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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

TrustDER: Trusted, Private and Scalable Coordination of Distributed Energy Resources

In this project, the Stanford and SLAC Teams have developed a Trusted, Private and Scalable platform for coordinating Coordination of Distributed Energy Resources (TrustDER). This is a layered system that ensures private, trusted and scalable coordination and monitoring of DERs. It accommodates a variety of resources, such as solar generation, gensets and loads, with a particular focus on battery systems-based resources, as they are a transformational technology experiencing fast growth in adoption by large critical facilities. The platform can be used as standalone or added to existing aggregation systems to enable trust, privacy and resilience. TrustDER consists of layers that address each of the shortcomings of the existing state of the art. Each layer in the platform can operate independently but provides information to the layers above it to enable a novel form of overall coordination architecture. The project consists of several tasks, with each task dedicated to the design of each layer. Task 2 Resource Virtualization defined a software abstraction layer for distributed energy resources (DERs). The goal of this abstraction was to simplify the implementation of algorithms utilizing cooperation of DERs resources in a variety of use cases. Task 3 is on Secure ID for Asset Authentication. Identity Management Systems (IDMS) are a foundational infrastructure for interactions between entities (organizations, users, devices, and services). Secure ID is blockchain-based a distributed identity management system allowing (1) identity provisioning, (2) authentication, (3) authorization, and (4) identity data sharing for IoT-enabled assets on the electricity grid. In this project, the SLAC team focused on designing and testing Keymaker, a protocol for authenticating device identity managed by Secure ID. Task 5 Private and Safe Integration is focused on the design and evaluation of a DER cooperation scheme which allows for the aggregation of DERs without impacting network reliability. The approach is designed based on realistic assumptions regarding data availability, communication infrastructure limitations, and privacy. Task 6 Scalable Distributed Privacy for Information explored how virtualized batteries could be managed privately. Specifically, it examined the case in which a principal provides a partitioned battery to multiple clients. Task 7 Use Cases was to ensure that this technology was applied in relevant situations and scenarios. Primarily, this means that virtualization needed to be employed in a manner that either improved flexibility, bolstered security or privacy, or decreased costs.

25 ENERGY STORAGE↗
DOE OSTI2023

Open Building Operating System: An Open-Source Grid Responsive Control Platform for Buildings

Grid-interactive efficient buildings (GEBs) with flexible loads are a promising method to decarbonize buildings, shift loads during peak hours, and lower energy use and electricity costs. Despite the promising benefits of GEBs, automation systems that manage flexible loads in response to energy prices or other grid signals are still uncommon in small and medium commercial buildings. Recent literature demonstrates such control solutions, but they often rely on custom integrations lacking the tools and drivers needed for scalability. To address these gaps, our team has created a fully open-source software stack capable of integrating heterogeneous flexible building loads and implementing integrated portable control applications called the Open Building Operating System (OpenBOS). The software can be deployed over existing control architecture with a small capital cost. OpenBOS leverages semantic models, which have been the subject of recent investigations to facilitate application portability. The use of semantic data reduces the labor and expense required to deploy and update smart control applications, increasing scalability. In this paper, the semantic modeling schema "Brick" was used, but the proposed approach can also be applied to ASHRAE standard 223P, when released. This paper describes the methodology and software components of OpenBOS and demonstrates its functionality with a rule-based demand flexibility control application configured using a semantic model. This application was tested at a real building in NY that uses a dual-fuel heating system made up of five ductless heat pump mini-splits and a central furnace serving a single zone. The demonstration reduced electricity costs at the site by 27%, demand during a shed event by 49%, and furnace usage by 35%.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2009

Distributed Health Monitoring System for Reusable Liquid Rocket Engines

The ability to correctly detect and identify any possible failure in the systems, subsystems, or sensors within a reusable liquid rocket engine is a major goal at NASA John C. Stennis Space Center (SSC). A health management (HM) system is required to provide an on-ground operation crew with an integrated awareness of the condition of every element of interest by determining anomalies, examining their causes, and making predictive statements. However, the complexity associated with relevant systems, and the large amount of data typically necessary for proper interpretation and analysis, presents difficulties in implementing complete failure detection, identification, and prognostics (FDI&P). As such, this paper presents a Distributed Health Monitoring System for Reusable Liquid Rocket Engines as a solution to these problems through the use of highly intelligent algorithms for real-time FDI&P, and efficient and embedded processing at multiple levels. The end result is the ability to successfully incorporate a comprehensive HM platform despite the complexity of the systems under consideration.

