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Taken together the components of the Einstein Suite provide two revolutionary capabilities - they have the potential to change the way engineering and financial engineering are performed by: (1) providing currently unavailable functionality, and (2) providing a 10-100 times improvement over currently available but impractical or costly functionality.
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Collaborative open science practices are changing the way research is conducted. These changes affect how scientists work together on data, code and information. Data systems enhance open science by offering forward thinking technological solutions, such as providing data and computation on the cloud, to enable collaboration, sharing and analysis. In this paper, we present our vision for a conceptual data system on the cloud that enables open science. We also present our work on the Multi-Mission Algorithm and Analysis Platform (MAAP)which has served as a pathfinder data system for this conceptual approach.
The Multi‐mission Algorithm and Analysis Platform (MAAP) is a collaborative effort between NASA and the European Space Agency (ESA) to support above ground biomass (AGB) research in an open science framework. MAAP brings together relevant data, algorithms, and computing capabilities in a common cloud environment to address the challenges of sharing and processing data from field, airborne and satellite measurements. MAAP was publicly released in October 2021, providing computing capabilities co-located with the data, a collaborative coding and analysis environment, and a set of interoperable tools and algorithms developed to support the estimation and visualization of data. MAAP has allowed scientists from both North America and Europe to collaborate on the generation and analysis/visualization of data derived from multiple, discipline-adjacent missions in an open, collaborative environment that has reached beyond traditional scientific investigation. MAAP has been used to support multiple scientific activities. To date, existing LiDAR data from multiple platforms has been calibrated with field measurements and combined for more comprehensive and accurate estimates of above ground biomass AGB; these LiDAR platforms include airborne (e.g. LVIS), the International Space Station (NASA’s Global Ecosystem Dynamics Investigation (GEDI), and satellites (e.g. ICESat-2). The current challenge is to effectively and seamlessly combine the aforementioned LiDAR-based data with new data sources such as P-band RADAR from ESA’s upcoming BIOMASS mission, existing ESA Sentinel-1 C-band SAR, and the 30 PB/yr of high cadence global coverage L-band SAR data from the upcoming NASA-ISRO SAR (NISAR) mission. Recent analysis using MAAP merged ICESat-2 and optical data (Harmonized Landsat Sentinel) produced the most comprehensively precise estimate of boreal-wide AGB to date. Another effort using MAAP is the production and open distribution of global comparisons of AGB map estimates, including from ICESat-2 and GEDI, to bolster stakeholder uptake for policy applications. These map estimates will feed into the Intergovernmental Panel on Climate Change (IPCC) database, likely aiding the next Global Carbon Stocktake of the UNFCCC. Furthermore, the biomass retrieval intercomparison exercise BRIX-2 could benefit from the MAAP providing standardized test cases (based on airborne campaign and spaceborne data) allowing the community to develop and apply retrieval algorithms based on these test cases, while forthcoming SAR data training curricula could also use the MAAP as a teaching and learning platform. The MAAP is meeting the challenges inherent in international, open science collaboration and large scale computing with a platform that is entirely open source and cloud native, using open standards for data access, manipulation, protocols, and formats. The MAAP data system consists of a dedicated data store whose data is indexed in an online catalog conforming to established metadata, application programmatic interfaces (APIs), and service interface standards, using an implementation of the open sourced NASA Common Metadata Repository. Federation of user identities allows users from either NASA or ESA to access and consume services from the other using a unified metadata catalog for the data utilized across the ESA and NASA MAAP platforms. Similarly, we are exploring how to increase interoperability to achieve a common approach to packaging, orchestrating and executing algorithms, with interoperable access to data for subsetting, fast browse, and cloud-optimized access, all using interoperable standards such as those from the Open Geospatial Consortium (OGC). Designed for interoperability, ESA and NASA utilize a common architecture for the software platform. It provides a cloud-based algorithm development environment (ADE) that enables scientists to develop algorithms collaboratively with access to the MAAP data catalog as well as other data archives. MAAP provides an Eclipse Che-based ADE supporting both Python and R languages, popular in this biomass community. Algorithms developed and containerized within the ADE can be deployed to run to thousands of computational nodes in the MAAP’s data processing system (DPS), dramatically speeding up processing and giving scientists a rapid, iterative turnaround of results. NASA’s implementation of the DPS is based on the Hybrid Science Data System (HySDS) framework, used by NASA flight projects to produce Earth science standard products.
