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At least 505 records · Page 28

The Mathematics of Navigating the Solar System

In navigating spacecraft throughout the solar system, the space navigator relies on three academic disciplines - optimization, estimation, and control - that work on mathematical models of the real world. Thus, the navigator determines the flight path that will consume propellant and other resources in an efficient manner, determines where the craft is and predicts where it will go, and transfers it onto the optimal trajectory that meets operational and mission constraints. Mission requirements, for example, demand that observational measurements be made with sufficient precision that relativity must be modeled in collecting and fitting (the estimation process) the data, and propagating the trajectory. Thousands of parameters are now determined in near real-time to model the gravitational forces acting on a spacecraft in the vicinity of an irregularly shaped body. Completing these tasks requires mathematical models, analyses, and processing techniques. Newton, Gauss, Lambert, Legendre, and others are justly famous for their contributions to the mathematics of these tasks. More recently, graduate students participated in research to update the gravity model of the Saturnian system, including higher order gravity harmonics, tidal effects, and the influence of the rings. This investigation was conducted for the Cassini project to incorporate new trajectory modeling features in the navigation software. The resulting trajectory model will be used in navigating the 4-year tour of the Saturnian satellites. Also, undergraduate students are determining the ephemerides (locations versus time) of asteroids that will be used as reference objects in navigating the New Millennium's Deep Space 1 spacecraft autonomously.

Hintz, Gerald↗

TPSAS-NF1676L-31944-DND

The Plum Island Estuary (PIE) in Massachusetts is New England’s largest salt marsh. This dynamic ecosystem plays an important role in the surrounding communities by providing ecosystem and social services, acting as a center for education, research, and recreation. However, marshes around the world are threatened by sea level rise. As the equilibrium between sediment supply, erosion rates, and vegetation growth is unbalanced by rising waters, marshes are liable to recede, or even drown. Because sediment is so crucial, researchers use sediment budgets as a metric to assess Plum Island Estuary’s vulnerability to rising seas; however, established data collection methods are limited in scope. The project employed five years of imagery from Landsat 8 Operational Land Imager (OLI) and three years of imagery from Sentinel-2 Multispectral Instrument (MSI), in conjunction with in situ data, to generate and refine a local algorithm that derives suspended sediment concentration from remote sensing reflectance. This information was applied to a flux model to analyze transport patterns and possible sediment sources, particularly the Merrimack River. The use of remote sensing techniques will provide our partners at the US Geological Survey, US Fish and Wildlife Service, and Plum Island Ecosystems Long Term Ecological Research Network with higher spatial and temporal resolution data, which will allow for the development of more effective management practices.

Sydney Neugebauer↗

Megadroughts in the Common Era and the Anthropocene

Megadroughts, often lasting multiple decades, have caused major ecological and societal disturbances in the past. While most research has focused on megadroughts in North America, the concept has gained increased international attention in recent years. In this Review, we discuss shared causes and features of Common Era and future megadroughts. Paleoclimate reconstructions spanning the last 2,000 years document the occurrence of megadroughts on every continent, save Antarctica. Megadroughts are often linked to decadal variations in sea surface temperatures, with radiative forcing and land-atmosphere interactions acting as secondary factors. Anthropogenic climate change has already contributed to recent megadroughts in southwestern North America and Chile-Argentina and will likely increase future megadrought risk and severity in many regions. Notably, future megadroughts will be differentiated from past events through higher temperatures, which act as the main driver of increased risk, severity, and impacts. Major deficiencies in our understanding of natural and anthropogenic megadrought processes remain, however. These include 1) sparse high-resolution paleoclimate information over some regions, 2) incomplete representations of internal variability and land-surface processes in climate models, and 3) the undetermined capacity of water-resource management systems to manage megadrought impacts. Resolving these key uncertainties will be necessary to increase confidence in projections of future megadrought risk and resiliency planning.