Lin, C. F.↗
DOE OSTI2013

Enhanced LAW Glass Formulation Testing (Final Report)

The principal objective of this work was to extend the glass formulation methodology developed in the earlier work for Envelope A, B and C waste compositions for development of compliant glass compositions targeting five high sodium-sulfur waste loading regions. This was accomplished through a combination of crucible-scale tests, and tests on the DM10 melter system. The DM10 was used for several previous tests on LAW compositions to determine the maximum feed sulfur concentrations that can be processed without forming secondary sulfate phases on the surface of the melt pool. This melter is the most efficient melter platform for screening glass compositions over a wide range of sulfate concentrations and therefore was selected for the present tests. The tests were conducted to provide information on melter processing characteristics and off-gas data, including sulfur incorporation and partitioning. As described above, the main objective was to identify the limits of waste loading in compliant glass formulations spanning the range of expected Na 2 O and SO 3 concentrations in the LAW glasses.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

AI-Based Analytics and Energy Modeling Framework for Characterizing Urban Energy Systems

Developing location-specific district energy models is essential for understanding energy patterns and supporting efficient management and planning decisions. However, accurately characterizing these models remains challenging due to gaps in building characteristics and labor-intensive traditional modeling workflows. To address these challenges, we develop an AI-based framework that integrates top-down and bottom-up building energy data to automate urban energy model characterization. The framework trains multimodal deep learning models using heterogeneous ResStockTM datasets to infer missing building characteristics from varying levels of known information and generate simulation-ready inputs for district-scale energy modeling. It also employs a conditioning-based injection approach to generate ”what-if” scenarios, enabling users to explore retrofit, efficiency, and technology-upgrade pathways. Integrated within URBANoptTM, a bottom-up district energy modeling platform for simulating co-located buildings, the framework infers detailed building-level inputs required for bottom-up simulations. Both localized and generalized AI models are developed to learn relationships across categorical, numerical, and time-series data, enabling reconstruction of missing attributes and generation of targeted upgrade scenarios. We demonstrate this methodology on a residential neighborhood in Baltimore, MD, assessing internal consistency against ResStock reference data and URBANopt simulation, and comparing selected attributes against real-world building characteristics. Results show strong overall predictive accuracy in data completion and scenario generation, with localized and generalized models offering complementary trade-offs between precision and scalability. Overall, our automated framework streamlines energy modeling and provides a reliable framework for urban building energy characterization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2008

PrismTech Data Distribution Service Java API Evaluation

My internship duties with Launch Control Systems required me to start performance testing of an Object Management Group's (OMG) Data Distribution Service (DDS) specification implementation by PrismTech Limited through the Java programming language application programming interface (API). DDS is a networking middleware for Real-Time Data Distribution. The performance testing involves latency, redundant publishers, extended duration, redundant failover, and read performance. Time constraints allowed only for a data throughput test. I have designed the testing applications to perform all performance tests when time is allowed. Performance evaluation data such as megabits per second and central processing unit (CPU) time consumption were not easily attainable through the Java programming language; they required new methods and classes created in the test applications. Evaluation of this product showed the rate that data can be sent across the network. Performance rates are better on Linux platforms than AIX and Sun platforms. Compared to previous C++ programming language API, the performance evaluation also shows the language differences for the implementation. The Java API of the DDS has a lower throughput performance than the C++ API.

