SEARCH · Engineering Papers

Results for “technology assessment framework”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 577 records · Page 32

All sources NASA NTRS DOE OSTI

DOE OSTI2021

Advancing Solar Innovation for Low and Moderate-Income Households (Final Technical Report)

The overarching goal of this project was to deepen the understanding of the social and economic aspects of solar adoption, with a specific eye towards any pathways or barriers that could be identified that directly impact low and moderate-income households. Specific objectives included (1) identifying and assessing significant non-economic barriers that complicate the ability of LMI households to adopt and benefit from solar, even under scenarios with low economic barriers; (2) assessing the differential ability of groups to benefit from solar adoption based on their ability to invest in different solar innovations; (3) explaining why some LMI communities nonetheless experience significantly higher rates of solar adoption and benefit than others; (4) developing a methodological model for generating data addressing key issues to the project; and (5) designing and developing an interactive web portal that aggregates existing datasets, provides researchers trend analysis capabilities, standardizes project protocols for other states and communities; provides the opportunities for researchers using the same protocol in other communities to upload their results; and engages with the general public by providing them the ability to upload their own perspectives and stories of solar technology adoption. Through a common framework for conducting semi-structured field interviews. In partnership with cooperative extension services, in conjunction with survey research and the aggregation of existing solar adoption datasets, this study has identified that currently ,there is a strong values alignment and knowledge access challenge that continues to affect solar adoption. Participants in this study – many of whom are either low or moderate-income and/or live in underserved rural communities do not believe solar is an option where they live or believe solar is appropriate for their lifestyle. This perception challenge is further exacerbated by the absolute dearth of adopters in most communities and a total lack of local marketing for solar energy. What marketing that does exist is geared towards audiences other than those in the participant's community, reinforcing a perception that 22% of survey respondents (n = 1,551) have: that solar energy is not meant for them and their community. Overcoming these serious human challenges pertaining to knowledge and marketing are critical to reducing the customer acquisition costs incurred amongst LMI communities and especially those in rural America where the opportunities solar provides to increase local energy resilience, security, all while engaging in personal stewardship of the planet could align with local values. Community-Based Social Marketing, built in partnership with community leaders and geared towards meeting local visions of ideal life, is a near term opportunity to bridge the gap between local priorities and national market and policy imperatives for solar while moving towards the administration's goals for renewable energy as part of a just and equitable decarbonization program. The tools and methods developed for this study can serve as a template for identifying other specific local challenges for solar adoption in other state, and provide the opportunity for a common data framework for understanding system-wide trends and barriers to achieving uptake of residential solar in communities that may, ultimately, benefit the most from the technology.

14 SOLAR ENERGY↗

DOE OSTI2025

Multiphase computational fluid dynamics modeling of reacting flows in absorption columns for carbon capture

First-principles derived computational fluid dynamics (CFD) simulations have been proposed as a fundamental tool for investigating solvent-based CO 2 absorption in packed columns due to their ability to accurately represent the underlying nonlinear, multiscale dynamics. Numerous studies have previously utilized such CFD simulations to investigate hydrodynamics of columns with structured and random packings by assessing the key hydrodynamic metrics such as the interfacial and wetted areas. While mapping such metrics for different conditions is essential to the optimization of absorption columns, it is not sufficient, as the CO 2 capture rate depends also on the coupled, nonlinear dynamics from the underlying chemical reaction kinetics, thermodynamics, and heat-transfer rates. In this work, we present detailed CFD simulation results augmented by incorporating the effects of interfacial physical mass transfer of CO 2 , heat release from chemical reaction kinetics, and thermophysical property variations from resulting temperature gradients. We demonstrate the applicability of the proposed approach in numerically assessing the performance of packed columns by evaluating key hydrodynamic quantities, CO 2 absorption rates, and temperature rise in a reference column with packings that are structurally similar to the Sulzer Mellapak™ 250.Y packing, for different solvent inflow velocities and temperatures. Predictions from simulation results are found to be consistent with the trends in experimental observations from the literature, suggesting that the predictive capabilities of the simulation framework can be leveraged to guide the future development of absorber-column designs and optimized process flowsheets.

