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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Multiscale and Machine Learning Modeling for Additive Manufacturing

Additive manufacturing (AM) techniques provide the opportunity to simultaneously design new materials and components with complex structures in less time, enabling faster material developments. Even though compositionally similar, the texture of the materials produced by such techniques is significantly different from conventionally manufactured materials. Additively manufactured materials produces highly heterogeneous microstructure within a single build. Such variations in the microstructure make qualifying AM products challenging for extreme environment applications. Understanding the AM process and its influence on the materials’ microstructures/properties is paramount for evaluating the workability and performance of the manufactured materials. The performance of AM materials for advanced nuclear reactor applications is of interest to the Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy. Hence, considering the microstructural variabilities in the AM products and their impact on the performance of the material, it is important to correlate the process conditions to the final product and establish a process-structure-property- performance (PSPP) correlation for AM materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1993

Exploration planning in the context of human exploration and development of the Moon

It is widely believed that the next step beyond low Earth orbit in attaining the United States' stated goal of 'Expanding human presence beyond the Earth' should be to reestablish a lunar capability, building on the Apollo program, and preparing the way for eventual human missions to Mars. The Moon offers important questions in planetary and Earth science, can provide a unique platform for making astronomical observations of high resolution and sensitivity, and can be in the development path for unlocking resources of the inner solar system to support space activities and return benefits to Earth. NASA's Office of Exploration has undertaken the planning of future lunar exploration missions with the assistance of the Solar System Exploration Division in matters dealing with the quality of scientific data and the manner in which it will be made available to the scientific community. The initial elements of the proposed program include the Lunar Scout missions, which consist of two small identical spacecraft in polar orbit around the Moon, which can accomplish most of the objectives associated with previous proposals for Lunar Polar Orbiters. These missions would be followed by 'Artemis' landers, capable of emplacing up to 200 kg payloads anywhere on the Moon. In addition, the exploration program must incorporate data obtained from other missions, including the Galileo lunar flybys, the Clementine high orbital observations, and Japanese penetrator missions. In the past year, a rather detailed plan for a 'First Lunar Outpost (FLO)' which would place 4 astronauts on the lunar surface for 45 days has been developed as a possible initial step of a renewed human exploration program. In the coming year, the FLO concept will be reviewed and evolved to become more highly integrated with planning for the initial human exploration of Mars, which could come perhaps 5 years after the reestablishment of lunar capability. Both programs could benefit from the common development of systems and subsystems, where that is sensible from a performance perspective.

Duke, Michael B.↗
NASA NTRS2002

Activation Energy

Teaming is so common in today's project management environment that most of us assume it comes naturally. We further assume that when presented with meaningful and challenging work, project teams will naturally engage in productive activity to complete their tasks. This assumption is expressed in the simple (but false) equation: Team + Work = Teamwork. Although this equation appears simple and straightforward, it is far from true for most project organizations whose reality is a complex web of institutional norms based on individual achievement and rewards. This is illustrated by the very first successful team experience from my early Air Force career. As a young lieutenant, I was sent to Squadron Officer School, which was the first in the series of Air Force professional military education courses I was required to complete during my career. We were immediately formed into teams of twelve officers. Much of the course featured competition between these teams. As the most junior member of my team, I quickly observed the tremendous pressure to show individual leadership capability. At one point early in the course, almost everyone in our group was vying to become the team leader. This conflict was so intense that it caused us to fail miserably in our first outdoor team building exercise. We spent so much time fighting over leadership that we were unable to complete any of the events on the outdoor obstacle course. This complete lack of success was so disheartening to me that I gave our team little hope for future success. What followed was a very intense period of bickering, conflict, and even shouting matches as our dysfunctional team tried to cope with our early failures and find some way to succeed. British physician and researcher Wilfred Bion (Experiences in Groups, 1961) discovered that there are powerful psychological forces inherent in all groups that divert from accomplishing their primary tasks. To overcome these restraining forces and use the potential power of the team, greater emphasis must be placed on establishing and maintaining group cohesiveness. This relationship is expressed in the revised (true) mathematical equation: Team + Work (on the Team) = Teamwork.