Riggs, Cortney↗
DOE OSTI2016

Stem Inc. SunShot Incubator Program Final Technical Report

In this Energy Storage Control Algorithms project, Stem sought to develop tools and control algorithms to increase the value and reduce balance-of-system and grid integration costs associated with adding distributed solar generation to the grid. These advances fell under the headings SolarScope and SolarController. Stem sought to create initial market traction with a fully commercialized product for the solar industry to size storage systems (SolarScope) as well as a solar intermittency-mitigation framework for utilities (SolarController) in the course of the project. The company sought to align strategic growth plans and enable the rollout of the products to broader audiences in multiple geographic regions by leveraging the major solar companies in the national market as partners. Both final products were both intended to be commercialized. They are: SolarScope: Analysis tool to identify viable PV + storage projects and thereby expedite the sales and interconnection processes. SolarScope combines customer load data, PV production estimates, utility rate tariff, and simulated storage into a simple user interface for PV developers. Developers can easily identify viable solar + storage sites without the need for complex and time consuming, site-by-site spreadsheet modeling. SolarContoller: Tool to autonomously dispatch distributed storage in order to mitigate voltage fluctuation and reduce curtailment. SolarController co-optimizes, in real time, storage dispatch for circuit stability and curtailment reduction, enabling higher penetrations of PV. SolarController is automated, not requiring utility dispatch or management, as Stem hardware senses grid voltage, frequency, customer load, PV production, and power factor. In the end the two products met with different outcomes. SolarScope was tested by potential users, and continues to be used as a foundational platform for partnership with key solar industry partners. SolarController, on the other hand, was successful in lab testing but was not commercialized due to a lack of marketability and lack of interested customer base. Together the development of these two products marked a material step forward for Stem; and a new milestone along the pathway of integration for the solar and storage industries. SolarScope is leading to real, out-of-the-lab project development in storage + solar for the commercial customer sector. Meanwhile SolarController has opened the eyes of regulators and utility executives alike to the potential of distributed solar and by doing so, has moved the conversation forward for the integration of distributed energy resources more broadly on the grid.

25 ENERGY STORAGE↗
DOE OSTI2015

GRDC. A Collaborative Framework for Radiological Background and Contextual Data Analysis

The Radiation Mobile Analysis Platform (RadMAP) is unique in its capability to collect both high quality radiological data from both gamma-ray detectors and fast neutron detectors and a broad array of contextual data that includes positioning and stance data, high-resolution 3D radiological data from weather sensors, LiDAR, and visual and hyperspectral cameras. The datasets obtained from RadMAP are both voluminous and complex and require analyses from highly diverse communities within both the national laboratory and academic communities. Maintaining a high level of transparency will enable analysis products to further enrich the RadMAP dataset. It is in this spirit of open and collaborative data that the RadMAP team proposed to collect, calibrate, and make available online data from the RadMAP system. The Berkeley Data Cloud (BDC) is a cloud-based data management framework that enables web-based data browsing visualization, and connects curated datasets to custom workflows such that analysis products can be managed and disseminated while maintaining user access rights. BDC enables cloud-based analyses of large datasets in a manner that simulates real-time data collection, such that BDC can be used to test algorithm performance on real and source-injected datasets. Using the BDC framework, a subset of the RadMAP datasets have been disseminated via the Gamma Ray Data Cloud (GRDC) that is hosted through the National Energy Research Science Computing (NERSC) Center, enabling data access to over 40 users at 10 institutions.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
NASA NTRS2003

An Architectural Concept for Intrusion Tolerance in Air Traffic Networks

The goal of an intrusion tolerant network is to continue to provide predictable and reliable communication in the presence of a limited num ber of compromised network components. The behavior of a compromised network component ranges from a node that no longer responds to a nod e that is under the control of a malicious entity that is actively tr ying to cause other nodes to fail. Most current data communication ne tworks do not include support for tolerating unconstrained misbehavio r of components in the network. However, the fault tolerance communit y has developed protocols that provide both predictable and reliable communication in the presence of the worst possible behavior of a limited number of nodes in the system. One may view a malicious entity in a communication network as a node that has failed and is behaving in an arbitrary manner. NASA/Langley Research Center has developed one such fault-tolerant computing platform called SPIDER (Scalable Proces sor-Independent Design for Electromagnetic Resilience). The protocols and interconnection mechanisms of SPIDER may be adapted to large-sca le, distributed communication networks such as would be required for future Air Traffic Management systems. The predictability and reliabi lity guarantees provided by the SPIDER protocols have been formally v erified. This analysis can be readily adapted to similar network stru ctures.