Absorption columns↗

DOE OSTI2026

Thermochemistry of Layered and Two-Dimensional Niobium Carbo-Chalcogenides

Two-dimensional transition metal carbo-chalcogenides (TMCCs) represent a novel class of layered materials with tunable electronic structures and high chemical versatility, making them promising candidates for energy and environmental applications. In this work, the structural and thermochemical properties of a series of TMCCs are investigated. High-temperature oxidative solution calorimetry, conducted at 800 °C in molten sodium molybdate (3Na2O·4MoO3), was used to determine the enthalpies of oxidation and formation from the elements at 25 °C, enabling a comprehensive thermodynamic assessment. Comparison of these enthalpies reveals distinct stability trends across the series. Cu0.67Nb2S2C exhibits the most exothermic oxidation enthalpy, indicating a strong thermodynamic driving force for oxidation and reduced resistance to oxidative degradation. Its positive enthalpy of formation from the elements suggests lower thermodynamic stabilization relative to the other compositions, consistent with the energetic influence of Cu and residual Fe within the Nb–S–C framework. In contrast, delaminated Nb2S2C exhibits poor oxidative stability but a highly exothermic enthalpy of formation, consistent with a defect-rich, metastable structural state rather than enhanced lattice stability. These findings establish correlations between crystal structure and energetic stability, providing insights into the design of robust TMCC-based materials for advanced energy and environmental technologies.

Cassell, Nakeshma [Clemson University]↗

DOE OSTI2022

Risk-Informed Initiating Events and Accident Response

Emerging nuclear technologies and advanced reactor developments have brought proposed changes to the regulatory framework which can be leveraged to improve safety implementation and regulatory oversight processes at existing operating nuclear power plants. Specifically, opportunities exist to make plants’ regulatory compliance processes more efficient. This can be done by decreasing reliance on purely deterministic and prescriptive approaches and expansion of the use of risk informed and performance-based approaches to demonstrate reactor safety while achieving economic gains and efficiencies. In this report, we researched possibilities of economic benefits potentially available from the application of concepts associated with a modernized regulatory framework developed for advanced reactors to the existing light water reactors. We used timing factors to demonstrate the complexity of the existing risk assessments and described how these complexities affect regulatory compliance activities at the plants. We also investigated regulatory framework for both existing and new reactors and provided an overview of potential improvements. Lastly, we evaluated various areas of existing plant operations where modernization of compliance activities can offer substantial benefits.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

DYFLOW: A flexible framework for orchestrating scientific workflows on supercomputers

Modern scientific workflows are increasing in complexity with growth in computation power, incorporation of non-traditional computation methods, and advances in technologies enabling data streaming to support on-the-fly computation. These workflows have unpredictable runtime behaviors, and a fixed, predetermined resource assignment on supercomputers can be inefficient for overall performance and throughput. Inability to change resource assignments further limits the scientists to avail of science-driven opportunities or respond to failures.We introduce DYFLOW, a flexible framework that orchestrates scientific workflows on supercomputers based on user-designed policies. DYFLOW compartmentalizes orchestration stages into simplified constructs, and end-users can program and reuse them according to their workflow requirements through an easy-to-use interface. These constructs hide the intricacies involved in runtime management from end-users, for instance, procurement of information to understand the workflow state, assessment, and supervision of the runtime changes. DYFLOW is designed to work alongside existing workflow management systems and reuse the available (static) support for workflow management. We have integrated DYFLOW with an existing workflow management tool as a demonstration. With experiments performed on use cases from three types of scientific workflows and two different parallel architectures, we show that DYFLOW achieves the desired orchestration incurring a small cost to carry out the runtime changes.