Gadeken, Owen↗
NASA NTRS2004

Performance of a Fuel-Cell-Powered, Small Electric Airplane Assessed

Rapidly emerging fuel-cell-power technologies may be used to launch a new revolution of electric propulsion systems for light aircraft. Future small electric airplanes using fuel cell technologies hold the promise of high reliability, low maintenance, low noise, and - with the exception of water vapor - zero emissions. An analytical feasibility and performance assessment was conducted by NASA Glenn Research Center's Airbreathing Systems Analysis Office of a fuel-cell-powered, propeller-driven, small electric airplane based on a model of the MCR-01 two-place kitplane (Dyn'Aero, Darois, France). This assessment was conducted in parallel with an ongoing effort by the Advanced Technology Products Corporation and the Foundation for Advancing Science and Technology Education. Their project - partially funded by a NASA grant - is to design, build, and fly the first manned, continuously propelled, nongliding electric airplane. In our study, an analytical performance model of a proton exchange membrane (PEM) fuel cell propulsion system was developed and applied to a notional, two-place light airplane modeled after the MCR-01 kitplane. The PEM fuel cell stack was fed pure hydrogen fuel and humidified ambient air via a small automotive centrifugal supercharger. The fuel cell performance models were based on chemical reaction analyses calibrated with published data from the fledgling U.S. automotive fuel cell industry. Electric propeller motors, rated at two shaft power levels in separate assessments, were used to directly drive a two-bladed, variable-pitch propeller. Fuel sources considered were compressed hydrogen gas and cryogenic liquid hydrogen. Both of these fuel sources provided pure, contaminant-free hydrogen for the PEM cells.

Berton, Jeffrey J.↗
NASA NTRS2006

Can We Power Future Mars Missions?

The Vision for Space Exploration identified the exploration of Mars as one of the key pathways. In response, NASAs Mars Program Office is developing a detailed mission lineup for the next decade that would lead to future explorations. Mission architectures for the next decade include both orbiters and landers. Existing power technologies, which could include solar panels, batteries, radioisotope power systems, and in the future fission power, could support these missions. Second and third decade explorations could target human precursor and human in-situ missions, building on increasingly complex architectures. Some of these could use potential feed forward from earlier Constellation missions to the Moon, discussed in the ESAS study. From a potential Mars Sample Return mission to human missions the complexity of the architectures increases, and with it the delivered mass and power requirements also amplify. The delivered mass at Mars mostly depends on the launch vehicle, while the landed mass might be further limited by EDL technologies, including the aeroshell, parachutes, landing platform, and pinpoint landing. The resulting in-situ mass could be further divided into payload elements and suitable supporting power systems. These power systems can range from tens of watts to multi-kilowatts, influenced by mission type, mission configuration, landing location, mission duration, and season. Regardless, the power system design should match the power needs of these surface assets within a given architecture. Consequently, in this paper we will identify potential needs and bounds of delivered mass and architecture dependent power requirements to surface assets that would enable future in-situ exploration of Mars.

solar panels↗
NASA NTRS2018

Impact of Powder Variability on the Microstructure and Mechanical Behavior of Selective Laser Melted (SLM) Alloy 718

Nickel Alloy 718 has found wide use in high-temperature aerospace applications (up to 700°C), due to a combination of good mechanical properties, environmental resistance, and workability at moderate cost. These properties have led Alloy 718 to early adoption by selective laser melting (SLM) additive manufacturing. This presentation will share results from a comprehensive industry survey of 718 powder feedstock for SLM. The survey focuses on the impact of variability in powder characteristics on build quality, microstructure, tensile and high cycle fatigue in the as-fabricated and machined surface conditions. The investigation includes sixteen powder lots from eight suppliers that are produced by gas atomization or rotary atomization in argon or nitrogen. This research was previously presented and published at the 9th International Symposium on Superalloy 718 & Derivatives and was funded by NASA Space Launch System Liquid Engine Office with the Human Exploration Operations Mission Directorate.