Droughts↗

Machine Learning-Driven Quantification of CO2 Plume Dynamics at Illinois Basin Decatur Project Sites Using Microseismic Data

This study utilizes machine learning to quantify CO2 plume extents by analyzing microseismic data from the Illinois Basin Decatur Project (IBDP). Leveraging a unique dataset of well logs, microseismic records, and CO2 injection metrics, this work aims to predict the temporal evolution of subsurface CO2 saturation plumes. The findings illustrate that machine learning can predict plume dynamics, revealing vertical clustering of microseismic events over distinct time periods within certain proximities to the injection well, consistent with an invasion percolation model. The buoyant CO2 plume partially trapped within sandstone intervals periodically breaches localized barriers or baffles, which act as leaky seals and impede vertical migration until buoyancy overcomes gravity and capillary forces, leading to breakthroughs along vertical zones of weakness. Between different unsupervised clustering techniques, K-Means and DBSCAN were applied and analyzed in detail, where K-means outperformed DBSCAN in this specific study by indicating the combination of the highest Silhouette Score and the lowest Davies–Bouldin Index. The predictive capability of machine learning models in quantifying CO2 saturation plume extension is significant for real-time monitoring and management of CO2 sequestration sites. The models exhibit high accuracy, validated against physical models and injection data from the IBDP, reinforcing the viability of CO2 geological sequestration as a climate change mitigation strategy and enhancing advanced tools for safe management of these operations.

Iyegbekedo, Ikponmwosa↗

Checklist interruption and resumption: A linguistic study

This study forms part of a project investigating the relationships among the formal structure of aviation procedures, the ways in which the crew members are taught to execute them, and the ways in which thet are actually performed in flight. Specifically, this report examines the interactions between the performance of checklists and interruptions, considering both interruptions by radio communications and by other crew members. The data consists of 14 crews' performance of a full mission simulation of a higher ratio of checklist speech acts to all speech acts within the span of the performance of the checklist. Further, it is not number of interruptions but length of interruptions which is associated with crew performance quality. Use of explicit holds is also associated with crew performance.

Linde, Charlotte↗

Space Suit Survivability Enhancement NASA Research Announcement 96-OLMSA-01B: Advanced Life Support and Environmental Technologies for Human Exploration and Development of Space

Conducted two meetings to review the project scope and develop concepts for self-sealing material compositions, Focus has been on developing concepts that would seal a penetration enough to allow the astronauts to re-enter the spacecraft within the window provided by the emergency air supply. Concepts discussed include: quilted fabrics containing a viscous flow material in the quilted cells which would seal the bladder breach when forced to flow by the internal suit pressure; a sealant impregnated felt liner which acts similar to above; and a "blousy" fibrous layer which would mechanically plug a rupture under pressure. Illustrations of the above concepts are included in the attached viewgraphs, which were used in a presentation. The most promising of these concepts will be made into prototypes for testing. ILC has developed a test fixture to test the scaling characteristics of various material layups by measuring real-time changes in pressure and make-up flow in a pressurized cylinder. Candidate viscous sealing compounds such as silicones and urethanes have been identified. These compounds will be coated on existing bladder cloth for initial tests. The most promising compounds will be integrated into the above material structures for final testing. Design and analysis of fabric weaves to improve cut and puncture resistance of the suit TMG layers is underway. Philadelphia Textile is developing a mathematical model to correlate yarn type and weave structure to cut and tear resistance. The computer mathematical modeling of the fabric failure mechanisms by Cornell University, as originally proposed, will be replaced with the above model and empirical testing methods, due to the loss of key Cornell personnel.

Source record↗

Design and Impacts of Land-Biogenic-Atmosphere Coupling in the NASA-Unified WRF (NU-WRF) Modeling System

Land-Atmosphere coupling is typically designed and implemented independently for physical (e.g. water and energy) and chemical (e.g. biogenic emissions and surface depositions)-based models and applications. Differences in scale, data requirements, and physics thus limit the ability of Earth System models to be fully coupled in a consistent manner. In order for the physical-chemical-biological coupling to be complete, treatment of the land in terms of surface classification, condition, fluxes, and emissions must be considered simultaneously and coherently across all components. In this study, we investigate a coupling strategy for the NASA-Unified Weather Research and Forecasting (NU-WRF) model that incorporates the traditionally disparate fluxes of water and energy through NASA's LIS (Land Information System) and biogenic emissions through BEIS (Biogenic Emissions Inventory System) and MEGAN (Model of Emissions of Gases and Aerosols from Nature) into the atmosphere. In doing so, inconsistencies across model inputs and parameter data are resolved such that the emissions from a particular plant species are consistent with the heat and moisture fluxes calculated for that land cover type. In turn, the response of the atmospheric turbulence and mixing in the planetary boundary layer (PBL) acts on the identical surface type, fluxes, and emissions for each. In addition, the coupling of dust emission within the NU-WRF system is performed in order to ensure consistency and to maximize the benefit of high-resolution land representation in LIS. The impacts of those self-consistent components on' the simulation of atmospheric aerosols are then evaluated through the WRF-Chem-GOCART (Goddard Chemistry Aerosol Radiation and Transport) model. Overall, this ambitious project highlights the current difficulties and future potential of fully coupled. components. in Earth System models, and underscores the importance of the iLEAPS community in supporting improved knowledge of processes and innovative approaches for models and observations.

