance objectives of DOE O 435.1. Overall, there are no substantive changes to primary PA assumptions and no changes to the PA analysis conclusion; therefore, compliance with DOE O 435.1 and the Disposal Authorization Statement is maintained. A new PA to evaluate the long-term impacts of three disposal trenches that are currently active within the 200 East and 200 West Areas (Trench 94 in the 200 East Area and Trenches 31 and 34 in the 200 West Area) was initiated in fiscal year 2019 and completed in fiscal year 2022. Corrective actions addressing 3 key issues and 31 secondary issues identified during the review process were developed and submitted to the Low-Level Waste Disposal Facility Federal Review Group Co-Chairs for review and approval. This PA provides additional technical basis for the continued adequacy of the existing Operating Disposal Authorization Statement.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Improving Operational Acceptability of Dynamic Weather Routes Through Analysis of Commonly Use Routings

The Dynamic Weather Routes (DWR) tool is a ground-based trajectory automation system that continuously and automatically analyzes active in-flight aircraft in en route airspace to find simple modifications to flight plan routes that can save significant flying time, while avoiding weather and considering traffic conflicts, airspace sector congestion, special use airspace, and FAA routing restrictions. Trials of the DWR system have shown that significant delay savings are possible. However, some DWR advised routes are also rejected by dispatchers or modified before being accepted. Similarly, of those sent by dispatchers to flight crews as proposed route change requests, many are not accepted by air traffic control, or are modified before implementation as Center route amendments. Such actions suggest that the operational acceptability of DWR advised route corrections could be improved, which may reduce workload and increase delay savings. This paper analyzes the historical usage of different flight routings, varying from simple waypoint pairs to lengthy strings of waypoints incorporating jet routes, in order to improve DWR route acceptability. An approach is developed that can be incorporated into DWR, advising routings with high historical usage and savings potential similar to that of the nominal DWR advisory. It is hypothesized that modifying a nominal DWR routing to one that is commonly used, and nearby, will result in more actual savings since common routings are generally familiar and operationally acceptable to air traffic control. The approach allows routing segments with high historical usage to be concatenated to form routes that meet all DWR constraints. The relevance of a route's historical usage to its acceptance by dispatchers and air traffic control is quantified by analyzing historical DWR data. Results indicate that while historical usage may be less of a concern to flight dispatchers accepting or rejecting DWR advised route corrections, it may be important to air traffic control acceptance of DWR routes.

dynamic weather routes↗

Improving Operational Acceptability of Dynamic Weather Routes (DWR) Through Analysis of Commonly Used Routings

The Dynamic Weather Routes (DWR) tool is a ground-based trajectory automation system that continuously and automatically analyzes active in-flight aircraft in en route airspace to find simple modifications to flight plan routes that can save significant flying time, while avoiding weather and considering traffic conflicts, airspace sector congestion, special use airspace, and FAA routing restrictions. Trials of the DWR system have shown that significant delay savings are possible. However, some DWR advised routes are also rejected by dispatchers or modified before being accepted. Similarly, of those sent by dispatchers to flight crews as proposed route change requests, many are not accepted by air traffic control, or are modified before implementation as Center route amendments. Such actions suggest that the operational acceptability of DWR advised route corrections could be improved, which may reduce workload and increase delay savings. This paper analyzes the historical usage of different flight routings, varying from simple waypoint pairs to lengthy strings of waypoints incorporating jet routes, in order to improve DWR route acceptability. An approach is developed that can be incorporated into DWR, advising routings with high historical usage and savings potential similar to that of the nominal DWR advisory. It is hypothesized that modifying a nominal DWR routing to one that is commonly used, and nearby, will result in more actual savings since common routings are generally familiar and operationally acceptable to air traffic control. The approach allows routing segments with high historical usage to be concatenated to form routes that meet all DWR constraints. The relevance of a routes historical usage to its acceptance by dispatchers and air traffic control is quantified by analyzing historical DWR data. Results indicate that while historical usage may be less of a concern to flight dispatchers accepting or rejecting DWR advised route corrections, it may be important to air traffic control acceptance of DWR routes.