Sudbrack, Chantal↗
NASA NTRS1989

Development of a funding, cost, and spending model for satellite projects

The need for a predictive budget/funging model is obvious. The current models used by the Resource Analysis Office (RAO) are used to predict the total costs of satellite projects. An effort to extend the modeling capabilities from total budget analysis to total budget and budget outlays over time analysis was conducted. A statistical based and data driven methodology was used to derive and develop the model. Th budget data for the last 18 GSFC-sponsored satellite projects were analyzed and used to build a funding model which would describe the historical spending patterns. This raw data consisted of dollars spent in that specific year and their 1989 dollar equivalent. This data was converted to the standard format used by the RAO group and placed in a database. A simple statistical analysis was performed to calculate the gross statistics associated with project length and project cost ant the conditional statistics on project length and project cost. The modeling approach used is derived form the theory of embedded statistics which states that properly analyzed data will produce the underlying generating function. The process of funding large scale projects over extended periods of time is described by Life Cycle Cost Models (LCCM). The data was analyzed to find a model in the generic form of a LCCM. The model developed is based on a Weibull function whose parameters are found by both nonlinear optimization and nonlinear regression. In order to use this model it is necessary to transform the problem from a dollar/time space to a percentage of total budget/time space. This transformation is equivalent to moving to a probability space. By using the basic rules of probability, the validity of both the optimization and the regression steps are insured. This statistically significant model is then integrated and inverted. The resulting output represents a project schedule which relates the amount of money spent to the percentage of project completion.

Johnson, Jesse P.↗
DOE OSTI2020

Issue Resolution During the Development of the Performance Assessment for the Savannah River Site Saltstone Disposal Facility - 20125

In 2019, Savannah River Remediation developed a revision to the performance assessment (PA) on behalf of the U.S. Department of Energy (DOE) Savannah River Operations Office (SR) for the near-surface disposal of low-level waste at the Savannah River Site (SRS) Saltstone Disposal Facility (SDF). Soluble waste from SRS Tank Farms undergoes salt processing to remove cesium and other high-activity constituents. The low-activity decontaminated salt solution (DSS) is then immobilized by mixing it into a cementitious waste form known as saltstone. After mixing, the saltstone is poured into leak-tight concrete vaults, known as saltstone disposal units (SDUs), where the waste form cures. By the time of facility closure, the SDF is expected to consist of 15 SDUs with a combined capacity of 1.06 E+09 L (280 Mgal) of cured saltstone. The facility operates under a Disposal Authorization Statement from DOE and a permit from the South Carolina Department of Health and Environmental Control (SCDHEC). Since the start of operations in 1990, the SDF has received almost 6.7 E+07 L (18 Mgal) of DSS, resulting in the safe disposal of 2.7 E+16 Bq (7.3 E+05 Ci) of activity. Due to the radioactive decay of short-lived contaminants, the total remaining activity in the disposed waste is estimated to be approximately 1.4 E+16 Bq (3.9 E+05 Ci), as of September 2018. The Disposal Authorization Statement requires a demonstration that the system of engineered and natural features of the disposal facility will limit releases from the facility and be protective of human health and the environment for at least the next 1,000 years. The long-term performance of the facility was evaluated under the requirements of the DoE's Radioactive Waste Management Manual (US DOE Manual 435.1-1). Simulations were performed to demonstrate that the disposal facility would meet performance objectives specified in the manual. The evaluation was based on numerical models that simulate the releases of contaminants from the saltstone waste form. Contaminants were transported through groundwater and air pathways to points of assessment to evaluate compliance (i.e., 100 m from the SDUs). In addition, the potential consequences of an inadvertent human intrusion (IHI) were also evaluated. A number of issues were overcome during the development of these simulations. These issues were identified as part of internal technical reviews. Simulations are developed by people and people make mistakes, so the internal technical review process is a vital step in PA development. Specific examples of resolved issues include a unit-conversion error, an inappropriate definition for a model boundary condition, a model time-stepping issue, and an error in the calculation for the buildup of contaminants in soil. Actions taken to address these issues resulted in an improved product with a better supported technical basis and more defensible results. The identification and correction of these issues are discussed. By understanding these issues, model developers and technical reviewers working on PAs in the future may avoid repeating these types of mistakes. Transparency with respect to these mistakes builds trust between waste management sites, regulators, and stakeholders. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Status of the Top Plate and Anticryostat for High Field Cable Test Facility at Fermilab