Tan, Qian↗

Seeding Innovative Ideas and Partnering with the Ecosystem

Jenn Gustetic will talk about how NASA selects ideas and collaborates with the ecosystem to develop new technologies for NASA’s portfolio. She will explain how the organization encourages collaboration, co-invests to develop ideas from lab to market, and acts as the hub-and-spoke of the ecosystem. Jenn will also discuss NASA’s journey to break silos and work horizontally across programs. • Gathering and evaluating ideas internally and externally with diverse players – engaging communities, being the hub-and-spoke of the ecosystem, and encouraging collaboration through co-investments • Identify the best ideas, funding ideas from maturation to hand-off with fluctuating budgets, and managing IP and tech transfer • Balancing investments in projects that address NASA’s needs with higher risk ideas that may not have an obvious application • Transitioning ideas to the next phase – training people and teams and ensuring ownership • Developing a 3.0 innovation capacity strategy – disrupting silos, enabling the ecosystem to work seamlessly together, and taking people and leaders along

innovation↗

System Would Generate Virtual Heads-Up Display

Proposed helmet-mounted electronic display system superimposes full-color alphanumerical and/or graphical information onto observer's visual field. Displayed information projected directly onto observer's retinas, giving observer illusion of full-size computer display in foreground or background. Display stereoscopic, holographic, or in form of virtual image. Used by pilots to view navigational information while looking outside or at instruments, by security officers to view information about critical facilities while looking at visitors, or possibly even stock-exchange facilities to view desktop monitors and overhead displays simultaneously. System includes acousto-optical tunable filter (AOTF), which acts as both spectral filter and spatial light modulator.

Lambert, James L.↗

The NPOESS Preparatory Project (NPP) Science Data Segment (SDS) Data Depository and Distribution Element (SD3E) System Architecture

The National Polar-orbiting Operational Environmental Satellite System (NPOESS), the U.S. Government's future low-Earth orbiting satellite system, will monitor global weather and environmental conditions. Serving as a risk reduction for NPOESS, the NPOESS Preparatory Project (NPP) will provide remotely sensed atmospheric, land, ocean, ozone, and sounder data that will serve the meteorological and global climate change scientific communities. The National Aeronautics and Space Administration (NASA) NPP Science Data Segment's (SDS) primary role is to independently assess the quality of the NPP science and environmental data records for their ability to support climate research. The SDS is composed of nine elements; an input element that receives data from the operational agencies and acts as a buffer, a calibration analysis element, five elements devoted to measurement based quality assessment, an element used to test algorithmic improvements, and an element that provides overall science direction. Each element requires a set of sensor specific science data products for their evaluation. There are four NPP sensors that will be flown on the NPP observatory. They are the Visible Infrared Imagining Radiometer Suite (VIIRS), the Advanced Technology Microwave Sounder (ATMS), the Cross-Track Infrared Sounder (CrIS), and the Ozone Mapper/Profiler Suite (OMPS). It is estimated that these four sensors combined will make daily data requests for approximately six terabytes of NPP science products from the operational data providers. As a result, issues associated with duplicate data requests, data transfers of large volumes of diverse products, and data transfer failures raised concerns with respect to the network traffic and bandwidth consumption. Therefore, a central data broker system for receiving and buffering data requests and data products for the SDS was developed. The data element for this system is called the SDS Data Depository and Distribution Element (SD3E). It supports science mission data assessment by assuring the timely and validated acquisition and subsequent transfer of the NPP Science Mission data to the SDS Elements and NPP Science Team. The six science elements that interface with the SD3E span across the NASA Goddard Space Flight Center (GSFC), the NASA Jet Propulsion Laboratory (JPL), and the University of Wisconsin. As the primary communication vehicle for the science elements and science team, the SD3E has an interface to the operational data providers: National Environment Satellite, Data, and Information Service (NESDIS) Interface Data Processing System (IDPS) and the National Oceanic Atmospheric Administration's (NOAA) Comprehensive Large Array-data Stewardship system (CLASS) Archive Data System (ADS), that are responsible for product generation and archive and distribution respectively. The SD3E is designed to be a semi-customizable and semi-automated system. This system is designed to provide flexibility and ease of use for the science users in accessing the latest data products by creating a rolling data cache that temporarily stores the products locally before transferring the data to the SDS Measurement based elements for the land, ocean, atmosphere, sounder, and ozone. This paper describes the design and architecture of one of the nine SDS elements, the SD3E, and how this system has provided a mechanism for efficient data exchange, how it has helped in alleviating some of the network traffic and usage, and how it has contributed to reducing operational costs.

