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At least 73 records · Page 4

Functional Coordination of a Full-Body Gaze Control Mechanisms Elicited During Locomotion

Control of locomotion requires precise interaction between several sensorimotor subsystems. Exposure to the microgravity environment of spaceflight leads to postflight adaptive alterations in these multiple subsystems leading to postural and gait disturbances. Countermeasures designed to mitigate these postflight gait alterations will need to be assessed with a new generation of functional tests that evaluate the interaction of various elements central to locomotor control. The goal of this study is to determine how the multiple, interdependent, full- body sensorimotor subsystems aiding gaze stabilization during locomotion are functionally coordinated. To explore this question two experiments were performed. In the first study (Study 1) we investigated how alteration in gaze tasking changes full-body locomotor control strategies. Subjects (n=9) performed two discreet gaze stabilization tasks while walking at 6.4 km/hr on a motorized treadmill: 1) focusing on a central point target; 2) reading numeral characters; both presented at 2m in front at eye level. The second study (Study 2) investigated the potential of adaptive remodeling of the full-body gaze control systems following exposure to visual-vestibular conflict. Subjects (n=14) walked (6.4 km/h) on the treadmill before and after they were exposed to 0.5X minifying lenses worn for 30 minutes during self-generated sinusoidal vertical head rotations performed while seated. In both studies we measured: temporal parameters of gait, full body sagittal plane segmental kinematics of the head, trunk, thigh, shank and foot, accelerations along the vertical axis at the head and the shank, and the vertical forces acting on the support surface. Results from Study 1 showed that while reading numeral characters as compared to the central point target: 1) compensatory head pitch movements were on average 22% greater 2) the peak acceleration measured at the head was significantly reduced by an average of 13% in four of the six subjects 3) the knee joint total movement was on average 11% greater during the period from the heel strike event to the peak knee flexion event in stance phase of the gait cycle. Results from Study 2 indicate that following exposure to visual-vestibular conflict changes in full-body strategies were observed consistent with the requirement to aid gaze stabilization during locomotion.

Bloomberg, Jacob J.↗

A Modified Delphi Method to Accelerate Consensus Building in Expert Judgment Elicitation

The 2017 Earth Science Decadal Survey recommends the implementation of a novel Earth Observing mission to study Aerosols, Clouds, Convection, and Precipitation. The assessment of the candidate architectures under consideration requires the use of Expert Judgment Elicitation. Some of the assessment scores are obtained through consensus among the Science Leadership Team. A modified Delphi method was developed to accelerate the consensus building process and reduce the number of cycles required to converge. This paper discusses which elements of the traditional method were modified, how the method was applied, and the impact of the modifications on generating consensus.

Expert Judgement↗

A Modified Delphi Method to Accelerate Consensus Building in Expert Judgment Elicitation

The 2017 Earth Science Decadal Survey recommends the implementation of a novel Earth Observing mission to study Aerosols, Clouds, Convection, and Precipitation. The assessment of the candidate architectures under consideration requires the use of Expert Judgment Elicitation. Some of the assessment scores are obtained through consensus among the Science Leadership Team. A modified Delphi method was developed to accelerate the consensus building process and reduce the number of cycles required to converge. This paper discusses which elements of the traditional method were modified, how the method was applied, and the impact of the modifications on generating consensus.

Expert Judgment↗

Exploring Requirements for Software that Learns: A Research Preview

Context & motivation: The development of software that learns has revolutionized how many systems perform. For the most part, these systems are neither safety- nor mission-critical. However, as technology and aspirations advance, there is an increased desire and need for Machine Learning (ML) software in safety- and mission-critical systems, e.g., driverless cars or autonomous space robotics. Problem: In these domains, reliability is crucial and systems have to undergo much scrutiny in terms of both the developed artefacts and the adopted development process. Central to the development of such systems is the elicitation and definition of software requirements that are used to guide the design and verification process. The addition of software components that learn, and the associated capability for unforeseen behavior, makes defining detailed software requirements especially difficult. Principal ideas/results: In this paper, we identify unique characteristics of software requirements that are specific to ML components. To this end, we collect and examine requirements from both academic and industrial sources. Contribution: To the best of our knowledge, this is the first work that presents real-life, industrial patterns of requirements for ML components. Furthermore, this paper identifies key characteristics and provides a foundation for developing a taxonomy of requirements for software that learns.