Fermi National Accelerator Laboratory (FNAL) and Lawrence Berkeley National Laboratory (LBNL) are building a new High Field Vertical Magnet Test Facility (HFVMTF) for testing superconducting cables in high magnetic field. This facility will be located at Fermilab and will have a capability similar to EDIPO at PSI and FRESCA2 at CERN. The background magnetic field of 15T in HFVMTF will be produced by a magnet pro-vided by LBNL. The HFVMTF is jointly funded by the US DOE Offices of Science, High Energy Physics, and Fusion Energy Sciences. As a primary use it will be superconducting cable test facility, in high magnetic fields and wide range of temperatures. Complementary, this facility will be used to test high-field super-conducting magnet models and demonstrators, including hybrid magnets, produced by the US Magnet Development Program (MDP). The paper describes the status of Top Plates Assembly and Sample Insert Anticryostat, which will be a main interface component between cable test mode and magnet test mode at this facility.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1988

MTK: An AI tool for model-based reasoning

A 1988 goal for the Systems Autonomy Demonstration Project Office of the NASA Ames Research Office is to apply model-based representation and reasoning techniques in a knowledge-based system that will provide monitoring, fault diagnosis, control, and trend analysis of the Space Station Thermal Control System (TCS). A number of issues raised during the development of the first prototype system inspired the design and construction of a model-based reasoning tool called MTK, which was used in the building of the second prototype. These issues are outlined here with examples from the thermal system to highlight the motivating factors behind them, followed by an overview of the capabilities of MTK, which was developed to address these issues in a generic fashion.

Erickson, William K.↗
NASA NTRSDate not supplied

Building a Real-Time Predictive Flood Model for Improving Early Warning Systems in Ellicott City, Maryland

As flood events in the United States grow in frequency and intensity, the use of applied remote sensing analyses is increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP National Program partnered with the Howard County government in Maryland to investigate the use of machine learning for advanced flood risk detection, and to test the feasibility of integrating this approach into the county’s flood early warning system. To strengthen the efforts of the Howard County Office of Emergency Management (OEM), the project developed a prediction model capable of hindcasting the two severe flash flood events that devastated Ellicott City, and transitioned to an Long Short-Term Memory (LSTM) based sequence-to-sequence deep learning model with 8-hour forecast capability. The team combined data inputs from public sources including river and precipitation gauges, NASA and NOAA Earth observations, and numerical weather model products using scripts written in the Google Colaboratory Python scripting environment. In addition to designing the deep learning architecture, the team trained and tested the model, and evaluated its performance using the Nash-Sutcliffe Efficiency (NSE). The final product, called the Sequentially Trained Real-time EstimAted Model (STREAM), predicts stage height for the Hudson Branch gauge in Ellicott City using data products available in near real-time, including the High-Resolution Rapid Refresh (HRRR) model’s accumulated precipitation forecasts supplemented by stream gauge data from the OEM and the U.S. Geological Survey. STREAM was incorporated into an online dashboard in a user-friendly interface capable of triggering the alarms that initiate the OEM’s emergency response protocols up to 8 hours in advance of a predicted severe flood event. The project demonstrated the potential for the integration of open data and Earth observations into a flood risk forecasting tool capable of informing near real-time decision making.

