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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2016

Marshall Space Flight Center Telescience Resource Kit

Telescience Resource Kit (TReK) is a suite of software applications that can be used to monitor and control assets in space or on the ground. The Telescience Resource Kit was originally developed for the International Space Station program. Since then it has been used to support a variety of NASA programs and projects including the WB-57 Ascent Vehicle Experiment (WAVE) project, the Fast Affordable Science and Technology Satellite (FASTSAT) project, and the Constellation Program. The Payloads Operations Center (POC), also known as the Payload Operations Integration Center (POIC), provides the capability for payload users to operate their payloads at their home sites. In this environment, TReK provides local ground support system services and an interface to utilize remote services provided by the POC. TReK provides ground system services for local and remote payload user sites including International Partner sites, Telescience Support Centers, and U.S. Investigator sites in over 40 locations worldwide. General Capabilities: Support for various data interfaces such as User Datagram Protocol, Transmission Control Protocol, and Serial interfaces. Data Services - retrieve, process, record, playback, forward, and display data (ground based data or telemetry data). Command - create, modify, send, and track commands. Command Management - Configure one TReK system to serve as a command server/filter for other TReK systems. Database - databases are used to store telemetry and command definition information. Application Programming Interface (API) - ANSI C interface compatible with commercial products such as Visual C++, Visual Basic, LabVIEW, Borland C++, etc. The TReK API provides a bridge for users to develop software to access and extend TReK services. Environments - development, test, simulations, training, and flight. Includes standalone training simulators.

Wade, Gina↗
NASA NTRS2008

The Telesupervised Adaptive Ocean Sensor Fleet (TAOSF) Architecture: Coordination of Multiple Oceanic Robot Boats

Earth science research must bridge the gap between the atmosphere and the ocean to foster understanding of Earth s climate and ecology. Ocean sensing is typically done with satellites, buoys, and crewed research ships. The limitations of these systems include the fact that satellites are often blocked by cloud cover, and buoys and ships have spatial coverage limitations. This paper describes a multi-robot science exploration software architecture and system called the Telesupervised Adaptive Ocean Sensor Fleet (TAOSF). TAOSF supervises and coordinates a group of robotic boats, the OASIS platforms, to enable in-situ study of phenomena in the ocean/atmosphere interface, as well as on the ocean surface and sub-surface. The OASIS platforms are extended deployment autonomous ocean surface vehicles, whose development is funded separately by the National Oceanic and Atmospheric Administration (NOAA). TAOSF allows a human operator to effectively supervise and coordinate multiple robotic assets using a sliding autonomy control architecture, where the operating mode of the vessels ranges from autonomous control to teleoperated human control. TAOSF increases data-gathering effectiveness and science return while reducing demands on scientists for robotic asset tasking, control, and monitoring. The first field application chosen for TAOSF is the characterization of Harmful Algal Blooms (HABs). We discuss the overall TAOSF architecture, describe field tests conducted under controlled conditions using rhodamine dye as a HAB simulant, present initial results from these tests, and outline the next steps in the development of TAOSF.

sensor web↗
NASA NTRS2012

Integrating High-Resolution Taskable Imagery into a Sensorweb for Automatic Space-Based Monitoring of Flooding in Thailand

Several space-based assets (Terra, Aqua, Earth Observing One) have been integrated into a sensorweb to monitor flooding in Thailand. In this approach, the Moderate Imaging Spectrometer (MODIS) data from Terra and Aqua is used to perform broad-scale monitoring to track flooding at the regional level (250m/pixel) and EO-1 is autonomously tasked in response to alerts to acquire higher resolution (30m/pixel) Advanced Land Imager (ALI) data. This data is then automatically processed to derive products such as surface water extent and volumetric water estimates. These products are then automatically pushed to organizations in Thailand for use in damage estimation, relief efforts, and damage mitigation. More recently, this sensorweb structure has been used to request imagery, access imagery, and process high-resolution (several m to 30m), targetable asset imagery from commercial assets including Worldview-2, Ikonos, Radarsat-2, Landsat-7, and Geo-Eye-1. We describe the overall sensorweb framework as well as new workflows and products made possible via these extensions.

sensorweb operations↗
NASA NTRS2006

Transforming Our SMEX Organization by Way of Innovation, Standardization, and Automation