Operational Acceptability↗

Quality Assurance Surveillance Tool Designed for SLS EM-1 Certificate of Flight Readiness

Exploration Mission-1 (EM-1) is an uncrewed mission that is launching on the Space Launch System (SLS) Block 1 vehicle. This is a critical flight test for the agency's human deep space exploration goals. Exploration Ground Systems (EGS) Quality (SA-F2) is responsible for providing Quality Assurance Surveillance Plans (QASPs) for NASA contracts and facilities. A QASP assures products and services are provided to EGS in accordance with the contract requirements. In order to encapsulate the multiple KSC Safety and Mission Assurance surveillance and audit activities that need to be accomplished specifically for EM-1 Certificate of Flight Reediness (CoFR), a QASP tool needed to be implemented. This tool would be able to intuitively track Work Authorization Documents (WADs) under development by Test Operations Support Contract (TOSC), reviewed and accepted WADs, Government Mandatory Inspection Points (GMIPs), Nonconformances (NCs), Material Review Board (MRB) Status, Corrective Actions, Alterations, Deviations, and Waivers for flight hardware and Ground Support Equipment (GSE). This would help ensure that all SLS EM-1 flight hardware and related GSE surveillances and requirements are being recognized and completed with zero constraints identified for the mission.

Morris, Patrick↗

Building an EPA Class VI Permit Application

Summary To accelerate the commercialization of carbon capture and storage (CCS), the US Department of Energy (US DOE) is building on decades of characterization efforts and pilot-scale projects through their CarbonSAFE program. Administered through their National Energy Technology Laboratory, this program seeks to bring fully integrated projects to the sector that can store more than 50 million tonnes of CO2 over a 30-year period. The program, which was enacted before the enhancement of Internal Revenue Code Section 45Q, is in the capture assessment, characterization, and permitting phase. The objectives of this paper are to discuss (a) the injection permitting requirements of the CarbonSAFE projects; (b) information gathering in support of the permit; (c) the timelines of field development and permit-related activities; (d) the major technical components of the field development plan; and (e) early feedback from the regulators toward acceptance of the permit. In Mississippi, more than 30,000 acres have been characterized by six deep characterization wells, a deep groundwater well, and 92 line miles of 2D seismic as part of the CarbonSAFE Project ECO2S. During the acquisition of seismic data, all receiver lines were live, which resulted in the generation of a pseudo-3D seismic design. The incorporation of a 3D seismic survey was not included as part of this project due to logistical difficulties presented by the undulating, wooded surface terrain. A suite of openhole geophysical logs was taken from each well, allowing for a detailed interpretation of prospective storage reservoirs and confining intervals to complement the analysis carried out on the 290 ft of a whole core that was cut through the prospective confining zone and storage reservoir. The detailed geologic and reservoir data were assembled and entered into a 3D model to assess the injection capacity and the area of review (AoR). This information fed into the detailed corrective action, monitoring, testing, and postinjection site care (PISC) modeling. The results have been exceptional. The geologic assessment has revealed three primary storage targets, ranging in depth from 3,500 ft to 6,000 ft. These storage reservoirs net 1,300 ft of sandstone, with mean porosity and permeability of 29% and 3.6 darcies, respectively. Together, these reservoirs have storage capacities that may exceed 20 million tonnes per square mile, making this a gigatonne prospect. Forward modeling of the project resulted in an AoR of 16 sq miles, injecting about 8000 t/d, for 30 years, via two deep injection wells. The excellent confining characteristics of the caprock, relatively simple geologic structure, and lack of historical well drilling activity in this area provide excellent containment of the injected CO2. Based on this work, the project has proposed 20 years of PISC. To date, only two US CO2 injection permits have been granted. These projects relied on a singular capture point feeding a singular sequestration point (source to sink), and considerations have not been made to garner CO2 emissions from other industrial sources. The Kemper County Storage Complex is a first-of-its-kind storage hub concept that looks to develop an area capable of storing significant quantities of CO2 from the region. Also, this work will show how characterization efforts, geological and numerical modeling efforts, and plan development were constructed in support of permit and incentives acceptance.