Ryan Hammock↗
NASA NTRSDate not supplied

Building a Real-Time Flood Prediction Model for Improving Early Warning Systems in Ellicott City, Maryland

As flood events in the United States grow in frequency and intensity, the use of applied remote sensing analyses is increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP National Program partnered with the local government of Howard County, Maryland, to investigate the use of machine learning for advanced flood risk detection, and to test the feasibility of integrating this approach into the county’s flood early warning system. To strengthen the efforts of the Howard County Office of Emergency Management (OEM), the project developed a statistical model capable of hindcasting the two severe flash flood events that devastated Ellicott City and transitioned to a ‘Long Short-Term Memory’ based sequence-to-sequence deep learning model with 8-hour forecast capability. The team combined data inputs from public sources including river and precipitation gauges, NASA and NOAA Earth observations, and numerical weather model products using scripts written in the Google Colaboratory Python scripting environment. In addition to designing the deep learning architecture, the team trained and tested the model, and evaluated its performance using Nash-Sutcliffe Efficiency. The final product, the Sequentially Trained Real-time EstimAted Model (STREAM) predicts stage height for the Hudson Branch gauge in Ellicott City using data products available in near real-time, including the High-Resolution Rapid Refresh model’s accumulated precipitation forecasts supplemented by stream gauge data from the OEM and the U.S. Geological Survey. STREAM was incorporated into an online dashboard in a user-friendly interface capable of triggering the alarms that initiate emergency response protocols up to 8 hours in advance of a predicted severe flood event. The project demonstrated the potential for the integration of open data and Earth observations into a flood risk forecasting tool capable of informing near real-time decision making.

NASA DEVELOP↗
DOE OSTI2020

5G Enabled Energy Innovation: Advanced Wireless Networks for Science (Workshop Report)

Rapidly expanding, new telecommunications infrastructure based on 5G technologies will disrupt and transform how we design, build, operate, and optimize scientific infrastructure and the experiments and services enabled by that infrastructure, from continental-scale sensor networks to centralized scientific user facilities, from intelligent Internet of Things devices to supercomputers. Concurrently, 5G will introduce, or exacerbate, challenges related to protecting infrastructure and associated scientific data as well as to fully leveraging opportunities related to expanded infrastructure scale and complexity. The U.S. Department of Energy (DOE) Office of Science operates scientific infrastructure, supporting some of the nation’s most advanced intellectual discoveries, spanning the country and including 30 world-class user facilities from supercomputers to accelerators. Along with field experiments and remote observatories, every aspect of DOE’s scientific enterprise will be affected by 5G, which amounts to a complete renovation of the underpinnings of the nation’s information infrastructure. In this report we explore the scientific opportunities and new research challenges associated with 5G, ranging from scalability to heterogeneity to cybersecurity. The rapid commercial deployment of 5G opens the opportunity to rethink and reinvent DOE’s scientific infrastructure and experimentation, from intelligent sensor networks at unprecedented scales to a digital continuum of cyberinfrastructure spanning low-power sensors, high-performance computing embedded within and at the edge of the network, and DOE’s large-scale user instrument and computing facilities. New programming paradigms, workflow and data frameworks, and AI-based system design, operation, and autonomous adaptation and optimization will be necessary in order to exploit these new opportunities. Field deployments and centralized scientific instruments can also be revolutionized, moving (without traditional performance penalties) from wired to wireless connectivity for data and control systems, improving flexibility, and opening new sensing modalities, including the use of the 5G electromagnetic spectrum itself as an environmental probe. For DOE science, in contrast to commercial 5G applications and settings, devices will be deployed in extreme environments such as cryogenically cooled instrument control systems and in remote settings with harsh conditions, requiring the design of new materials for RF communication and edge processing to operate in these regimes. Concurrently, 5G infrastructure comprises both hardware and sophisticated software systems - currently closed and proprietary. The cybersecurity challenges to 5G-empowered reinvention mirror the complexity and variety of new 5G features, from virtualization to private network slices to ubiquitous access. Research is also needed in order to accelerate the development of secure and open 5G software infrastructure, reducing reliance on hardware and software produced outside the United States and providing the transparency and rigorous evaluation and testing afforded through open software. Twelve broad research thrusts are laid out in four chapters, with a companion fifth chapter (and three additional research thrusts) underscoring the needs and opportunities for an aggressive testbed program co-designed by networking experts and scientists involved in the 15 research thrusts. The urgency of undertaking this research is fueled by a global, accelerating deployment of new telecommunications infrastructure that is designed for entertainment and commercial applications - barely scratching the surface of what 5G can do to extend U.S. leadership in scientific discovery.