Singhal, Swati↗

DOE OSTI2022

A Tool Kit for Generating Simulated Radiation Measurements for Advanced Reactor Safeguards and Security

A tool kit was developed to simulate and analyze passive radiation measurements of molten salt reactor (MSR) operations to support development of nuclear safeguards approaches for this emerging reactor technology. A Transient Simulation Framework of Reconfigurable Modules (TRANSFORM) multiphysics simulation of an MSR produces time-dependent isotopic inventories at user-selected locations within the model. The tool kit implements the Gamma Detector Response and Analysis Software (GADRAS) application programming interface to inject the TRANSFORM isotopic inventories extracted/processed by a Python pipeline into GADRAS models of user-defined geometries. The TRANSFORM inventories are the source terms used to obtain synthetic measurements from GADRAS-defined detectors. The speed of TRANSFORM and GADRAS simulations enables surveying the large design space of MSRs (e.g., fuel type, fuel salt composition, number of loops) and the plethora of measurements (e.g., location, detector type, and collimation) within the reactor. This has enabled timely assessment of the various measurement locations and detectors to identify the most effective and efficient safeguards approach for a specific MSR design. Lastly, the tool kit also simulates extracted samples that can be aged to a desired dose, enabling stakeholders to optimize a measurement plan to use sample analysis as an element within a broader material accountancy plan.

Westphal, Greg↗

DOE OSTI2023

Machine Learning for Geothermal Resource Exploration in the Tularosa Basin, New Mexico

Geothermal energy is considered an essential renewable resource to generate flexible electricity. Geothermal resource assessments conducted by the U.S. Geological Survey showed that the southwestern basins in the U.S. have a significant geothermal potential for meeting domestic electricity demand. Within these southwestern basins, play fairway analysis (PFA), funded by the U.S. Department of Energy’s (DOE) Geothermal Technologies Office, identified that the Tularosa Basin in New Mexico has significant geothermal potential. This short communication paper presents a machine learning (ML) methodology for curating and analyzing the PFA data from the DOE’s geothermal data repository. The proposed approach to identify potential geothermal sites in the Tularosa Basin is based on an unsupervised ML method called non-negative matrix factorization with custom k-means clustering. This methodology is available in our open-source ML framework, GeoThermalCloud (GTC). Using this GTC framework, we discover prospective geothermal locations and find key parameters defining these prospects. Our ML analysis found that these prospects are consistent with the existing Tularosa Basin’s PFA studies. This instills confidence in our GTC framework to accelerate geothermal exploration and resource development, which is generally time-consuming.

15 GEOTHERMAL ENERGY↗

NASA NTRS2016

The Impact of New Trends in Satellite Launches on Orbital Debris Environment

The main goal of this study is to examine the impact of new trends in satellite launch activities on the orbital debris environment and collision risk. Starting from the launch of the first artificial satellite in 1957, space borne technology has become an indispensable part of our lives. More than 6,000 satellites have been launched into Earth orbit. Though the annual number of satellites launched stayed flat for many decades, the trend has recently changed. The satellite market has been undergoing a major evolution with new space companies replacing the traditional approach of deploying a few large, complex and costly satellites with an approach to use a multitude of smaller, less complex and cheaper satellites. This new approach creates a sharp increase in the number of satellites and so the historic trends are no longer representative. As a foundation for this study, a scenario for satellite deployments based on the publicly announced future satellite missions has been developed. These constellation-deploying companies include, but are not limited to, Blacksky, CICERO, EROS, Landmapper, Leosat, Northstar, O3b, OmniEarth, OneWeb, Orbcomm, OuterNet, PlanetIQ, Planet Labs, Radarsat, RapidEye Next Generation, Sentinel, Skybox, SpaceX, and Spire. Information such as the annual number of launches, the number of orbital planes to be used by the constellation, as well as apogee, perigee, inclination, spacecraft mass and area were included or approximated. Besides the production of satellites, a widespread ongoing effort to enhance orbital injection capabilities will allow delivery of more spacecraft more accurately into Earth orbits. A long list of companies such as Microcosm, Rocket Lab, Firefly Space Systems, Sierra Nevada Corporation and Arca Space Corporation are developing new launch vehicles dedicated for small satellites. There are other projects which intend to develop interstages with propulsive capabilities which will allow the deployment of satellites into their desired orbits beyond the restrictions of the launch vehicle used. These near future orbital injection technologies are also covered in the developed scenario. Using the above-mentioned background information, this study aims to examine how the orbital debris environment will be affected from the new dynamics of the emerging space markets. We developed a simulation tool that is capable of propagating the objects in a given deployment scenario with variable-sized time-steps as small as one second. Over the course of the run, the software also detects collisions; additional debris objects are then created according to the NASA breakup model and are fed back into the simulation framework. Examining the simulation results, the total number of particles to accumulate in different orbits can be monitored and the number of conjunctions can be tracked to assess the collision risks. The simulation makes it possible to follow the short- and long-term effects of a particular satellite or constellation on the space environment. Likewise, the effects of changes in the debris environment on a particular satellite or constellation can be evaluated. It is authors hope that the results of this paper and further utilization of the developed simulation tool will assist in the investigation of more accurate deorbiting metrics to replace the generic 25-year disposal guidelines, as well as to guide future launches toward more sustainable and safe orbits.