Probabilistic requirements↗

Immunization of cows with HIV envelope trimers generates broadly neutralizing antibodies to the V2-apex from the ultralong CDRH3 repertoire

The generation of broadly neutralizing antibodies (bnAbs) to conserved epitopes on HIV Envelope (Env) is one of the cornerstones of HIV vaccine research. The animal models commonly used for HIV do not reliably produce a potent broadly neutralizing serum antibody response, with the exception of cows. Cows have previously produced a CD4 binding site response by homologous prime and boosting with a native-like Env trimer. In small animal models, other engineered immunogens were shown to focus antibody responses to the bnAb V2-apex region of Env. Here, we immunized two groups of cows (n = 4) with two regimens of V2-apex focusing Env immunogens to investigate whether antibody responses could be generated to the V2-apex on Env. Group 1 was immunized with chimpanzee simian immunodeficiency virus (SIV)-Env trimer that shares its V2-apex with HIV, followed by immunization with C108, a V2-apex focusing immunogen, and finally boosted with a cross-clade native-like trimer cocktail. Group 2 was immunized with HIV C108 Env trimer followed by the same HIV trimer cocktail as Group 1. Longitudinal serum analysis showed that one cow in each group developed serum neutralizing antibody responses to the V2-apex. Eight and 11 bnAbs were isolated from Group 1 and Group 2 cows, respectively, and showed moderate breadth and potency. Potent and broad responses in this study developed much later than previous cow immunizations that elicited CD4bs bnAbs responses and required several different immunogens. All isolated bnAbs were derived from the ultralong CDRH3 repertoire. The finding that cow antibodies can target more than one broadly neutralizing epitope on the HIV surface reveals the generality of elongated structures for the recognition of highly glycosylated proteins. The exclusive isolation of ultralong CDRH3 bnAbs, despite only comprising a small percent of the cow repertoire, suggests these antibodies outcompete the long and short CDRH3 antibodies during the bnAb response.

Microbiology↗

A systems engineering approach to automated failure cause diagnosis in space power systems

Automatic failure-cause diagnosis is a key element in autonomous operation of space power systems such as Space Station's. A rule-based diagnostic system has been developed for determining the cause of degraded performance. The knowledge required for such diagnosis is elicited from the system engineering process by using traditional failure analysis techniques. Symptoms, failures, causes, and detector information are represented with structured data; and diagnostic procedural knowledge is represented with rules. Detected symptoms instantiate failure modes and possible causes consistent with currently held beliefs about the likelihood of the cause. A diagnosis concludes with an explanation of the observed symptoms in terms of a chain of possible causes and subcauses.

Dolce, James L.↗

Let’s speak FRETish

FRET (https://github.com/NASA-SW-VnV/fret [github.com]) is a framework for the elicitation, formalization and analysis of requirements. FRET allows its user to enter requirements in a structured natural language called FRETish. Requirements written in FRETish are assigned unambiguous semantics. FRET supports its users in understanding this semantics and repairing requirements if applicable, by utilizing a variety of forms for each requirement: natural language description, formal mathematical logics, diagrams, and interactive simulation. FRET exports requirements into forms that can be used by a variety of analysis tools, including state-of-the-art model checkers and runtime monitoring tools. The talk will cover some of the theory behind the framework, present case studies from the aerospace and robotics domains, as well as current work on extending FRET for specifying requirements for software that learns.

FRET↗

Identifying Cognitive Capabilities Required for Optimal Exploration EVA Performance: A Cognitive Task Analysis