Ho, Evelyn L.↗

Clarifying the trophic state concept to advance macroscale freshwater science and management

For over a century, ecologists have used the concept of trophic state (TS) to characterize an aquatic ecosystem's biological productivity. However, multiple TS classification schemes, each relying on a variety of measurable parameters as proxies for productivity, have emerged to meet use‐specific needs. Frequently, chlorophyll a, phosphorus, and Secchi depth are used to classify TS based on autotrophic production, whereas phosphorus, dissolved organic carbon, and true color are used to classify TS based on both autotrophic and heterotrophic production. Both classification approaches aim to characterize an ecosystem's function broadly, but with varying degrees of autotrophic and heterotrophic processes considered in those characterizations. Moreover, differing classification schemes can create inconsistent interpretations of ecosystem integrity. For example, the US Clean Water Act focuses exclusively on algal threats to water quality, framed in terms of eutrophication in response to nutrient loading. This usage lacks information about non‐algal threats to water quality, such as dystrophication in response to dissolved organic carbon loading. Consequently, the TS classification schemes used to identify eutrophication and dystrophication may refer to ecosystems similarly (e.g., oligotrophic and eutrophic), yet these categories are derived from different proxies. These inconsistencies in TS classification schemes may be compounded when interdisciplinary projects employ varied TS frameworks. Even with these shortcomings, TS can still be used to distill information on complex aquatic ecosystem function into a set of generalizable expectations. The usefulness of distilling complex information into a TS index is substantial such that usage inconsistencies should be explicitly addressed and resolved. To emphasize the consequences of diverging TS classification schemes, we present three case studies for which an improved understanding of the TS concept advances freshwater research, management efforts, and interdisciplinary collaboration. To increase clarity in TS, the aquatic sciences could benefit from including information about the proxy variables, ecosystem type, as well as the spatiotemporal domains used to classify TS. As the field of aquatic sciences expands and climatic irregularity increases, we highlight the importance of re‐evaluating fundamental concepts, such as TS, to ensure their compatibility with evolving science.

classification↗

Seamlessly joining length scales: From atomistic thermal graphs to anisotropic continuum conductivity

Thermal transport in complex solids is governed by local structure, defects, and anisotropy, yet most continuum models still rely on oversimplified and homogenized conductivities. Here, we bridge atomistic and continuum descriptions by building finite element (FE) models directly from the site-projected thermal conductivity (SPTC), an atomic-level decomposition of the Green–Kubo thermal conductivity. We introduce a toolkit, the “Simulator Collection for Atomic-to-Continuum Scales (SCACS)”, which uses a graph neural network to predict SPTC on large atomic structures, coarse-grains these fields into anisotropic conductivity tensors, and embeds them into the heat-flow FE equation with a customized, anisotropy-aware adaptive mesh refinement scheme. Applied to silicon nanostructures, the resulting FE models act as representative volume elements, reproduce bulk conductivities, and capture interfacial and defect-driven anisotropy while maintaining thermodynamic consistency. Additionally, SCACS predicts experimental conductance trends and fields. This work demonstrates a general route for transferring atomistic transport information into device-scale thermal simulations with physics-based approximations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Approach for Structurally Clearing an Adaptive Compliant Trailing Edge Flap for Flight

The Adaptive Compliant Trailing Edge (ACTE) flap was flown on the National Aeronautics and Space Administration (NASA) Gulfstream GIII testbed at the NASA Armstrong Flight Research Center. This smoothly curving flap replaced the existing Fowler flaps creating a seamless control surface. This compliant structure, developed by FlexSys Inc. in partnership with the Air Force Research Laboratory, supported NASA objectives for airframe structural noise reduction, aerodynamic efficiency, and wing weight reduction through gust load alleviation. A thorough structures airworthiness approach was developed to move this project safely to flight. A combination of industry and NASA standard practice require various structural analyses, ground testing, and health monitoring techniques for showing an airworthy structure. This paper provides an overview of compliant structures design, the structural ground testing leading up to flight, and the flight envelope expansion and monitoring strategy. Flight data will be presented, and lessons learned along the way will be highlighted.

flight test↗

Tracing cosmic gas in filaments and halos: Low-redshift insights from the kinematic Sunyaev-Zel’dovich effect