New Space↗

DOE OSTI2023

Deriving spatially explicit direct and indirect interaction networks from animal movement data

Abstract Quantifying spatiotemporally explicit interactions within animal populations facilitates the understanding of social structure and its relationship with ecological processes. Data from animal tracking technologies (Global Positioning Systems [“GPS”]) can circumvent longstanding challenges in the estimation of spatiotemporally explicit interactions, but the discrete nature and coarse temporal resolution of data mean that ephemeral interactions that occur between consecutive GPS locations go undetected. Here, we developed a method to quantify individual and spatial patterns of interaction using continuous‐time movement models (CTMMs) fit to GPS tracking data. We first applied CTMMs to infer the full movement trajectories at an arbitrarily fine temporal scale before estimating interactions, thus allowing inference of interactions occurring between observed GPS locations. Our framework then infers indirect interactions—individuals occurring at the same location, but at different times—while allowing the identification of indirect interactions to vary with ecological context based on CTMM outputs. We assessed the performance of our new method using simulations and illustrated its implementation by deriving disease‐relevant interaction networks for two behaviorally differentiated species, wild pigs ( Sus scrofa ) that can host African Swine Fever and mule deer ( Odocoileus hemionus ) that can host chronic wasting disease. Simulations showed that interactions derived from observed GPS data can be substantially underestimated when temporal resolution of movement data exceeds 30‐min intervals. Empirical application suggested that underestimation occurred in both interaction rates and their spatial distributions. CTMM‐Interaction method, which can introduce uncertainties, recovered majority of true interactions. Our method leverages advances in movement ecology to quantify fine‐scale spatiotemporal interactions between individuals from lower temporal resolution GPS data. It can be leveraged to infer dynamic social networks, transmission potential in disease systems, consumer–resource interactions, information sharing, and beyond. The method also sets the stage for future predictive models linking observed spatiotemporal interaction patterns to environmental drivers.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

CalderaCast User Manual Version 1.0

CalderaCast is a user-friendly web-based tool for electrical-load forecast, providing stakeholders with a fully customizable decision-support framework that estimates the likely power draw from a possible future electric-vehicle (EV) charging station at a given location on a given day along an alternative fuel corridor (AFC). These EV charging profiles are accurately modeled in CalderaCast using the Caldera software framework developed by Idaho National Laboratories (INL), reflecting the realistic charging levels observed in actual charge events. This tool was developed as part of the National Electric Vehicle Infrastructure (NEVI) program, which is quickly generating substantial interest from would-be charging station operators (CSO), large and small electric utilities, and state transportation planners, some of whom had not seriously considered EV charging previously. All these entities—with or without background in EV infrastructure—must estimate the electricity load that a proposed charging station will generate. This load forecast is critically important for a utility to properly assess the capacity of their distribution network to support the proposed station or properly size grid upgrades for potential load growth due to future EV adoption, vehicle technology improvements, or station growth. This document describes each aspect of the CalderaCast tool and provides guidance to users who are interested in utilizing the tool for their work.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRSDate not supplied