NASA's Small Explorer (SMEX) Flight Operations Team (FOT) is currently tackling the challenge of supporting ground operations for several satellites that have surpassed their designed lifetime and have a dwindling budget. At Goddard Space Flight Center (GSFC), these missions are presently being reengineered into a fleet-oriented ground system. When complete, this ground system will provide command and control of four SMEX missions, and will demonstrate fleet automation and control concepts as a pathfinder for additional mission integrations. A goal of this reengineering effort is to demonstrate new ground-system technologies that show promise of supporting longer mission lifecycles and simplifying component integration. In pursuit of this goal, the SMEX organization has had to examine standardization, innovation, and automation. A core technology being demonstrated in this effort is the GSFC Mission Services Evolution Center (GMSEC) architecture. The GMSEC architecture focuses on providing standard interfaces for ground system applications to promote application interoperability. Building around commercial Message Oriented Middleware and providing a common messaging standard allows GMSEC to provide the capabilities necessary to support integration of new software components into existing missions and increase the level of interaction within the system. For SMS, GMSEC has become the technology platform to transform flight operations with the innovation and automation necessary to reduce operational costs. The automation technologies supported in SMEX are built upon capabilities provided by the GMSEC architecture that allows the FOT to further reduce the involvement of the console, operator. Initially, SMEX is automating only routine operations, such as safety and health monitoring, basic commanding, and system recovery. The operational concepts being developed here will reduce the need for staffed passes and are a necessity for future fleet management. As this project continues to evolve, additional innovations beyond GMSEC and automation have, and will continue to be developed. The team developed techniques for migrating ground systems of existing on-orbit assets. The tools necessary to monitor and control software failures were integrated and tailored for operational environments. All this was done with a focus of extending fleet operations to mission beyond SMU. The result of this work is the foundation for a broader fleet-capable ground system that will include several missions supported by the Space Science Mission Operations Project.

Madden, Maureen↗
NASA NTRS2007

Small Satellite Constellations: The Future for Operational Earth Observation

Nanosat, microsat and minisat are low-cost, rapid-response small-satellites built from advanced terrestrial technology. SSTL delivers the benefits of affordable access to space through low-cost, rapid response, small satellites designed and built with state-of-the-art COTS technologies by: a) reducing the cost of entry into space; b) Achieving more missions within fixed budgets; c) making constellations and formation flying financially viable; d) responding rapidly from initial concept to orbital operation; and e) bringing the latest industrial COTS component advances to space. Growth has been stimulated in constellations for high temporal revisit&persistent monitoring and military responsive space assets.

Stephens, J. Paul↗
NASA NTRS2005

Surveillance system and method having parameter estimation and operating mode partitioning

A system and method for monitoring an apparatus or process asset including creating a process model comprised of a plurality of process submodels each correlative to at least one training data subset partitioned from an unpartitioned training data set and each having an operating mode associated thereto; acquiring a set of observed signal data values from the asset; determining an operating mode of the asset for the set of observed signal data values; selecting a process submodel from the process model as a function of the determined operating mode of the asset; calculating a set of estimated signal data values from the selected process submodel for the determined operating mode; and determining asset status as a function of the calculated set of estimated signal data values for providing asset surveillance and/or control.

Bickford, Randall L.↗
NASA NTRS2003

Surveillance system and method having parameter estimation and operating mode partitioning

A system and method for monitoring an apparatus or process asset including partitioning an unpartitioned training data set into a plurality of training data subsets each having an operating mode associated thereto; creating a process model comprised of a plurality of process submodels each trained as a function of at least one of the training data subsets; acquiring a current set of observed signal data values from the asset; determining an operating mode of the asset for the current set of observed signal data values; selecting a process submodel from the process model as a function of the determined operating mode of the asset; calculating a current set of estimated signal data values from the selected process submodel for the determined operating mode; and outputting the calculated current set of estimated signal data values for providing asset surveillance and/or control.