Maddalon, Jeffrey M.↗
DOE OSTI2025

Site and endmember spectra of terrestrial vegetation and soils for the Colorado Headwaters Ecological Spectroscopy Study, June-July 2025

This dataset provides site and endmember spectra collected during the 2025 Colorado Headwaters Ecological Spectroscopy Study (CHESS) campaign. The site spectra were collected to help validate airborne hyperspectral data acquired by the National Ecological Observatory Network's aerial observation platform (NEON AOP). Endmember spectra were collected to augment existing spectral libraries with additional samples of bare surfaces and non-photosynthetic vegetation. All measurements were acquired with an Analytical Spectral Devices (ASD) FieldSpec4 Hi-Res NG (Next Generation) spectroradiometer, which records radiance at 1nm (nanometer) intervals from the ultraviolet to the short-wave infrared (350-2500 nm). The dataset includes spectra measured at meadow sites where the CHESS team also collected vegetation samples for trait analyses. The site spectra were collected with the ASD FieldSpec4 palm grip attachment using an 8° field-of-view foreoptic. Site spectra are integrated measurements of the entire surface within the foreoptic’s field of view. For site-level spectra, the sun is the illumination source. A Spectralon panel mounted on a tripod was used for instrument optimization and white reference measurements for all site spectra. Site spectra were acquired within two hours of solar noon and within 48 hours of a NEON AOP overflight. Site spectra are labeled by date, sampling area, and site number according to the naming conventions of the CHESS campaign’s data management plan. The dataset also contains endmember spectra in the following categories: photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV), bare (soil/rock), and flowers. Endmember measurements were acquired using either the contact probe or the leaf clip attachments of the ASD FieldSpec4. In these configurations, the bulb inside the spectrometer provides the light source for the measurements. The spectrometer was optimized and white reference measurements were recorded using the circular white pucks attached to the contact probe and leaf clip. Because they do not rely on solar illumination, contact probe and leaf clip measurements were collected during a broader time frame than the palm grip site spectra. Some endmembers were measured at CHESS meadow sites, while others were collected within the larger sampling area or in nearby locations (e.g. Gothic Townsite) with similar characteristics. Radiance, reflectance, and metadata files are split into three subfolders according to measurement type: proximal/palm grip (prx), contact probe (cp), and leaf clip (lc). Radiance spectra are provided in ASD file format (.asd file extension). All ASD files can be opened using the provided scripts. Metadata is provided in two formats: CSV file format (no geolocation) and GEOJSON file format (includes geolocation for each spectra). The dataset includes a set of pre-processed reflectance spectra as CSV files (yyyymmdd_rfl.csv). The python scripts and jupyter notebook used to calculate reflectance spectra from the ASD radiance data is included here and was previously published at: https://doi.org/10.3334/ORNLDAAC/2446. There is also a folder of JPEG photographs corresponding to selected spectra. We include a protocol document with detailed steps for ASD FieldSpec4 assembly and operations. This data additionally contains a file level metadata (flmd.csv) and data dictionary (dd.csv) file. Geospatial information: Geospatial data for mapping measurement site locations are in the files CHESS_polygons_lai_UTM.geojson, CHESS_polygons_shrub_UTM.geojson, and CHESS_polygons_meadow_UTM.geojson in the companion geospatial package for the 2025 CHESS campaign, ‘CHESS 2025: Location data for field observations and sampling’ (Henderson et al., 2026). CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgment: This research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004) and was funded by EMIT Extended Mission Phase E Science.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2013

North Slope Decision Support for Water Resource Planning and Management (Final Technical Report)

The objective of this project was to enhance the water resource decision-making process with respect to oil and gas exploration/production activities on Alaska’s North Slope. To this end, a web-based software tool was developed to allow stakeholders to assemble, evaluate, and communicate relevant information between and amongst themselves. The software, termed North Slope Decision Support System (NSDSS), is a visually-referenced database that provides a platform for running complex natural system, planning, and optimization models. The NSDSS design was based upon community input garnered during a series of stakeholder workshops, and the end product software is freely available to all stakeholders via the project website. The tool now resides on servers hosted by the UAF Water and Environmental Research Center, and will remain accessible and free-of-charge for all interested stakeholders. The development of the tool fostered new advances in the area of data evaluation and decision support technologies, and the finished product is envisioned to enhance water resource planning activities on Alaska’s North Slope.