42 ENGINEERING↗
DOE OSTI2022

Triton Initiative: FY22 Communications, Outreach, and Engagement End-of-Year Report

The Department of Energy (DOE) Water Power Technologies Office (WPTO) Triton Initiative supports the advancement of the marine energy (ME) industry through environmental monitoring research and technology development. This report presents the results and analysis of the Triton Initiative’s communications, outreach, and engagement (TCOE) efforts in fiscal year 2022. The primary TCOE goals were to: (1) educate and raise awareness of ME and the role of Triton's environmental monitoring research in supporting the industry; (2) build trust with audiences through transparent communications and outreach; and (3) evaluate and refine TCOE tactics based on feedback and metrics. To support these goals, the TCOE team used multiple platforms and approaches. Notable achievements include: (1) 12 newsletter issues sent to 185 subscribers with an average open rate of 56.4%. (2) 10 Triton Stories, resulting in 2,871 collective views contributing to 46% of all Triton website views. (3) 78 Triton-specific social media posts, which generated a total of 81,896 impressions, 1,037 post-clicks, and 7,814 video views. (4) 6,320 Triton website views with increased search engine optimization ranking in several categories. (5) 3 Triton researchers interviewed as guests on two different podcasts, Water Women and Big Deep: An Ocean Podcast. (6) A Triton special issue of the Journal of Marine Science and Engineering (JMSE) featuring 10 peer reviewed publications. All articles ranked in the top 25%, and two in the top 5%, for digital attention of all research outputs scored by Altmetric. (7) A seven-part webinar series called Triton Talks to share and discuss research and results from the research published in the JMSE special issue. Triton leveraged unique opportunities, particularly the JMSE special issue, to disseminate research results to end users, educate stakeholders, and gain valuable feedback. These concerted communication efforts increased exposure across platforms ultimately resulting in greater reach and access across audiences. Based on audience analyses of webinar attendees and newsletter subscribers, the TCOE team was able to successfully engage with general audiences, research partners, and ME stakeholders, including subject matter experts from government agencies, research organizations, and the regulatory community. The TCOE task established channels to gather input and create opportunities for two-way communication with people engaged with Triton’s outreach efforts. The feedback received will enable the TCOE team to support its goals for ongoing evaluation of outreach and engagement tools while continuing to build trust in the ME community and educate diverse audiences about the impactful research conducted by the Triton Initiative. This report is a Triton Initiative Fiscal Year 2022 Quarter 4 Milestone Deliverable due to the DOE WPTO Sponsor on 9/30/2022. An updated version to include data through 9/30/2022 will be delivered in October 2022.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Summary of Pilot Project State Technical Assistance on Multi-Sector Analysis for Electric and Petroleum Fuels

The Oregon Energy Security Plan, (ODOE 2024) published in September 2024, builds a strong case for the state to give acute attention to the fuel supply chain. In December 2024, Pacific Northwest National Laboratory (PNNL) in partnership with Oregon Department of Energy (ODOE), announced a pilot project to conduct an analysis that synthesizes current and projected transportation fuel dynamics, supply chain risks, and risk comparators with relevant sectors, such as transportation electrification, sponsored by the Department of Energy’s (DOE) Office of Cybersecurity, Energy Security, and Emergency Response (CESER). The study, is intended to leverage existing modeling and frameworks from a recent 2024 sector coupling analysis supported by the DOEs Office of Electricity (OE) (B. Mitra, S. Pal, et al., Coupling of the Electricity and Transportation Sectors - Part I: Sector Overviews 2024) (B. Mitra, S. Pal and J. Reeve, et al. 2024). While the PNNL team set out to conduct a quantitative risk analysis driven by detailed data that synthesizes current and projected transportation fuel dynamics, supply chain risks, and risk comparators with relevant sectors. The intention was to provide an approach that could be extendable to other parts of the country. They encountered data limitations and adjusted their approach accordingly. This report summarizes PNNL's original plan for executing the study, including limitations for obtaining data requirements for fuel flows and interim products, as well as a risk matrix that can be used to identify supply chain risks.