In this work, we leverage cosmic microwave background (CMB) data from the Atacama Cosmology Telescope (ACT) and LSS data from the imaging survey conducted by the Dark Energy Spectroscopic Instrument (DESI) to study the distribution of gas around galaxy groups at low redshift, z ≈ 0.3, via the kinematic Sunyaev-Zel'dovich (kSZ) effect. In particular, we perform velocity-weighted stacking on the photometric galaxies from the Bright Galaxy Survey (BGS) to isolate the monopole and quadrupole of the kSZ signal, orienting the stacked images along 2D filaments identified using the Hessian of the projected gravitational potential. We find a 7.2σ detection in the monopole of the signal (i.e., the gas density profile) and a 4σ detection in the quadrupole (m = 2), constituting the first measurement of the alignment between gas distribution and the cosmic web through the kSZ effect. As it is a linear probe of the local gas density, the kSZ has heightened sensitivity to the warm-hot intergalactic medium (WHIM), which is believed to house the majority of the "missing baryons."Mapping out the gas density at low redshifts, as enabled by our measurements, is crucial for weak lensing surveys, for which the impact of baryons on small scales is a major impediment. We compare the anisotropic signal against two hydrodynamical simulations, TNG300-1 and Illustris, which have very different baryonic feedback prescriptions. We find that the anisotropic signal measured in the data is comparable but slightly larger and more extended compared with the simulations. Further, this suggests that there is excess accretion and feedback taking place through the filaments, hinting at the possible presence of spin-filament alignment of the BGS objects.

79 ASTRONOMY AND ASTROPHYSICS↗

Demonstration and Validation of a Virtual Energy Audit Tool for DoD Buildings

Electricity consumption has been in the spotlight as part of the battle for sustainability resulting in legislative measures to try and reduce the amount of energy used. EISA 432 and the Energy Act of 2020 are two examples that require federal facilities to investigate buildings and find saving opportunities through energy audits. EDIFES solves this problem by providing fully virtual audits. Only five inputs are needed (15-minute interval electricity consumption, location, square footage, number of stories, and building end use) to produce complete energy audits. The virtual audit is automated, making them inexpensive and the small number of inputs allows a large number of buildings to be entered quickly. During this project, EDIFES performed energy audits on hundreds of buildings to ensure proper functionality and workflow. Over 250 DoD buildings received energy audits that then had their results posted to an interactive dashboard with portfolio rankings. Several validation methods were employed. All confirmed that EDIFES's methods worked as expected and with a high degree of accuracy.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Designing the Ares I Crew Launch Vehicle Upper Stage Element and Integrating the Stack at NASA's Marshall Space Flight Center

Fielding an integrated launch vehicle system entails many challenges, not the least of which is the fact that it has been over 30 years since the United States has developed a human-rated vehicle - the venerable Space Shuttle. Over time, whole generations of rocket scientists have passed through the aerospace community without the opportunity to perform such exacting, demanding, and rewarding work. However, with almost 50 years of experience leading the design, development, and end-to-end systems engineering and integration of complex launch vehicles, NASA's Marshall Space Flight Center offers the in-house talent - both junior- and senior-level personnel - to shape a new national asset to meet the requirements for safe, reliable, and affordable space exploration solutions.' These personnel are housed primarily in Marshall's Engineering Directorate and are matrixed into the programs and projects that reside at the rocket center. Fortunately, many Apollo era and Shuttle engineers, as well as those who gained valuable hands-on experience in the 1990s by conducting technology demonstrator projects such as the Delta-Clipper Experimental Advanced, X-33, X-34, and X-37, as well as the short-lived Orbital Space Plane, work closely with industry partners to advance the nation's strategic capability for human access to space. Currently, only three spacefaring nations have this distinction, including the United States, Russia, and, more recently, China. The U.S. National Space Policy of2006 directs that NASA provide the means to travel to space, and the NASA Appropriations Act of2005 provided the initial funding to begin in earnest to replace the Shuttle after the International Space Station construction is complete in 20 IO? These and other strategic goals and objectives are documented in NASA's 2006 Strategic Plan.3 In 2005, a team of NASA aerospace experts conducted the Exploration Systems Architecture Study, which recommended a two-vehicle approach to America's next space transportation system for missions to the International Space Station in the next decade and to explore the Moon and establish an outpost around the 2020 timeframe.4 Based on this extensive study, NASA selected the Ares I crew launch vehicle configuration and the heavy-lift Ares V cargo launch vehicle (fig 1). This paper will give an overview of NASA's approach to integrating the Ares I vehicle stack using capabilities and assets that are resident in Marshall's Engineering Directorate, working in partnership with other NASA Centers and the U.S. aerospace industry. It also will provide top-level details on the progress of the in-house design of the Ares I vehicle's upper stage element.