Bickford, Randall L.↗
NASA NTRS2021

ICESat-2 Constraint Analysis and Monitoring System (CAMS)

The Ice, Cloud and land Elevation Satellite-2 was launched on 15 September 2018 with mission goals of collecting surface elevation data that can precisely measure ice sheet topography, cloud and aerosol heights, land topography, as well as vegetation height for ecosystems studies. The Constraint Analysis and Monitoring System (CAMS) was implemented as an ICESat-2 ground system element to perform Mission Planning and Spacecraft Safety Monitoring. Mission Planning requires CAMS to serve as an interface between the Project Science Office, the Instrument Support Facility and the Mission Operation Control Center. By ingesting inputs received from all three groups, the CAMS builds an optimized and deconflicted timeline of science and instrument activities. Based upon the timeline of activities, the CAMS utilizes a sophisticated set of algorithms to model and predict the location and pointing of the spacecraft instrument relative to the Earth and Sun. From the predicted position and pointing, the CAMS provides precise monitoring of instrument health, and performs space asset laser conjunction detection. Furthermore, the CAMS determines alternative plans to prevent detected health constraint violations or mitigate potential laser conjunctions. This paper provides an overview of the CAMS and presents the operational performance of planning science and instrument activities, the monitoring of instrument constraints for health and safety, and the space asset laser conjunction screening and mitigation process.

ICESat-2↗
NASA NTRS2012

Telerobotics Workstation (TRWS) for Deep Space Habitats

On medium- to long-duration human spaceflight missions, latency in communications from Earth could reduce efficiency or hinder local operations, control, and monitoring of the various mission vehicles and other elements. Regardless of the degree of autonomy of any one particular element, a means of monitoring and controlling the elements in real time based on mission needs would increase efficiency and response times for their operation. Since human crews would be present locally, a local means for monitoring and controlling all the various mission elements is needed, particularly for robotic elements where response to interesting scientific features in the environment might need near- instantaneous manipulation and control. One of the elements proposed for medium- and long-duration human spaceflight missions, the Deep Space Habitat (DSH), is intended to be used as a remote residence and working volume for human crews. The proposed solution for local monitoring and control would be to provide a workstation within the DSH where local crews can operate local vehicles and robotic elements with little to no latency. The Telerobotics Workstation (TRWS) is a multi-display computer workstation mounted in a dedicated location within the DSH that can be adjusted for a variety of configurations as required. From an Intra-Vehicular Activity (IVA) location, the TRWS uses the Robot Application Programming Interface Delegate (RAPID) control environment through the local network to remotely monitor and control vehicles and robotic assets located outside the pressurized volume in the immediate vicinity or at low-latency distances from the habitat. The multiple display area of the TRWS allows the crew to have numerous windows open with live video feeds, control windows, and data browsers, as well as local monitoring and control of the DSH and associated systems.

Mittman, David S.↗
NASA NTRS2018

Enabling Reanalysis Research Using the Collaborative Reanalysis Technical Environment (CREATE)

Modern atmospheric and oceanic reanalysis are valuable assets for atmospheric research and climate monitoring (Kalnay et al. 1996). Now that most reanalysis records are more than 36 years long, the data have become more useful for climate modeling research (Dole et al. 2008). For investigators who need to use multiple reanalysis, a common challenge is that the data are distributed at various sites and often in different formats. The NASA CREATE system provides access to the data in one location in a standard format (one variable per file and standardized metadata in the CMIP5 style; see Table 1 for a list of the key acronyms used in this paper). The collection includes monthly and 6-hourly data from the seven major atmospheric reanalysis: CFSR (Saha et al. 2010), ERA-Interim (Dee et al. 2011), MERRA (Rienecker et al. 2011), MERRA-2 (Gelaro et al. 2017), JRA-25 (Onogi et al. 2007), JRA-55 (Kobayashi et al. 2014), and 20CRv2c (Compo et al. 2011). An ancillary portion of CREATE includes eight ocean reanalysis: NCEP CFSR, CMCC C-GLORSv5 (Storto et al. 2016), ECMWF ORAS4 (Balmaseda et al.2013), ECMWF ORAP5.0 (Zuo et al. 2015), University of Hamburg GECCO2 (Köhl 2015), GFDL ECDA (Zhang et al. 2007), NOAA GODAS (Saha et al. 2010), and MOVE/MRI.COM-G2i (Toyoda et al. 2016). The ocean state variables were similarly reformatted but were then also regridded onto a common horizontal and vertical grid. This approach facilitated the calculation of an ensemble average and spread that is also published alongside the native gridded data. A third reanalysis product is a global hourly 0.5° land surface air temperature dataset constructed by Wang and Zeng (2013). All three datasets are distributed through the ESGF in a format consistent with the CMIP style described by Cinquini et al. (2014).