BACKGROUND Extravehicular activity (EVA) is one of the most dangerous and cognitively demanding actions that astronauts can execute, and the cognitive demands associated with future exploration EVA on the Moon and Mars are expected to be higher compared to EVA currently conducted from the International Space Station (ISS). Decrements in cognitive performance present an important risk to crew safety during exploration mission class EVA. Yet there is currently insufficient characterization of the cognitive capabilities required prior to, during, and following EVA. Furthermore, it is unclear which cognitive domains are most important for conducting mission critical decisions with crew safety implications. To address this gap, we conducted a cognitive task analysis of exploration EVA to characterize the cognitive capabilities, critical safety decisions, and contributing factors (e.g., lunar communications delay) important to monitor for optimal performance in future exploration EVA. This cognitive task analysis was conducted through interviews with astronauts and subject matter experts in EVA research and operations. Interviews focused on exploration EVA and elicited feedback on the cognitive capabilities required for specific EVA tasks and subtasks. The information from this cognitive task analysis will help close the gap in our understanding of the key cognitive capabilities required for safe decision-making during exploration mission class EVA on the Moon and Mars. METHOD We used an applied cognitive task analysis method1 over the course of interviews with a total of 15 NASA astronauts and subject matter experts in EVA. Each interview was led by a scientist with expertise in cognitive neuroscience from the Behavioral Health & Performance (BHP) Laboratory at NASA Johnson Space Center. Notes were taken by a research coordinator in the BHP Laboratory and interviews were recorded on Microsoft Teams to ensure the accuracy of notetaking. In the first interview protocol, participants were asked about the specific tasks and cognitive demands associated with EVA. This provided a high-level overview of the steps involved in the major tasks conducted during exploration EVA, as well as which of the steps require the most cognitive skill. Next, participants completed a knowledge audit, which employs a set of probes designed to describe types of domain knowledge of skill and elicit appropriate examples. In the second interview protocol, completed with a separate set of subject matter experts, interviewees were asked to complete a simulated incapacitated crew rescue (ICR) scenario2, which provided specific context that allowed probing around relevant issues such as situational awareness and potential errors. Experts were then asked to identify the knowledge, skills, and abilities (KSAs) underlying each EVA task and to provide ratings on the importance and cognitive demand of each KSA. Finally, participants also described the most likely and consequential critical safety incidents related to decrements in cognitive performance during exploration EVA and assessed the impact of lunar communication delay on cognitive performance. RESULTS & DISCUSSION Interviews for this cognitive task analysis are nearly complete and results will be presented in full at IWS 2025. Results will include a summary of all expert ratings of EVA tasks and subtasks, qualitative summaries of content from each interview part, and a discussion of future directions for products addressing cognitive performance monitoring and cognitive domain mapping in exploration EVA.

S R Anderson↗

The Making of a Metric: Co-Producing Decision-Relevant Climate Science

Developing decision-relevant science for adaptation requires the identification of climatic parameters that are both actionable for practitioners as well as tractable for modelers. In many sectors, these decision-relevant climatic metrics and the approaches that enable their identification remain largely unknown. “Co-production” of science with scientists and decision-makers is one potential way to identify these metrics, but there is little research describing specific and successful co-production approaches. This paper examines the negotiations and outcomes from Project Hyperion, wherein scientists and water managers jointly developed decision-relevant climatic metrics for adaptive water management. We identify successful co-production strategies by analyzing the project’s numerous back-and-forth engagements and tracing the evolution of the science during these engagements. We found that effective mediation between scientists and managers needed dedicated “boundary spanners” with significant modeling expertise. Translating practitioners’ information needs into tractable climatic metrics required direct and indirect methods of eliciting knowledge. We identified four indirect methods that were particularly salient for extracting tacitly held knowledge and enabling shared learning: developing a hierarchical framework linking management issues with metrics, starting discussions from the planning challenges, collaboratively exploring the planning relevance of new scientific capabilities, and using analogies of other “good” metrics. The decision-relevant metrics we developed provide insights into advancing adaptation-relevant climate science in the water sector. The co-production strategies we identified can be used to design and implement productive scientist–decision-maker interactions. Overall, the approaches and metrics we developed can help climate science to expand in new and more use-inspired directions.

Planning↗

Adaptive Stress Testing of Collision Avoidance Systems for Small UASs with Deep Reinforcement Learning

The next-generation Airborne Collision Avoidance System for smaller UASs (ACAS sXu) is currently being developed and tested by the Federal Aviation Administration (FAA) to provide detect-and-avoid capability for small unmanned aircraft operating beyond line-of-sight. Due to the complexity and safety-critical nature of the system, safety validation is important not only for the certification of the final system, but also for informing changes during the iterative development process. In this paper, we analyze a prototype of ACAS sXu in simulated aircraft encounters to discover scenarios of small near mid-air collisions (sNMACs), an important safety event in which two aircraft come closer than 50 feet horizontally and 15 feet vertically. Due to the size and complexity of the system as well as rarity of sNMAC events, traditional methods such as Monte Carlo testing often require informed setup and targeting to elicit failures. However, such a dependence on domain knowledge can be incompatible with the independent verification and validation (IV&V) process, the aim of which is to discover unforeseen issues. To address these challenges, we apply an accelerated validation method called adaptive stress testing (AST) to find the most likely sNMAC scenarios without reliance on system introspection. AST uses reinforcement learning to adapt the search towards the most promising areas of the search space as it progresses. We use a state-of-the-art deep reinforcement learning algorithm, proximate policy optimization, to more efficiently search the large and continuous state space. We find that this approach significantly improves the performance of AST compared to a prior approach based on Monte Carlo tree search. We perform experiments using AST to find sNMAC events under various encounter configurations, varying parameters pertaining to dynamics and coordination. Our experiments show AST to be very effective at finding sNMAC scenarios. We summarize our findings, presenting high-level categories of discovered sNMACs and specific examples of encounters in each category.