The next era in human space exploration is rapidly approaching. The use of health countermeasures and biomonitoring systems for space missions are required to counteract space health hazards and to support life to thrive in deep space (e.g., humans, animals, plants, crops; entire ecosystems within spacecrafts/habitats/spacesuits). The development of these mission components will be highly dependent on our understanding of basic biological and health responses to myriad space hazards (ionizing radiation, altered gravitational fields, altered day-night cycles, confined isolation, hostile-closed environments, distance-duration from Earth, planetary dust-regolith, and extreme temperatures/atmospheres). The fast-growing array of space biological and mission telemetry data, which in the past was simply archived after minimal analysis, holds great potential once applied to these mission challenges if it can be reorganized and formatted for Open Science. Organizing the data for such analysis is a challenge because of its multi-hierarchical, multi-modal, and heterogenous nature (molecular, cellular, tissue, organ, whole organism, behavior, ecosystem, microbiome; tabular, omics, imaging, video, biospecimen, environmental physical-chemical telemetry). This session focuses on current approaches in this domain such as: making space biological data FAIR (findable, accessible, interoperable, reusable), effective data ingestion/dissemination, observational versus experimental data, Open Science collaborations, data analysis techniques, AI/ML/knowledge graph/modeling methods, and data integration/discovery tools.
Poster on “CO2 Storage Economic Analysis: CarbonSAFE Use Case” for the CCUS 2025 conference held in Houston, Texas March 3-5, 2025. The cost of designing, permitting, constructing, operating, and closing a CO2 storage project is of vital importance to project developers. The National Energy Technology Laboratory has developed the NRAP/SMART Technoeconomic and Liability Evaluation for Storage (TALES) Model to provide quantitative cost-based insights to support developers planning CO2 injection and storage projects. This study presents a collaborative economic analysis applying TALES with data from the San Juan Basin CarbonSAFE Phase III project led by the New Mexico Institute of Mining and Technology to estimate potential costs incurred during the implementation of a real-world commercial-scale carbon storage project. Scenario analysis was implemented in which different operational and cost attributes were varied and the associated cost implications observed. Key results data and project cost summary metrics, first-year breakeven price of CO2 ($/tonne) and net present value (NPV), are presented for base and alternative cases. Output provides a unique perspective for project stakeholders towards evaluating the influence of different operational strategies and financing approaches on overall project cost and financial viability.
The ATLAS collaboration, using 139 fb −1 of 13 TeV collisions from the Large Hadron Collider, has placed limits on the decay of a Z boson to three dark photons. We reproduce the results of the ATLAS analysis, and then recast it as a limit on a exotic Higgs decay mode, in which the Higgs boson decays via a pair of intermediate (pseudo)scalars a to four dark photons V (or some other spin-one meson). Across the mass range for m a and m V , we find limits on the exotic Higgs branching fraction BR(H → aa → V V V V ) in the range of 4 × 10 −5 to 1 × 10 −4 .
This presentation offers an overview of NREL's REopt(R) web tool for the National Community Solar Partnership+ States Collaborative. REopt is a techno-economic modeling tool for evaluating distributed energy resources toward a site's cost savings and resilience goals. The presentation includes an overview of the REopt platform, a REopt web tool demonstration, and resources to learn more about REopt.
The first joint analysis of data from the NOvA and T2K neutrino oscillations experiments was published in 2025, offering the most precise measurements of the larger mass splitting $\Delta m_{32}^{2}$, the largest mixing angle $\theta_{23}$, and the CP-violating phase $\delta_{CP}$ available at the time. In addition to working towards a reanalysis with additional data collected since that analysis, the collaborations are now exploring possible constraints on BSM physics scenarios. This poster will discuss the potential of a joint measurement of parameters in a framework treating effective non-standard neutral-current neutrino-matter interactions, NC-NSI. Uniquely, the differing baselines and energies of T2K and NOvA allow strong constraints to be set on the electron-muon and electron-tau parameters of NSI contributions to the Hamiltonian, while at the same time maintaining good sensitivity to the standard 3-flavor neutrino oscillations parameters, including the CP phase.