Potter, Gerald L.↗
NASA NTRS2009

Monitoring Disasters by Use of Instrumented Robotic Aircraft

Efforts are under way to develop data-acquisition, data-processing, and data-communication systems for monitoring disasters over large geographic areas by use of uninhabited aerial systems (UAS) robotic aircraft that are typically piloted by remote control. As integral parts of advanced, comprehensive disaster- management programs, these systems would provide (1) real-time data that would be used to coordinate responses to current disasters and (2) recorded data that would be used to model disasters for the purpose of mitigating the effects of future disasters and planning responses to them. The basic idea is to equip UAS with sensors (e.g., conventional video cameras and/or multispectral imaging instruments) and to fly them over disaster areas, where they could transmit data by radio to command centers. Transmission could occur along direct line-of-sight paths and/or along over-the-horizon paths by relay via spacecraft in orbit around the Earth. The initial focus is on demonstrating systems for monitoring wildfires; other disasters to which these developments are expected to be applicable include floods, hurricanes, tornadoes, earthquakes, volcanic eruptions, leaks of toxic chemicals, and military attacks. The figure depicts a typical system for monitoring a wildfire. In this case, instruments aboard a UAS would generate calibrated thermal-infrared digital image data of terrain affected by a wildfire. The data would be sent by radio via satellite to a data-archive server and image-processing computers. In the image-processing computers, the data would be rapidly geo-rectified for processing by one or more of a large variety of geographic-information- system (GIS) and/or image-analysis software packages. After processing by this software, the data would be both stored in the archive and distributed through standard Internet connections to a disaster-mitigation center, an investigator, and/or command center at the scene of the fire. Ground assets (in this case, firefighters and/or firefighting equipment) would also be monitored in real time by use of Global Positioning System (GPS) units and radio communication links between the assets and the UAS. In this scenario, the UAS would serve as a data-relay station in the sky, sending packets of information concerning the locations of assets to the image-processing computer, wherein this information would be incorporated into the geo-rectified images and maps. Hence, the images and maps would enable command-center personnel to monitor locations of assets in real time and in relation to locations affected by the disaster. Optionally, in case of a disaster that disrupted communications, the UAS could be used as an airborne communication relay station to partly restore communications to the affected area. A prototype of a system of this type was demonstrated in a project denoted the First Response Experiment (Project FiRE). In this project, a controlled outdoor fire was observed by use of a thermal multispectral scanning imager on a UAS that delivered image data to a ground station via a satellite uplink/ downlink telemetry system. At the ground station, the image data were geo-rectified in nearly real time for distribution via the Internet to firefighting managers. Project FiRE was deemed a success in demonstrating several advances essential to the eventual success of the continuing development effort.

Wegener, Steven S.↗
NASA NTRS2009

Detection, Identification, Location, and Remote Sensing Using SAW RFID Sensor Tags

The Electromagnetic Systems Branch (EV4) of the Avionic Systems Division at NASA Johnson Space Center in Houston, TX is studying the utility of surface acoustic wave (SAW) radiofrequency identification (RFID) tags for multiple wireless applications including detection, identification, tracking, and remote sensing of objects on the lunar surface, monitoring of environmental test facilities, structural shape and health monitoring, and nondestructive test and evaluation of assets. For all of these applications, it is anticipated that the system utilized to interrogate the SAW RFID tags may need to operate at fairly long range and in the presence of considerable multipath and multiple-access interference. Towards that end, EV4 is developing a prototype SAW RFID wireless interrogation system for use in such environments called the Passive Adaptive RFID Sensor Equipment (PARSED) system. The system utilizes a digitally beam-formed planar receiving antenna array to extend range and provide direction-of-arrival information coupled with an approximate maximum-likelihood signal processing algorithm to provide near-optimal estimation of both range and temperature. The system is capable of forming a large number of beams within the field of view and resolving the information from several tags within each beam. The combination of both spatial and waveform discrimination provides the capability to track and monitor telemetry from a large number of objects appearing simultaneously within the field of view of the receiving array. In this paper, we will consider the application of the PARSEQ system to the problem of simultaneous detection, identification, localization, and temperature estimation for multiple objects. We will summarize the overall design of the PARSEQ system and present a detailed description of the design and performance of the signal detection and estimation algorithms incorporated in the system. The system is currently configured only to measure temperature (jointly with range and tag ID), but future versions will be revised to measure parameters other than temperature as SAW tags capable of interfacing with external sensors become available. It is anticipated that the estimation of arbitrary parameters measured using SAW-based sensors will be based on techniques very similar to the joint range and temperature estimation techniques described in this paper.