aircraft collision avoidance↗

Ensuring Safe Decision-Making on the Moon and Mars: Cognitive Performance Assessment for Exploration Class Mission EVA

Extravehicular activity (EVA) is one of the most dangerous and cognitively demanding actions that astronauts can execute, and the cognitive demands associated with future partial gravity EVAs on the Moon and Mars are expected to be higher compared to microgravity EVAs currently conducted from the International Space Station. Decrements in cognitive performance present an important risk to crew safety during exploration mission class EVA. Yet there is currently insufficient data to characterize cognitive performance prior to, during, and following EVA. Furthermore, it is still unclear which cognitive domains are most important for conducting mission critical decisions with crew safety implications. To address this gap, we conducted a cognitive task analysis (CTA) of EVA to characterize the procedures, the cognitive demands required, and the critical safety decisions associated with decrements in cognitive performance. We conducted a cognitive task analysis with 15 astronauts and subject matter experts in EVA operations and research. Interviews focused on surface exploration EVA and elicited feedback from experts on the cognitive skills required for specific EVA tasks, including cognitive strategies, critical cues, and decision-making strategies. A cognitive demands table was assembled to consolidate and synthesize the information from all interviews. The information from this cognitive task analysis informs ongoing exploration EVA for Moon to Mars. This work identifies the specific cognitive challenges that astronauts are likely to encounter during surface exploration EVA, and provides the foundation for: (1) prioritized and targeted cognitive performance measurement and functional performance tests, (2) EVA simulation design at varying levels of cognitive workload, and (3) the development of training and other technologies that can improve safe decision-making and inform EVA planning on future spaceflight missions to the Moon and Mars.

Steven R Anderson↗

The Ten Lockheed Martin Cyber-Physical Challenges: Formalized, Analyzed, and Explained

Capturing and analyzing requirements of Cyber-Physical Systems (CPS) can be challenging, since CPS models typically involve time-varying and real-valued variables, physical system dynamics, or even adaptive behavior. MATLAB/Simulinkis a development and simulation framework that is widely used in industry to capture such systems. In this paper, we report on the application of NASA Ames tools to perform end-to-end analysis of the Ten Lockheed Martin Challenge Problems (LMCPS). LMCPS is a set of industrial Simulink model benchmarks and natural language requirements developed by domain experts. Our framework, which integrates the tools FRET and COCOSIM, is used to: 1) elicit, explain, and formalize the semantics of the given natural language requirements; 2) generate verification code and monitors that can be automatically attached to the Simulink models; 3) perform verification by using SMT-based model checkers. FRET and COCOSIM are open source, and can be used by other researchers and practitioners to replicate our case study. We provide a categorization of recurring patterns in the formalization of the requirements and discuss the strengths and weaknesses of our automated verification approach.

Anastasia Mavridou↗

Ensuring Safe Decision-Making on the Moon and Mars: Cognitive Performance Assessment for Exploration Class Mission EVA