The Fermilab Muon $g-2$ Experiment is designed to measure the muon's anomalous magnetic moment, $ a_\mu = (g-2)/2 $ with an accuracy of 140 parts per billion. This quantity is determined from two key measurements; the difference between the muon's spin precession frequency and its cyclotron frequency, given by $\omega_a = \omega_s - \omega_c$, and $\tilde{\omega_p^\prime}$, proportional to the muon-weighted magnetic field.In this talk, we focus on presenting the methodology for determining $\omega_a$. Muons with a momentum of 3.1 GeV are injected into a storage ring, and $\omega_a$ is extracted from the time distribution of decay positrons recorded by 24 electromagnetic calorimeters placed symmetrically inwards around the ring. We present the final result from the muon g-2 collaboration and analysis techniques based on data collected from 2020 to 2023.
A very extensive Io sodium imaging program beginning with the first images of the cloud and culminating in comprehensive characterization of the cloud's appearance and behavior as a function of both time and Io's orbital position now forms the basis for a collaborative modeling analysis and a continued observational study with emphasis on understanding how the cloud's behavior is diagnostic of spatial and temporal variations in the physical conditions of the inner Jovian magnetosphere. The sodium cloud was found to have a variety of systematic variations, a pronounced east-west orbital asymmetry, and temporal changes which could be diagnostic of time changes in both Io and its plasma environment. New comet imaging programs initiated at the 3.6-meter Canada-France-Hawaii Telescope draw upon both ultra high time resolution and high spatial resolution imaging capabilities. Seven observing runs between Dec. 1984 and May 1986 were devoted to observing Halley, Giacobini-Zinner, and several other comets. Among these observations were the first images of Halley through IHW filters, and images of Giacobini-Zinner during the ICE encounter which have been directly correlated with ICE magnetic field measurements.
The goal of this proposal was to perform simultaneous x-ray spectral and millisecond timing observations of accreting neutron stars to further our understanding of their accretion dynamics and in the hope of using these systems as probes of the physics of strong gravitational fields. Observations of the neutron star binaries 4U0614+091, 4U1728-34, 4U1820-30, and Cyg X-2 were carried out with RXTE and BeppoSAX, ASCA, and Chandra (not all simultaneously). In addition, archival data were analyzed for 4U0614+091 and 4U1820-30. This investigation led to publication of three papers in peer-reviewed journals. These are listed below. In addition, the results were presented at several meetings including the two poster presentations listed below. Dr. Santina Piraino visited SAO for 4 months during 2000 to collaborate on analysis of the data from NAG5-8408 and NAG5-9104.
Boeing was selected in 2007 to manufacture Ares I Upper Stage and Instrument Unit according to NASA's design which would require the use of the latest manufacturing and integration processes to meet NASA budget and schedule targets. Past production experience has established that the majority of the life cycle cost is established during the initial design process. Concept of Operations (CONOPs) visualizations/simulations help to reduce life cycle cost during the early design stage. Production and operation visualizations can reduce tooling, factory capacity, safety, and build process risks while spreading program support across government, academic, media and public constituencies. The NASA/Boeing production visualization (DELMIA; Digital Enterprise Lean Manufacturing Interactive Application) promotes timely, concurrent and collaborative producibility analysis (Boeing)while supporting Upper Stage Design Cycles (NASA). The DELMIA CONOPs visualization reduced overall Upper Stage production flow time at the manufacturing facility by over 100 man-days to 312.5 man-days and helped to identify technical access issues. The NASA/Boeing Interactive Concept of Operations (ICON) provides interactive access to Ares using real mission parameters, allows users to configure the mission which encourages ownership and identifies areas for improvement, allows mission operations or spacecraft detail to be added as needed, and provides an effective, low coast advocacy, outreach and education tool.
This paper will describe the information technologies developed by NASA and NOAA for the February 2016 Sensing Hazards with Operational Unmanned Technology (SHOUT) El Niño Southern Oscillation (ENSO) Campaign. The air vehicle is a NASA Global Hawk UAS, with a primary payload of four instruments, two developed by NASA, two developed by NOAA. The aircraft is based at the NASA Armstrong Flight Research Center, Edwards Air Force Base, California. The payload components are remotely operated by scientists at various facilities, and the data collected downloaded over satellite links in real time for analysis and collaboration. NOAA: Advanced Vertical Atmospheric Profiling System (AVAPS), developed by NCAR, which deploys dozens of dropsondes at altitudes up to 65,000 ft to collect high vertical resolution measurements of the temperature, pressure, relative humidity, and wind speed and direction. NASA: High-Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP), a radar designed to examine the factors of storm intensity: formation, structure and intensification. NOAA: O3 Photometer (UAS-O3), designed specifically for autonomous, precise, and accurate O3 measurements in the upper troposphere and lower stratosphere (UT/LS). NASA JPL: High Altitude MMIC Sounding Radiometer (HAMSR), an atmospheric microwave temperature and humidity sounder instrument that looks at the microwave spectrum.