Barton, Richard J.↗
NASA NTRS2016

The Staring OBservations of the Atmosphere (SOBA) Mission Concept

The Staring OBservations of the Atmosphere (SOBA) Mission is a concept that was developed and matured under the guidance of the NASA Ames Project EXellence (APEX) program. If funded, it will provide an unprecedented opportunity to improve ash transport forecasts and climate model simulations associated with volcanic eruptions. NASA and National science objectives require a better understanding of volcanic aerosol and trace gas emissions, transport, chemical transformation, and deposition, since they impact Earth's climate and atmospheric composition, human health, and aviation safety. Natural hazards such as the 2010 eruption of the Eyjafjallajökull volcano in Iceland demonstrated how existing remote-sensing assets were inadequate for individual volcanic event monitoring. During this eruption, available instruments were unable to provide data necessary to initialize volcanic plume transport models so that they could accurately predict the quantity and location of volcanic ash. As a result, thousands of flights around the world were grounded unnecessarily, at great expense. Volcanoes can also play a large role in regulation of the Earth's climate, so SOBA observations will also be used to evaluate and improve volcanic aerosol and trace gas simulation in chemical transport models (CTMs) and global climate models (GCMs). We propose the development of an airborne remote sensing concept and field campaign that will respond to an eruption and provide near real time observations of a volcanic plume, specifically ash injection height, transport, aerosol microphysical physical properties, and the location and concentration of sulfur dioxide (SO2) (sulfate (SO42-) aerosol precursor). This airborne system will utilize a depolarization sensitive, downward looking Light Detection And Ranging (lidar) instrument and an ultraviolet (UV) imaging spectrometer, and will provide data to be ingested by volcanic ash advisory models. Furthermore, the lessons learned in the development of this system could eventually guide regular deployment of similar systems by NASA or other government agencies.

Aerosols↗
NASA NTRS2017

Development of a High-Fidelity Simulation Environment for Shadow-Mode Assessments of Air Traffic Concepts

This paper will describe the purpose, architecture, and implementation of a gate-to-gate, high-fidelity air traffic simulation environment called the Shadow Mode Assessment using Realistic Technologies for the National Airspace System (SMART-NAS) Test Bed.The overarching purpose of the SMART-NAS Test Bed (SNTB) is to conduct high-fidelity, real-time, human-in-the-loop and automation-in-the-loop simulations of current and proposed future air traffic concepts for the Next Generation Air Transportation System of the United States, called NextGen. SNTB is intended to enable simulations that are currently impractical or impossible for three major areas of NextGen research and development: Concepts across multiple operational domains such as the gate-to-gate trajectory-based operations concept; Concepts related to revolutionary operations such as the seamless and widespread integration of large and small Unmanned Aerial System (UAS) vehicles throughout U.S. airspace; Real-time system-wide safety assurance technologies to allow safe, increasingly autonomous aviation operations. SNTB is primarily accessed through a web browser. A set of secure support services are provided to simplify all aspects of real-time, human-in-the-loop and automation-in-the-loop simulations from design (i.e., prior to execution) through analysis (i.e., after execution). These services include simulation architecture and asset configuration; scenario generation; command, control and monitoring; and analysis support.

human-in-the-loop↗
NASA NTRS2002

NASA Advanced Supercomputing (NAS) User Services Group

This viewgraph presentation provides an overview of NAS (NASA Advanced Supercomputing), its goals, and its mainframe computer assets. Also covered are its functions, including systems monitoring and technical support.