02 PETROLEUM↗
DOE OSTI2022

Artificial Intelligence for Earth System Predictability (AI4ESP) (2021 Workshop Report)

In October 2021, the U.S. Department of Energy (DOE) welcomed participants to the Artificial Intelligence for Earth System Predictability (AI4ESP) Workshop, hosted by the Office of Biological and Environmental Research (BER)—Advanced Scientific Computing Research (ASCR). The workshop is part of BER-ASCR’s ambition to more radically and aggressively advance prediction capabilities in the climate, Earth, and environmental sciences through the use of modern data analytics and artificial intelligence (AI). Advances in these capabilities are needed to improve predictions of climate change and extreme events that provide actionable information for planning and building resilience to their impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Forensic Analysis of SOHO Router Binaries

Small Office/Home Office (SOHO) routers are used by millions of consumers across the United States, and are commensurately vulnerable. Forensic analysis of SOHO router firmware helps to understand and mitigate those vulnerabilities. This poster focused particularly on analysis of BusyBox executables, a software suite that provides several Unix utilities in a single file. Three main tools were used to analyze the binaries. BinWalk was used to extract the files, but also to build entropy graphs, extract Linux kernel images, and identify CPU architectures; WiiBin processed the binaries to find endianness, architecture, the percent compressed/encrypted, and compiler data; and @DisCo, a machine learning tool used to determine function similarity in disassembled binaries, analyzed similarities and determined versions of extracted BusyBox files from each router. These tools found that venders from all five routers utilized the same version of the BusyBox software across different firmware updates, demonstrating the importance of constant firmware scrutiny to protect against security vulnerabilities.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Added Value for Integrated Marine Energy Data Systems (February 2021)

Launched in 2019, the Portal and Repository for Information on Marine Renewable Energy (PRIMRE) provides centralized access, standardization, community building, and integration of United States (U.S.) databases, tools and codes, and other resources that cover a range of marine energy information. The PRIMRE universe contains a series of Knowledge Hubs that represent data and information on testing of marine energy devices (MHKDR); environmental effects (Tethys); engineering and technical papers (Tethys Engineering); descriptions of marine energy companies and technologies (Marine Energy Projects Database); codes and models (Marine Energy Software); and guidance on testing and measurements (Telesto). Content is added to PRIMRE by applying a set of Guidelines and Best Practices (PRIMRE Guidelines). An aggregate search across the PRIMRE site enables users to find data and information from all the PRIMRE Knowledge Hubs simultaneously, using a single entry-point (PRIMRE Search). In addition to providing access to a range of data and information on marine energy development, testing, and effects, PRIMRE allows for the development of valueadded products and processes that will help move the marine energy industry forward. The PRIMRE team has recently launched two key initiatives in the U.S.-Signature Projects and Lessons Learned. Outputs and outcomes from these two initiatives will be highlighted in this paper. The Signature Projects initiative is intended to bring focus to a selection of ongoing and completed marine energy projects funded by the U.S. Department of Energy's Water Power Technologies Office (WPTO), and to inform the marine energy community of what investigations have been undertaken, what tools are available, and where gaps in information persist. Each Signature Project tags papers, reports, and data from large marine energy research projects, providing easy access and attention to all the output and associated products from each project. The Lessons Learned initiative is intended to ensure that hard-won achievements are recognized and available for those who come later, that missteps and unfortunate outcomes can be prevented in future, and that efficiencies and effective shortcuts can be publicized and used as the marine energy industry moves forward. This initiative builds off the Knowledge Hubs and reaches out to members of the marine energy community, particularly technology developers and researchers, to integrate experience in the development, deployment, assessment, success, challenges while creating this new industry and field of study.

data sharing↗