Sustainable Crop Cultivation in Space Analogs: A BRIDGES Methodology Perspective Through SpaCEA

Sustainable crop cultivation in space holds paramount significance for the support of life in future long-duration missions. This research explores the development and integration of innovative low-cost proof-of-concept (LC-POC) plant growth cabinets tailored for use in space analog missions. By outlining past and current efforts in space farming, this study introduces the SpaCEA Cabinet using BRIDGES framework, establishing a context for reproducible experiments and innovation in plant growth systems. The SpaCEA cabinets can either be delivered in flat packs or assembled on-site, employing cutting-edge methods like 3-D printing and laser cutting. The main objective is to assess how effectively these structures foster crop growth within analog environments while replicating conditions crucial for space exploration. Employing a multi-faceted approach encompassing technical and qualitative dimensions, this project integrates a qualitative investigation where representatives managing analog stations and analog astronauts will partake in interviews and questionnaires to discern specific requirements and challenges within these environments. Insights gained from these engagements will significantly define the final design parameters of updated SpaCEA plant growth cabinets. The practical applicability of these cabinets emphasizes ease of assembly and transportation, addressing the inherent spatial and logistical constraints associated with space missions. Furthermore, the BRIDGES framework ensures the standardization of hardware, software, and data-gathering elements within a unified structure, which utilizes cutting-edge manufacturing technologies for the prototyping and deployment of these cabinets. The anticipated outcomes of this research include the identification of key design considerations and technical specifications for plant growth cabinets tailored to space farming analog systems. This research is poised to contribute valuable knowledge to sustainable space exploration through the development of interoperable plant growth systems for analog environments, advancing research in space crop cultivation which will make up part of a larger bioregenerative life support system.

Advanced Life Support↗

NASA NTRSDate not supplied

Sustainable Crop Cultivation in Space Analogs: A BRIDGES Methodology Perspective Through SpaCEA

Advanced Life Support↗

DOE OSTI2022

Defensive Islanding to Enhance the Resilience of Distribution Systems Against Cyber-Induced Failures

The extensive integration of communication, computation, and control technologies into cyber-physical power systems (CPPSs) has increased the vulnerabilities of CPPSs to cyberattacks. This calls for developing solutions that assess and reduce the impacts of cyber-induced failures on CPPSs. This paper proposes a defensive islanding strategy to isolate impacted parts of the CPPS and form self-sufficient islanded grids with an objective of minimum load curtailment. The defensive islanding aims to split a power system into smaller grids to improve its resilience against a potential extreme event. A clustering approach that leverages the hierarchical spectral clustering method is utilized for the optimal defensive islanding. The proposed approach captures the fragility behavior and loading conditions of power system components due to cyber-induced failures. A graphical-based coupling framework is used to map the impacts of cyber failures into operation of power system components. The proposed method is demonstrated on a modified 33-node distribution feeder system integrated with distributed energy resources. The amount of load curtailment and radiality constraints have been used to evaluate the performance of the proposed clustering strategies. The results show the capability of the proposed algorithm to create islands considering the cyber-induced failures for enhanced resilience.

cyber-induced failures↗

DOE OSTI2021

A Method for Assessing Effectiveness and Technical Capabilities Required for Integrated Deterrence (NSLP-Final Report-Draft2022)