Extravehicular activity (EVA) is one of the most dangerous and cognitively demanding actions that astronauts can execute, and the cognitive demands associated with future partial gravity EVA on the Moon and Mars are expected to be higher compared to microgravity EVA currently conducted from the International Space Station (ISS). Decrements in cognitive performance present an important risk to crew safety during exploration mission class EVA. Yet there is currently insufficient data to characterize cognitive performance prior to, during, and following EVA. Furthermore, it is still unclear which cognitive domains are most important for conducting mission critical decisions with crew safety implications. To address this gap, we conducted a cognitive task analysis (CTA) of EVA to characterize the procedures, the cognitive demands required, and the critical safety decisions associated with decrements in cognitive performance. We used the applied cognitive task analysis method as outlined by Militello and Hutton (1998) and conducted interviews with subject matter experts (SMEs) in EVA at NASA Johnson Space Center in summer 2024. Interviews focused on exploration EVA and elicited feedback from SMEs on the cognitive skills required for specific EVA tasks including cognitive strategies, critical cues, and decision-making strategies. A cognitive demands table was assembled to consolidate and synthesize the information from all interviews. The information from this cognitive task analysis will inform ongoing work to identify the key cognitive domains for safe decision-making during exploration mission class EVA on the Moon and Mars. This work will importantly provide a link between cognitive domains identified in the cognitive task analysis and operationally-relevant performance metrics collected during spaceflight and simulation EVA that can be tracked and assessed by NASA mission operations. Ultimately, this work will aid in the development and application of exploration class cognitive performance monitoring capabilities to improve safe decision-making and inform EVA planning on future spaceflight missions to the Moon and Mars.

Steven R Anderson↗

A Biomechanical Comparison of 1-G and Fully-Loaded Simulated Zero-Gravity Locomotion

Exercise will almost certainly play an integral part in minimizing the bone mineral loss and muscular atrophy that occur during spaceflight. It has been hypothesized that an effective exercise regimen can be developed to elicit loads on the lower extremities and require muscle actions which resemble those encountered on Earth. The Penn State Zero-Gravity Simulator (PSZS) is a device which suspends subjects horizontally from multiple latex cords, with each cord negating the weight of a limb segment. A treadmill mounted on the wall under the PSZS enables subjects to run in simulated 0G. Subjects wear a harness to which a number of springs, which provide a gravity replacement load, are connected. The opposite end of each spring is connected to the side of the treadmill. During exercise, astronauts currently wear a similar harness in which the spring tethering load pulls at both the waist and shoulders. Ground reaction forces, muscular activations, and joint angles of the left leg during overground, treadmill, and fully-loaded zero-gravity simulated (ZLS) locomotion were assessed in order to gain insight into the effectiveness of the exercise regimen used by NASA to prevent the muscular atrophy and bone demineralization which occur in weightlessness. There were three hypotheses to this research. It was hypothesized that there will be no differences in peak ground reaction forces and peak loading rates between overground gait and gait in the full body weight loaded conditions in the ZLS. A second hypothesis was that that there will be no differences in hip, knee, and ankle joint positions between walking or running overground, on a standard treadmill, and in full bodyweight loaded conditions in the ZLS. The third hypothesis was that the muscular activations, as a percentage of maximal voluntary contraction, will be similar between walking or running overground, on a standard treadmill, and in full body-weight loaded conditions in the ZLS.

McCrory, Jean L.↗

Primate translational vestibuloocular reflexes. II. Version and vergence responses to fore-aft motion

To maintain binocular fixation on near targets during fore-aft translational disturbances, largely disjunctive eye movements are elicited the amplitude and direction of which should be tuned to the horizontal and vertical eccentricities of the target. The eye movements generated during this task have been investigated here as trained rhesus monkeys fixated isovergence targets at different horizontal and vertical eccentricities during 10 Hz fore-aft oscillations. The elicited eye movements complied with the geometric requirements for binocular fixation, although not ideally. First, the corresponding vergence angle for which the movement of each eye would be compensatory was consistently less than that dictated by the actual fixation parameters. Second, the eye position with zero sensitivity to translation was not straight ahead, as geometrically required, but rather exhibited a systematic dependence on viewing distance and vergence angle. Third, responses were asymmetric, with gains being larger for abducting and downward compared with adducting and upward gaze directions, respectively. As frequency was varied between 4 and 12 Hz, responses exhibited high-pass filter properties with significant differences between abduction and adduction responses. As a result of these differences, vergence sensitivity increased as a function of frequency with a steeper slope than that of version. Despite largely undercompensatory version responses, vergence sensitivity was closer to ideal. Moreover, the observed dependence of vergence sensitivity on vergence angle, which was varied between 2.5 and 10 MA, was largely linear rather than quadratic (as geometrically predicted). We conclude that the spatial tuning of eye velocity sensitivity as a function of gaze and viewing distance follows the general geometric dependencies required for the maintenance of foveal visual acuity. However, systematic deviations from ideal behavior exist that might reflect asymmetric processing of abduction/adduction responses perhaps because of different functional dependencies of version and vergence eye movement components during translation.