02 PETROLEUM↗
DOE OSTI2020

Development of the Intelligent, Preventive Infrared (IR) Inspection System Housed in Hybrid Robotic Platforms

Robots and robotic systems that are designed for inspection, environmental study, and health and safety aid are becoming an increasing necessity. However, there is a number of challenges that accompany robots that are designed for these specific applications. These challenges include: navigating compact, enclosed spaces, travelling over multiple terrains and large obstacles, using the proper sensing and detection methods to assess an environment, and the use of lightweight and durable materials. The robotic platforms currently in development look at all of these challenges and attempt to overcome them. These designs specific use of hybrid robotic platforms, or platform that utilizes soft and rigid materials, allows for a more flexible platform and makes environments more navigable. To further improve the navigation of the platforms and environmental assessment, a novel infrared detection system is housed in the platforms to create a robot that can be used for the applications listed above and more. Objectives: Further develop two types of robotic platforms that utilize additive manufacturing, soft materials, and rigid materials. Continue the development of an intelligent and inhibitory infrared detection system based on an artificial intelligence (AI) algorithm. Continued study and fabrication of active soft materials designed for both sensing and actuation in hybrid robotic systems. Improve additive manufacturing fabrication to design rigid and semi-rigid components for hybrid robotic platforms. Transformable Wheel Robotic Platform: The chassis, wheels, tires and inspection system housing use different additive manufacturing techniques for fabrication. Continued work with additive manufacturing has lead to studies in metal-based printing and modular design and manufacturing. The new platform design with integrated electrical component printed. This will allow integration of the sensor housing onto the platform. Electrical components are being tested for battery life and performance. To improve this performance, such as integration of Lithium Polymer (LiPo) batteries. Snake Robotic Platform: The main focus of the development has centered around liquid-based soft actuators. That act on the principles of electrostatic and hydraulic actuation. A liquid dielectric sits between two compliant electrodes, contained by a flexible polymer shell. The electrodes and film gradually collapse toward each other from one corner of the electrode to the other. When the electrodes and film close together, a majority of the fluid is pushed into the area not covered by an electrode. A thin layer of the liquid dielectric remains between the electrode. The actuators will be stacked to cause large displacement, and move the linkages. The chassis of this platform uses purely additively manufactured linkages. Intelligent, Preventive IR Inspection System: Development of the AI for the system has lead to using a Scikit-Learn which assists in creating predictive models based on Regression, clustering, classification etc. To improve the infrared thermometry for low emissivity sources, work on the fabrication of a tandem photoconductive infrared thermometer was a main focus. Distance-Voltage-Temperature response data has been collected in the range of 7 cm - 100 cm and 200-400 deg. C. Modifications were made to the existing test bench to have a better control over the data. Automated data collection was realized using a Python code and an Arduino controlled stepper motor to increase the sample rate. A protective enclosure has been built around the setup to minimize the effect of the environment on the measurements. To better predict temperature, different AI models are being optimized. The regression model, LARS showed a high accuracy but had convergence issues and only works for the current test set-up. Results: The Transformable Wheel Robot has developed into a more flexible and modular platform. With the improvements to the current work, effort on the tire or soft gripper design been a large focus. The soft grippers will be interchange able to allow for increased performance in identified terrain types. The development of the liquid-based actuators allows the snake robotic platform to achieve the goals of being flexible and able to navigate confined spaces. However, there is room for improvement. Optimization work is currently being done in COMSOL Multiphysics. With the current IR system set-up the LARS model perfectly predicts the data; however, considering the mobility aspect of the project other models will allow for an optimized system. Testing of other model types is currently being done.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

3-D Radiation Mapping and Data Fusion for Environmental Remediation and Cleanup - 18449

Recent developments in radiation detection and imaging in combination with the enormous advances in computer vision and data processing enable new and improved means in the assessment of radiological contamination relevant for environmental remediation. We have developed a new concept called 3-D Scene Data Fusion (SDF) that allows us to map scenes in three dimensions and fuse this scene data with nuclear radiation data in near real time while the instrument is freely moving through the scene. This new technology provides more accurate radio-isotopic mapping at higher speed than currently possible. SDF is designed to be independent of the deployment platform and can be implemented with gamma-ray imaging and non-imaging instruments. We have demonstrated this concept in a large range of configurations on unmanned aerial and ground-based systems, in hand-portable configurations or mounted on cars or manned helicopters. While it can be utilized in a wide range of applications, this paper focuses on the mapping of radiological and nuclear materials in the context of environmental remediation and clean-up specifically in urban environments. We show results from measurements in the evacuated areas in the Fukushima Prefecture to demonstrate the new concept in the mapping of contamination and hot spots and the verification of decontamination activities in urban environments. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1991

Feasibility of using a knowledge-based system concept for in-flight primary flight display research