The United States faces an ever-increasingly multi-polar security environment dominated by great power competition with China and a lingering Russian threat as well as from would-be regional hegemons led by ambitions from Iran and North Korea. Our adversaries are pursuing and expanding the strategic means by-which they have an asymmetric offset (e.g., cyber, space, and other modes below the level of armed conflict). To combat and deter against the widening range of hostile actions, the U.S. must have additional capabilities with-which to deter. All of which drives us towards a more thoughtful integrated approach to deterrence, attempting to best align deterrent tools with the adversary actions in order to maximize the credibility of our deterrent. Such an approach complicates our deterrence strategy and demands a methodology to assess whether the U.S. has the deterrent tools necessary to deter the adversarial actions most costly to the U.S. To address this complexity, we create a framework to comprehensively and systematically assess our deterrent tools as qualitatively measured against the adversarial actions we wish to deter. Deterrence is ultimately an operation in the cognitive domain and at the heart of the framework presented here is the fundamental deterrence calculus which we use as the defining measure of whether a tool will credibly deter a given action. We describe the eight levers of the deterrence calculus and distill these levers to four products that are used to qualitatively assess the overall effectiveness of deterrence tools against adversarial actions. Credibility is determined by two principal variables: the technical credibility of the deterrent tool, and the principle of proportionality. Technical credibility of realized deterrence products is assessed through development of key mission requirements and hardware (e.g., components) that will impose costs, deny benefits, or encourage restraint. The principle of proportionality qualitatively asserts that for a deterrent tool to be cognitively credible, the costs imposed against, or benefits denied by, an action are commensurate to the magnitude of costs received from the adversarial action. By basing this framework on these two fundamentals, it is possible to compare deterrent tools in a systematic approach across the broad spectrum of hostile actions.

42 ENGINEERING↗

NASA NTRS2007

Automated Target Planning for FUSE Using the SOVA Algorithm

The SOVA algorithm was originally developed under the Resilient Systems and Operations Project of the Engineering for Complex Systems Program from NASA s Aerospace Technology Enterprise as a conceptual framework to support real-time autonomous system mission and contingency management. The algorithm and its software implementation were formulated for generic application to autonomous flight vehicle systems, and its efficacy was demonstrated by simulation within the problem domain of Unmanned Aerial Vehicle autonomous flight management. The approach itself is based upon the precept that autonomous decision making for a very complex system can be made tractable by distillation of the system state to a manageable set of strategic objectives (e.g. maintain power margin, maintain mission timeline, and et cetera), which if attended to, will result in a favorable outcome. From any given starting point, the attainability of the end-states resulting from a set of candidate decisions is assessed by propagating a system model forward in time while qualitatively mapping simulated states into margins on strategic objectives using fuzzy inference systems. The expected return value of each candidate decision is evaluated as the product of the assigned value of the end-state with the assessed attainability of the end-state. The candidate decision yielding the highest expected return value is selected for implementation; thus, the approach provides a software framework for intelligent autonomous risk management. The name adopted for the technique incorporates its essential elements: Strategic Objective Valuation and Attainability (SOVA). Maximum value of the approach is realized for systems where human intervention is unavailable in the timeframe within which critical control decisions must be made. The Far Ultraviolet Spectroscopic Explorer (FUSE) satellite, launched in 1999, has been collecting science data for eight years.[1] At its beginning of life, FUSE had six gyros in two IRUs and four reaction wheels. Over time through various failures, the satellite has been left with one reaction wheel on the vehicle skew axis and two gyros. To remain operational, a control scheme has been implemented using the magnetic torque rods and the remaining momentum wheel.[2] As a consequence, there are attitude regions where there is insufficient torque authority to overcome environmental disturbances (e.g. gravity gradient torques). The situation is further complicated by the fact that these attitude regions shift inertially with time as the spacecraft moves through earth s magnetic field during the course of its orbit. Under these conditions, the burden of planning targets and target-to-target slew maneuvers has increased significantly since the beginning of the mission.[3] Individual targets must be selected so that the magnetic field remains roughly aligned with the skew wheel axis to provide enough control authority to the other two orthogonal axes. If the field moves too far away from the skew axis, the lack of control authority allows environmental torques to pull the satellite away from the target and can potentially cause it to tumble. Slew maneuver planning must factor the stability of targets at the beginning and end, and the torque authority at all points along the slew. Due to the time varying magnetic field geometry relative to any two inertial targets, small modifications in slew maneuver timing can make large differences in the achievability of a maneuver.