Objective: Investigate the effects on human performance as a function of scheduling task complexity for novice schedulers creating spaceflight timelines. Background: Future astronauts will be expected to self-schedule, yet will not be experts in creating timelines that meet complex constraints inherent to spaceflight operations. Method: Conducted a within-subject experiment to measure scheduling efficiency, effectiveness, workload and situation awareness while varying scheduling task complexity factors, namely number of constraints and types of constraints. Results: Fifteen participants completed various scheduling problems. Performance differences were identified between the independent variables. There was a main effect due to the number of constraints and type of constraint for efficiency, effectiveness, and workload. Significant interactions were observed in situation awareness and workload for certain types of constraints. Results also suggest that a lower number of constraints may be manageable by novice schedulers when compared to scheduling activities without constraints. Conclusion: Results suggest that novice schedulers performance decreases with high number of constraints and future scheduling aids may have to be targeted to type of constraint. Application: Knowledge on the effect of scheduling task complexity will help design scheduling systems that will enable self-scheduling for future astronauts. It will also inform other domains that conduct complex scheduling, such as nursing and manufacturing.
Problem Statement: The complexity of Gateway systems and of managing the integrated safety analysis have made traditional methods of engineering analysis and design increasingly challenging. To address these challenges, a prototype that integrate Model-Based Systems Engineering (MBSE) with Digital Twin technology has been developed to demonstrate the utilities and functions. Project Goal: Develop a prototype of a Digital Twin Of Gateway ECLSS IMV system to enhance fault management analysis through collaboration, visualization, and simulation. Overall Project Results / Accomplishments: - Developed extension to streamline the integration of SysML models with the Digital Twin platform - Demonstrated the capability to aggregate any relevant information and provide simulation integration within the DT prototype. - Generated digital twin simulation using SysML Activity Diagrams - Implemented a complex trade study use case based on the integrated SysML-Digital Twin infrastructure
Immersive visualization is changing how we explore, communicate, and understand complex scientific systems. In nuclear energy, an area in which data are often multidimensional, time-dependent, and difficult to interpret, virtual reality (VR) represents a powerful and intuitive informational medium. This work introduces a VR-based platform that visualizes the post-shutdown behavior and waste management lifecycle of molten-salt reactors (MSRs), a next-generation reactor type with unique operational and safety characteristics. The platform, built in Unity, is streamed on the Meta Quest 3 headset. It transforms high-fidelity simulation data into an interactive, immersive experience. Users can explore time-dependent reactor characteristics such as nuclide decay, which is a key factor for evaluating reactor waste strategies. The datasets were generated using the MOOSE (Multiphysics Object-Oriented Simulation Environment) framework and then processed through ParaView scripting for smooth integration into Unity. From a visualization standpoint, the platform emphasizes spatial storytelling, temporal exploration, and user-centered interaction. Users can navigate 3D reactor geometries, slice through volumetric data, and manipulate time to observe how physical phenomena evolve. Real-scale rendering and embodied interaction make the experience feel tangible. The interface is designed to be accessible, even to those without nuclear or simulation expertise. This lowers the barrier for stakeholders, policymakers, and the general public, while still supporting expert analysis and collaborative decision-making. This work shows how immersive visualization can function as both a scientific tool and a communication interface. By integrating simulation, processing, and visualization into a cohesive workflow, we offer a scalable framework for immersive scientific storytelling. The modular design supports future extensions to other reactor types and lifecycle stages, from shutdown to long-term storage, making the platform adaptable for both research and outreach.
As a collaborative effort among government aerospace research laboratories an advanced version of a widely used computational fluid dynamics code, OVERFLOW, was recently released. This latest version includes additions to model flexible rotating multiple blades. In this paper, the OVERFLOW code is applied to improve the accuracy of airload computations from the linear lifting line theory that uses displacements from beam model. Data transfers required at every revolution are managed through a Unix based script that runs jobs on large super-cluster computers. Results are demonstrated for the 4-bladed UH-60A helicopter. Deviations of computed data from flight data are evaluated. Fourier analysis post-processing that is suitable for aeroelastic stability computations are performed.