NASA Program Biomedical Research and Countermeasur↗

Full-Body Gaze Control Mechanisms Elicited During Locomotion: Effects Of VOR Adaptation

Control of locomotion requires precise interaction between several sensorimotor subsystems. During locomotion the performer must satisfy two performance criteria: maintain stable forward translation and to stabilize gaze (McDonald, et al., 1997). Precise coordination demands integration of multiple sensorimotor subsystems for fulfilling both criteria. In order to test the general hypothesis that the whole body can serve as an integrated gaze stabilization system, we have previously investigated how the multiple, interdependent full-body sensorimotor subsystems respond to changes in gaze stabilization task constraints during locomotion (Mulavara and Bloomberg, 2003). The results suggest that the full body contributes to gaze stabilization during locomotion, and that its different functional elements respond to changes in visual task constraints. The goal of this study was to determine how the multiple, interdependent, full-body sensorimotor subsystems aiding gaze stabilization during locomotion are functionally coordinated after the vestibulo-ocular reflex (VOR) gain has been altered. We investigated the potential of adaptive remodeling of the full-body gaze control system following exposure to visual-vestibular conflict known to adaptively reduce the VOR. Subjects (n=14) walked (6.4 km/h) on the treadmill before and after they were exposed to 0.5X manifying lenses worn for 30 minutes during self-generated sinusoidal vertical head rotations performed while seated. In this study we measured: temporal parameters of gait, full body sagittal plane segmental kinematics of the head, trunk, thigh, shank and foot, accelerations along the vertical axis at the head and the shank, and the vertical forces acting on the support surface. Results indicate that, following exposure to the 0.5X minifying lenses, there was a significant increase in the duration of stance and stride times, alteration in the amplitude of head movement with respect to space and a significant increase in the amount of knee flexion during the initial stance phase of the gait cycle. This study provides further evidence that the full body contributes to gaze stabilization during locomotion, and that different functional elements are responsive to changes in visual task constraints and are subject to adaptive alteration following exposure to visual-vestibular conflict.

Mulavara, A. P.↗

Loudness changes resulting from an electrically induced middle-ear reflex.

An experiment was conducted in order to determine the changes in loudness brought about by electro-cutaneous elicitation of the middle-ear reflex. Subjects were required to judge the relative loudness of the second of three consecutive 30-msec bursts of tone, the second tone being accompanied by an electrical shock to the external auditory meatus, capable of eliciting a contraction of the middle-ear muscles. The difference between these judgments and those of the control condition (shock on the arm) was taken to represent a measure of the attenuation provided by contraction of the middle-ear muscles. Test tones were 500, 1000, 2000, and 3000 Hz at levels of 65, 75, 85, 95, and 105 dB. The results indicate that the middle-ear reflex decreases the middle-ear's transmission mainly for low-frequency sounds. The results fail to lend support to the Loeb-Riopelle hypothesis that the middle-ear reflex acts as a limiter, rather than a linear attenuator.

Gunn, W. J.↗

Wabash CarbonSAFE Subtask 4.1 - Application of Policy Frameworks for Improved Carbon Capture and Storage Social Site Characterization & Stakeholder Engagement

Anthropogenic climate change threatens environmental and human health globally. Limiting these threats requires large-scale and innovative greenhouse gas mitigation responses across carbon-intensive energy and industrial sectors. Carbon capture and storage (CCS) technologies present potential opportunities for mitigating climate change while maintaining a diverse energy resource portfolio. Successful development of CCS physical sites requires effective and efficient project management solutions that elicit and incorporate the concerns and perspectives of diverse stakeholders. Due to the urgency of climate change mitigation technology implementation and the costs of CCS development, CCS project developers cannot risk setbacks by poor stakeholder assessment that concern management processes. Thus, this report presents four prominent policy frameworks and associated case studies as opportunities to improve CCS social site characterization and stakeholder engagement. After comparing the relative effectiveness and efficiencies of each framework with regard to CCS, this report concludes that the Advocacy Coalition Framework, Narrative Policy Framework, and Policy Conflict Framework can improve the CCS social site characterization process, while the Collaborative Governance Framework paired with the Q-Methodology provides an ideal framework for direct stakeholder engagement. Overall, this report finds that the Narrative Policy Framework and the Collaborative Governance Framework are most ideally suited for the purposes of CCS social site characterization and stakeholder engagement.

01 COAL, LIGNITE, AND PEAT↗