Pandori, John↗
NASA NTRS2013

Space Weather Impacts to Conjunction Assessment: A NASA Robotic Orbital Safety Perspective

National Aeronautics and Space Administration (NASA) recognizes the risk of on-orbit collisions from other satellites and debris objects and has instituted a process to identify and react to close approaches. The charter of the NASA Robotic Conjunction Assessment Risk Analysis (CARA) task is to protect NASA robotic (unmanned) assets from threats posed by other space objects. Monitoring for potential collisions requires formulating close-approach predictions a week or more in the future to determine analyze, and respond to orbital conjunction events of interest. These predictions require propagation of the latest state vector and covariance assuming a predicted atmospheric density and ballistic coefficient. Any differences between the predicted drag used for propagation and the actual drag experienced by the space objects can potentially affect the conjunction event. Therefore, the space environment itself, in particular how space weather impacts atmospheric drag, is an essential element to understand in order effectively to assess the risk of conjunction events. The focus of this research is to develop a better understanding of the impact of space weather on conjunction assessment activities: both accurately determining the current risk and assessing how that risk may change under dynamic space weather conditions. We are engaged in a data-- ]mining exercise to corroborate whether or not observed changes in a conjunction event's dynamics appear consistent with space weather changes and are interested in developing a framework to respond appropriately to uncertainty in predicted space weather. In particular, we use historical conjunction event data products to search for dynamical effects on satellite orbits from changing atmospheric drag. Increased drag is expected to lower the satellite specific energy and will result in the satellite's being 'later' than expected, which can affect satellite conjunctions in a number of ways depending on the two satellites' orbits and the geometry of the conjunction. These satellite time offsets can form the basis of a new technique under development to determine whether space weather perturbations, such as coronal mass ejections, are likely to increase, decrease, or have a neutral effect on the collision risk due to a particular close approach.

Ghrist, Richard↗
NASA NTRS2010

Emulating an Optical Planetary Access Link with an Aircraft

Video imagery was streamed from the ground to an aircraft using a free-space laser communication link. The link operated at 270 Mb/s over slant ranges of 5-9 km in day and night time background conditions. The experiment was designed to demonstrate autonomous link acquisition and served as a first proof-of-concept for a planetary access link between a surface asset and an orbiter at Mars. System parameters monitored during the link demonstration including acquisition and tracking and communication performance are discussed.

Ground-to-Aircraft↗
NASA NTRSDate not supplied

Merging Analytic Collaborative Frameworks with New Observing Strategies Toward a Digital Twin: Earth – Episodic Pulse Event Impacts on Ocean Carbon Cycle as an Example

Virtual representations of the Earth will allow us to address some of the most critical environmental issues of our time. Here, we show the first steps toward representation of riverine, estuarine, and coastal carbon processes to enable scenario driven “what-if” analyses of the carbon system and human footprint. Excess sediment and nutrient runoff from land-based human activities impact water quality and can pose serious threats to coastal and marine ecosystems. Episodic pulse events, such as extreme precipitation events, can increase the amount of nutrients entering estuaries and coastal regions, potentially leading to large phytoplankton blooms followed by anoxic conditions. Consequences of coastal runoff are predicted to increase with the higher intensity and frequency of extreme events. Beyond the threat to coastal ecosystems, recent findings suggest these episodic pulses might play a significant role for biological production influencing regional and global carbon fluxes and budgets. An improved understanding of these events through optimal, dynamic observing strategies will increase our knowledge of the land-ocean continuum and how regional events and nutrient fluxes affect the carbon cycle and ocean ecosystem. This conceptual framework enables focused science investigations by pairing data analytics and artificial intelligence tools (otherwise termed an Analytic Center Framework, ACF) with targeted measurement acquisition through distributed sensing and intelligent asset tasking (or New Observing Strategies, NOS). This NOS and ACF iterative approach acquires and integrates complementary and coincident satellite, in-situ and model data to build a more complete and in-depth picture of science phenomena. Specifically, Apache Science Data Analytic Platform (SDAP) is extended to incorporate relevant datasets for data access, harmonized analysis, and anomaly detection. When conditions are met for a likely pulse event, NASA’s D-SHIELD (Distributed Spacecraft with Heuristic Intelligence to Enable Logistical Decisions) tool is triggered to optimize asset overpass frequency and schedule observations for persistent monitoring. Targeted data is ingested by SDAP for enhanced investigation via iterative analysis until the trigger criteria is no longer met - steps toward a digital twin.

Laura Rogers↗