Lyles, Garry↗

Compact Focal Plane Assembly for Planetary Science

A compact radiometric focal plane assembly (FPA) has been designed in which the filters are individually co-registered over compact thermopile pixels. This allows for construction of an ultralightweight and compact radiometric instrument. The FPA also incorporates micromachined baffles in order to mitigate crosstalk and low-pass filter windows in order to eliminate high-frequency radiation. Compact metal mesh bandpass filters were fabricated for the far infrared (FIR) spectral range (17 to 100 microns), a game-changing technology for future planetary FIR instruments. This fabrication approach allows the dimensions of individual metal mesh filters to be tailored with better than 10- micron precision. In contrast, conventional compact filters employed in recent missions and in near-term instruments consist of large filter sheets manually cut into much smaller pieces, which is a much less precise and much more labor-intensive, expensive, and difficult process. Filter performance was validated by integrating them with thermopile arrays. Demonstration of the FPA will require the integration of two technologies. The first technology is compact, lightweight, robust against cryogenic thermal cycling, and radiation-hard micromachined bandpass filters. They consist of a copper mesh supported on a deep reactive ion-etched silicon frame. This design architecture is advantageous when constructing a lightweight and compact instrument because (1) the frame acts like a jig and facilitates filter integration with the FPA, (2) the frame can be designed so as to maximize the FPA field of view, (3) the frame can be simultaneously used as a baffle for mitigating crosstalk, and (4) micron-scale alignment features can be patterned so as to permit high-precision filter stacking and, consequently, increase the filter bandwidth and sharpen the out-of-band rolloff. The second technology consists of leveraging, from another project, compact and lightweight Bi0.87Sb0.13/Sb arrayed thermopiles. These detectors consist of 30-layer thermopiles deposited in series upon a silicon nitride membrane. At 300 K, the thermopile arrays are highly linear over many orders of magnitude of incident IR power, and have a reported specific detectivity that exceeds the requirements imposed on future mission concepts. The bandpass filter array board is integrated with a thermopile array board by mounting both boards on a machined aluminum jig.

Brown, Ari↗

Dynamic Assurance of Autonomous Systems through Ground Control Software

Assurance cases are being increasingly acknowledged as a way to build trust in complex systems with autonomous capabilities [1]. An assurance case is a comprehensive, defensible, and valid justification that a system will function as intended for the specific mission and operating environment. Such justifications for systems with autonomous capabilities are often based on various probabilistic quantifications [2]. Due to the dynamic nature of the environmental conditions in which these systems operate, as well as the changing nature of the autonomous systems themselves, these probabilistic quantifications cannot be simply estimated once during design time. Rather, they need to be continually evaluated during systems operations to ensure that the assurance case justifications are valid. We refer to the assurance case that combines both the static and dynamic elements as a Dynamic Assurance Case (DAC). Such complex systems with autonomous capabilities are often deployed with a Ground Control Software (GCS) component to enable remote operation. Whether the system is composed of a single unit or a fleet of units, deployed distributed or in remote environments, GCS acts as a window into the behavior of the deployed system. It receives telemetry from the system, issues commands to the system and provides various functionalities to visualize the system performance. We propose a dynamic assurance framework where the GCS acts as a relay between the autonomous system and its DAC. GCS can be used to measure both unit-specific as well as system-wide probabilistic quantifications using the incoming telemetry. We embed these quantifications throughout the DAC as variables that can be updated by external sources. We use the GCS to periodically update these variables, which allows us to continually evaluate the formally defined assurance case justifications. We demonstrate our dynamic assurance framework in the NASA Ames project Troupe1 that aims at developing a fleet of rovers capable of au- tonomously mapping their environment. The rovers work cooperatively, each collecting data for different parts of the environment. Each rover runs an identical core Flight System (cFS) [4] application. Troupe1 uses OpenC3 Cosmos [5] as the ground system, and AdvoCATE [3] to capture the system DAC. We show how we can measure both rover-specific and system-wide quantifications in Cosmos using its Ruby scripting editor and pass them into the DAC modelled in AdvoCATE. Then, we show how these incoming variables can be embedded in different parts of the DAC and how effects of their updates can be observed

Irfan Sljivo↗