Energy & Fuels↗

Post-Closure Inspection Report for the Tonopah Test Range and Nevada Test and Training Range, Nevada for Calendar Year 2020 (Rev. 0)

This report provides the results of the annual post-closure use restriction (UR) inspections at corrective action sites (CASs) located on the Tonopah Test Range (TTR) and Nevada Test and Training Range (NTTR). This report covers post-closure UR inspections for calendar year 2020, and includes visual inspections and repair activities completed at the following corrective action units (CAUs): • CAU 407, Roller Coaster RadSafe Area (TTR) • CAU 424, Area 3 Landfill Complexes (TTR) • CAU 453, Area 9 UXO Landfill (TTR) • CAU 487, Thunderwell Site (TTR). Note: CAU 400, Bomblet Pit and Five Points Landfill (TTR) (CASs TA-19-001-05PT, Ordnance Disposal Pit; and TA-55-00-TAB2, Ordnance Disposal Pit) no longer requires inspection and reporting, as described in the Post-Closure Inspection Report for the Tonopah Test Range and Nevada Test and Training Range, Nevada for Calendar Year 2019. Site figures are included in Appendix A. The Post-Closure Inspection Plans and Record of Technical Change modifying the requirements for each UR are included in Appendix B. The Post-Closure Inspection Checklists are included in Appendix C. Field Notes are included in Appendix D. Appendix E, Inspection Photographs, does not include photographs because none were taken during the 2020 post-closure inspections. Appendix F, Post-Closure Vegetation Monitoring Report, does not include any data because vegetation monitoring was not conducted or required at any CAU in 2020. Visual inspections were conducted according to the post-closure requirements outlined in specific CAU and CAS URs, and approved by NDEP. The annual post-closure inspections for CASs associated with CAUs 407, 424, 453, and 487 were conducted on May 20, 2020. No maintenance or repair issues were noted at CAUs 487, or at CASs associated with CAU 424 (except CASs 03-08-002-A304 and 03-08-002-A308). Maintenance items and subsequent repairs include the following: • CAU 407, CAS TA-23-001-TARC (Roller Coaster RadSafe Area): A UR sign was loose and was rehung during the inspection. • CAU 424, CAS 03-08-002-A304 (Landfill Cell A3-4): The northeast monument needed a UR sign. The UR sign was attached to the monument on August 11, 2020. • CAU 424, CAS 03-08-002-A308 (Landfill Cell A3-8): The southeast monument needed additional lava rock. The lava rock was added during the inspection. • CAU 453, CAS 09-55-001-0952 (Area 9 Landfill): Two animal burrows were noted in the western portion of the northern and southern trenches (one burrow per trench). The animal burrows were repaired on August 11, 2020.

54 ENVIRONMENTAL SCIENCES↗

A framework for integrating supply chain, environmental, and social justice factors during early stationary battery research

The transition to a decarbonized economy will drive dramatically higher demand for energy storage, along with technological diversification. To avoid mistakes of the past, the supply chain implications and environmental and social justice (ESJ) impacts of new battery technologies should be considered early during technological development. We propose herein a systematic framework for analyzing these impacts for new stationary battery technologies and illustrate the framework with a case study. The goal is to promote future development of technologies with secure supply chains and favorable ESJ profiles to avoid expensive corrective actions after substantial resources have been invested. This framework should be a useful tool for public and private researchers and sponsors who want to ensure that supply chain and ESJ concerns are considered and integrated as part of decision making throughout the research and development process.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Components Cleaning Facility, SWMU 030 Eastern High-Concentration Plume Area Implementation Work Plan Kennedy Space Center, Florida

This Implementation Work Plan (IWP) presents detailed design elements and coordination specifics to implement an air sparging (AS) Interim Measure (IM) to remediate groundwater at the Components Cleaning Facility (CCF), Eastern High Concentration Plume (HCP) Area located at Kennedy Space Center (KSC), Florida. The objective of the CCF East IM is to remediate groundwater where trichloroethene, cis-1,2-dichloroethene, and vinyl chloride concentrations exceed Florida Department of Environmental Protection Natural Attenuation Default Criteria (NADC) (identified as the HCP) via AS and to transition to monitored natural attenuation. CCF has been designated Solid Waste Management Unit 030 under KSC’s Resource Conservation and Recovery Act Corrective Action Program.

James Lloyd↗