A study was conducted to determine the feasibility of using knowledge-based systems architectures for inflight research of primary flight display information management issues. The feasibility relied on the ability to integrate knowledge-based systems with existing onboard aircraft systems. And, given the hardware and software platforms available, the feasibility also depended on the ability to use interpreted LISP software with the real time operation of the primary flight display. In addition to evaluating these feasibility issues, the study determined whether the software engineering advantages of knowledge-based systems found for this application in the earlier workstation study extended to the inflight research environment. To study these issues, two integrated knowledge-based systems were designed to control the primary flight display according to pre-existing specifications of an ongoing primary flight display information management research effort. These two systems were implemented to assess the feasibility and software engineering issues listed. Flight test results were successful in showing the feasibility of using knowledge-based systems inflight with actual aircraft data.

Ricks, Wendell R.↗
DOE OSTI2019

A Comparison of GoldSim, RESRAD-Onsite, and NORMALYSA Modeling Tools at Radioactive Waste Sites - 19480

Radioactive waste disposal and associated decision making is a challenging problem around the world. A strong performance assessment model plays a crucial role in making good management and remediation decisions and in optimizing the performance of a site. The International Atomic Energy Agency (IAEA) MODARIA II Working Group 1 (WG1) is comparing the performance of various modeling platforms used at Naturally Occurring Radioactive Material (NORM) and legacy waste sites to support risk-informed decision making. Neptune and Company, Inc. (Neptune) has developed probabilistic performance assessment models using the GoldSim system modeling software at a variety of radioactive waste sites. This paper presents a comparison between GoldSim and two other tools used to evaluate radiation exposure and their associated risks: the NORM And Legacy Site Assessment (NORMALYSA) tool used to assess risk at the Zapadnoe mill tailings site, and the residual radioactivity (RESRAD-Onsite) computer program used to calculate Authorized Limits at the Los Alamos National Laboratory (LANL). The International Atomic Energy Agency (IAEA) supported development of NORMALYSA based off of Ecolego 6.0, in which the user connects several universal modules, representing various environmental transport and exposure pathways, and enters in site-specific data. Further work with NORMALYSA has continued under the MODARIA II WG 1. A radionuclide transport and dose calculation model of the Zapadnoe uranium mill tailings site at the Pridneprovsky Chemical Plant in the Ukraine has been configured by MODARIA II WG1 to test the capabilities of NORMALYSA. Under this test case, contaminant transport and effective dose calculations were performed for two exposure scenarios. The onsite worker is exposed via external ground irradiation and radon and radioactive dust inhalation. The offsite resident defines a residence established 300 years after institutional control has ended, 800 meters downstream from the site with exposure pathways including: ingestion of garden vegetables irrigated by contaminated ground water, ingestion of fish from the Konoplyanka River and agricultural activities in the contaminated garden. GoldSim modeling software is a dynamic probabilistic modeling platform that evaluates uncertainty in a robust and transparent manner. Although GoldSim provides contaminant and radionuclide transport modules to facilitate integrated modeling of radionuclide migration in the environment, these features are not embedded in an existing modeling framework, except as created by the user. Neptune developed a GoldSim model for the two exposure scenarios of the Zapadnoe test case. Neptune's Generic PA Model was used as a starting point for the Zapadnoe site. Input parameters for the GoldSim model include site-specific parameters from the MODARIA Working Group as well as parameters from the Generic PA Model and other PA models created by Neptune. For the other comparison, Version 7.0 of RESRAD-Onsite, developed by Argonne National Laboratory for the U.S. Department of Energy (DOE), was used to calculate Authorized Limits for LANL. Authorized Limits are concentrations of radionuclides in soil that support the evaluation process to clear land for release under different uses. The RESRAD-Onsite computer code was used to calculate Authorized Limits because this program was specifically designed to derive radionuclide soil guidelines corresponding to a specific dose criterion. The scope of the RESRAD dose or risk evaluation is constrained to the transport and exposure pathways that have been included in the computer code. To assist in illustrating the capability of GoldSim modeling software, a GoldSim model was created to replicate the calculation of LANL's Authorized Limits for soil. The main exposure pathways in this model are inhalation of dust and gas, plant ingestion, soil ingestion, and external ground irradiation. All of the processes and outputs of RESRAD-Onsite and NORMALYSA can be created in a GoldSim model, but the value of GoldSim lies in its flexibility for application to any of a wide variety of environmental modeling problems. GoldSim allows development of site-specific inventory, transport mechanisms and risk assessment scenarios. If all potentially complete release, transport, and exposure pathways are addressed in an existing dose and risk assessment computer code, and if the code's capabilities fulfill the project modeling objectives, then expending resources to create a GoldSim model may not be necessary. Site optimization and good decision making about site management are often best when supported with the flexibility of GoldSim as a modeling tool. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Sparse Matrix-Matrix Multiplication on Multilevel Memory Architectures: Algorithms and Experiments