Heatwole, Scott↗

NASA NTRS2020

NeMO-Net – The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment

We present NeMO-Net, the Srst open-source deep convolutional neural network (CNN) and interactive learning and training software aimed at assessing the present and past dynamics of coral reef ecosystems through habitat mapping into 10 biological and physical classes. Shallow marine systems, particularly coral reefs, are under significant pressures due to climate change, ocean acidification, and other anthropogenic pressures, leading to rapid, often devastating changes, in these fragile and diverse ecosystems. Historically, remote sensing of shallow marine habitats has been limited to meter-scale imagery due to the optical effects of ocean wave distortion, refraction, and optical attenuation. NeMO-Net combines 3D cm-scale distortion-free imagery captured using NASA FluidCam and Fluid lensing remote sensing technology with low resolution airborne and spaceborne datasets of varying spatial resolutions, spectral spaces, calibrations, and temporal cadence in a supercomputer-based machine learning framework. NeMO-Net augments and improves the benthic habitat classification accuracy of low-resolution datasets across large geographic ad temporal scales using high-resolution training data from FluidCam.NeMO-Net uses fully convolutional networks based upon ResNet and ReSneNet to perform semantic segmentation of remote sensing imagery of shallow marine systems captured by drones, aircraft, and satellites, including WorldView and Sentinel. Deep Laplacian Pyramid Super-Resolution Networks (LapSRN) alongside Domain Adversarial Neural Networks (DANNs) are used to reconstruct high resolution information from low resolution imagery, and to recognize domain-invariant features across datasets from multiple platforms to achieve high classification accuracies, overcoming inter-sensor spatial, spectral and temporal variations.Finally, we share our online active learning and citizen science platform, which allows users to provide interactive training data for NeMO-Net in 2D and 3D, integrated within a deep learning framework. We present results from the PaciSc Islands including Fiji, Guam and Peros Banhos 1 1 2 1 3 1 where 24-class classification accuracy exceeds 91%.

Chirayath, Ved↗

NASA NTRS1989

Application of reusable software components at the SEI

Robert Holibaugh of the Software Engineering Institute described a project which is studying the application of reusable software components. The primary goals are to gain practical experience with state-of-the-art reusable components, methods, and tools and to capture the lessons learned in the application of reuse technology. In addition the project will assess the impact of reuse on the software development process and products and will identify and validate the information that facilities software reuse during system development. The project includes two tasks - a reuse experiment and a redevelopment effort. The reuse experiment will define a life cycle and a methodology for reuse-based development, and define and implement a data collection mechanism for measuring the development. The redevelopment effort will construct a reuse test bed and will redevelop and realistically test subsystems from an embedded mission-critical real-time application. The reuse experiment will produce several products including a tested real-time application, reuse-based components and tools evaluation, a reuse-based development method, a framework for data collection, a framework for measuring productivity, and lessons learned data. Successful development with reusable components will require a rich set of components and an integrating methodology. The Tomahawk Land Attack Missile system is the application for the redevelopment effort.

Holibaugh, Robert↗

DOE OSTI2024

A Framework to Assess Advanced Reactor Spent Fuel Management Facility Deployment

Advanced nuclear reactors offer various operational advantages over existing light water reactors but could produce types of spent nuclear fuel (SNF) with a wide variety of forms and characteristics depending on how many different concepts are deployed. Each advanced reactor SNF type potentially poses unique management challenges. New planning efforts will be necessary to anticipate how the management requirements of advanced reactor SNF will affect the deployment of an integrated waste management system. This paper applies a framework of high-level facility deployment milestones to a generic SNF management system, reviewing them together with the advanced reactor SNF characteristics and management requirements. This allows for the investigation of factors that influence facility and system deployment, and ultimately, the identification of challenges facing the deployment of different kinds of SNF management facilities. Here, the back end of the once-through fuel cycle is examined for four advanced reactor system technology types: sodium-cooled fast reactors, high-temperature gas-cooled reactors, liquid-fuel molten salt reactors, and lead-cooled fast reactors. It is observed that milestones earlier in the facility deployment process (e.g., siting and facility design) are more impacted by the uniqueness of advanced reactor SNF characteristics than others (e.g., construction and testing). Ultimately, none of the differences are seen as fundamentally disqualifying in a technical sense; however, they should be considered early, potentially as part of reactor design, to avoid issues in the future.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