Architectures with multiple classes of memory media are becoming a common part of mainstream supercomputer deployments. So called multi-level memories offer differing characteristics for each memory component including variation in bandwidth, latency and capacity. This paper investigates the performance of sparse matrix multiplication kernels on two leading highperformance computing architectures — Intel's Knights Landing processor and NVIDIA's Pascal GPU. We describe a data placement method and a chunking-based algorithm for our kernels that exploits the existence of the multiple memory spaces in each hardware platform. We evaluate the performance of these methods w.r.t. standard algorithms using the auto-caching mechanisms Our results show that standard algorithms that exploit cache reuse performed as well as multi-memory-aware algorithms for architectures such as Ki\iLs where the memory subsystems have similar latencies. However, for architectures such as GPUS where memory subsystems differ significantly in both bandwidth and latency, multi-memory-aware methods are crucial for good performance. In addition, our new approaches permit the user to run problems that require larger capacities than the fastest memory of each compute node without depending on the software-managed cache mechanisms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Elastic Stochastic Full Waveform Inversion (eSFWI)

This collaboration between Lawrence Livermore National Security, LLC (LLNS) as manager and operator of Lawrence Livermore National Laboratory (LLNL) and Chevron USA Inc., acting through its Chevron Technical Center division, aimed at developing next-generation computational methods for the Elastic Stochastic Full Waveform Inversion (eSFWI). Seismic imaging is heavily used in the oil and gas industry for identifying and operating subsurface reservoirs. Improved seismic imaging methods can improve productivity, lower costs, and improve operational and environmental safety. This CRADA demonstrated that new high-performance computing (HPC) architectures being rolled out over the next five years can enable unprecedented seismic imaging resolution when using eSFWI techniques to process active seismic data. An open-source computational mini-application was developed, capable of demonstrating near-peak performance for eSFWI algorithms on CPU and GPU enabled HPC platforms. Performance was demonstrated on LLNL HPC systems such as Lassen, as well as on Chevron systems. This project benefited Chevron USA Inc. by demonstrating the potential computational efficiency of their full waveform inversion capabilities used to characterize oil/gas reservoirs, which in turn benefits the public through potential increases in capabilities to perform analysis of leasing sites.

04 OIL SHALES AND TAR SANDS↗
NASA NTRSDate not supplied

An Overview of NASA’s Catalog of Archived Suborbital Earth Science Investigations (CASEI): Supporting FAIR and Open Access to Airborne and Field Data

Since 2019, NASA’s Airborne Data Management Group (ADMG) within the Interagency Implementation and Advanced Concepts Team (IMPACT) has worked to promote and ensure the discoverability and accessibility of the agency’s non-satellite Earth science observations. A primary component of this effort is the development of NASA’s Catalog of Archived Suborbital Earth Science Investigations (CASEI) and the vetting of key contextual details required to sustain this unique inventory of airborne and field metadata. CASEI provides information on the science objectives motivating data collection, key events/time periods in the observational record aligned with the science objectives, complementary simultaneous observations, programmatic details, and much more. The diverse set of data formats and disciplines served by CASEI have required the implementation of a common data model to organize suborbital observation metadata and efficiently connect appropriate campaigns, platforms, and instruments. The CASEI inventory provides a single entry point for users to search and browse NASA’s airborne and field data archives, regardless of which repository is responsible for their stewardship. This presentation will provide a summary of the motivations for and the development of the CASEI system. Particular attention will be granted to how CASEI facilitates discovery and reuse of these lesser-known NASA data, supporting the Open Science vision and enhancing the return on investments made to collect these unique and varied observations. An up-to-date summary of CASEI inventory content and initial metrics will be provided. Current and future avenues ADMG is pursuing to enhance both CASEI and specific components of suborbital data stewardship at various stages of the data life cycle will also be discussed.

Stephanie M. Wingo↗