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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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At least 181 records · Page 10

A Simplified Model of VIPER Thermal Management System. Part I: Loop Heat Pipe

NASA’s Volatiles Investigating Polar Exploration Rover (VIPER) uses a combination of loop heat pipes (LHPs) and heaters as the primary hardware to modulate the temperature of the electronic boxes and payloads instruments. LHPs have been designed and instrumented to be capable of passive and active shutdown. The goal of the passive shutdown, using a thermal control valve (TCV) to limit the flow of the working fluid, is to preserve thermal energy and avoid unnecessary heat leaks during lunar night. The goal of the active shutdown on the other hand, is to forcefully increase the vehicle internal temperature to bakeout the payload instruments. Several numerical modeling tools are available to analyze LHP performance under the complex set of operational requirements and environments levied on the VIPER Thermal Management System (TMS). Yet, while those numerical modeling tools are capable of detailed performance analysis, they tend to take large computational resources and long computational time. In this paper, a model of a single LHP developed based on control volume approach is presented. By using the control volume approach, the complex geometry of the LHP, and the components attached to it, are reduced to thermal lump capacitances, thus reducing the computation effort. This paper also describes the effort to correlate the proposed LHP model using thermal vacuum (TVAC) test data.

Loop Heat Pipe↗

A Simplified Model of VIPER Thermal Management System. Part I: Loop Heat Pipe

NASA’s Volatiles Investigating Polar Exploration Rover (VIPER) uses a combination of loop heat pipes (LHPs) and heaters as the primary hardware to modulate the temperature of the electronic boxes and payloads instruments. LHPs have been designed and instrumented to be capable of passive and active shutdown. The goal of the passive shutdown, using a thermal control valve (TCV) to limit the flow of the working fluid, is to preserve thermal energy and avoid unnecessary heat leaks during lunar night. The goal of the active shutdown on the other hand, is to forcefully increase the vehicle internal temperature to bakeout the payload instruments. Several numerical modeling tools are available to analyze LHP performance under the complex set of operational requirements and environments levied on the VIPER Thermal Management System (TMS). Yet, while those numerical modeling tools are capable of detailed performance analysis, they tend to take large computational resources and long computational time. In this paper, a model of a single LHP developed based on control volume approach is presented. By using the control volume approach, the complex geometry of the LHP, and the components attached to it, are reduced to thermal lump capacitances, thus reducing the computation effort. This paper also describes the effort to correlate the proposed LHP model using thermal vacuum (TVAC) test data.

Loop Heat Pipe↗

Validation of A Simulation Environment for Future Space Traffic Management

This study presents initial results of a newly developed simulation environment intendedto explore and assess future Space Traffic Management (STM) scenarios. The number ofnew Resident Space Objects (RSOs) in near-Earth orbit is expected to increase significantlywith the expected future deployment of a number of large constellations. These futurescenarios involve the addition of many tens of thousands of new RSOs, making the analysisinto their impact on collision risk extend beyond what traditional data-mining of present-dayconjunction data can reliably predict. To address this, a robust simulation environment wasdeveloped that implements a full force-model for orbit propagation, and computes continuousall-on-all conjunction statistics for arbitrarily large catalog sizes and simulation timeframes.Collision avoidance and station-keeping maneuvers can be optionally implemented based onconfigurable user inputs including physical characteristics and spacecraft meta-data (e.g.,commercial/government, owner country, etc.). Constellation build-out and de-orbit scenarioswere also implemented and modeled based on real-data analysis. Validation of the simulationresults was a critical component of the simulation development, and was done using the currentcatalog with comparisons against both public and internal NASA data-sets. The comparisonsdemonstrate that, with the appropriate settings, representative levels of conjunction ratesand probabilities can be obtained, providing confidence that the simulation tool can generatemeaningful outcomes for test scenarios. As an initial demonstration of the tool’s capabilities,year-long simulations with station-keeping were conducted to examine conjunction historiesusing both the current object catalog (5800 active satellites) and a hypothetical 60,000 objectscenario involving five potential large constellations. Output metrics include the number ofconjunction events, estimates of collision consequence (fragmentation), delta-V maneuver costs,and the probability of at least one collision occurring. The results highlight the potential thatthe simulation tool has for incorporating and running performance comparisons between, e.g.,various sets of maneuver guidelines, industry norms, and definitions of risk, with the overallobjective of providing actionable data to STM policy makers. The presentation will providean overview of the simulation development and validation efforts, as well as a discussion ofobservations gathered from the initial simulations performed.

conjunction assessment↗

Application of the Tool for Turbine Engine Closed-Loop Transient Analysis (TTECTrA) for Dynamic Systems Analysis

The aircraft engine design process seeks to achieve the best overall system-level performance, weight, and cost for a given engine design. This is achieved by a complex process known as systems analysis, where steady-state simulations are used to identify trade-offs that should be balanced to optimize the system. The steady-state simulations and data on which systems analysis relies may not adequately capture the true performance trade-offs that exist during transient operation. Dynamic Systems Analysis provides the capability for assessing these trade-offs at an earlier stage of the engine design process. The concept of dynamic systems analysis and the type of information available from this analysis are presented in this paper. To provide this capability, the Tool for Turbine Engine Closed-loop Transient Analysis (TTECTrA) was developed. This tool aids a user in the design of a power management controller to regulate thrust, and a transient limiter to protect the engine model from surge at a single flight condition (defined by an altitude and Mach number). Results from simulation of the closed-loop system may be used to estimate the dynamic performance of the model. This enables evaluation of the trade-off between performance and operability, or safety, in the engine, which could not be done with steady-state data alone. A design study is presented to compare the dynamic performance of two different engine models integrated with the TTECTrA software.

systems analysis↗

NASA SensorWeb and OGC Standards for Disaster Management

I. Goal: Enable user to cost-effectively find and create customized data products to help manage disasters; a) On-demand; b) Low cost and non-specialized tools such as Google Earth and browsers; c) Access via open network but with sufficient security. II. Use standards to interface various sensors and resultant data: a) Wrap sensors in Open Geospatial Consortium (OGC) standards; b) Wrap data processing algorithms and servers with OGC standards c) Use standardized workflows to orchestrate and script the creation of these data; products. III. Target Web 2.0 mass market: a) Make it simple and easy to use; b) Leverage new capabilities and tools that are emerging; c) Improve speed and responsiveness.

Mandl, Dan↗

Gimballed Shoulders for Friction Stir Welding

In a proposed improvement of tooling for friction stir welding, gimballed shoulders would supplant shoulders that, heretofore, have been fixedly aligned with pins. The proposal is especially relevant to self-reacting friction stir welding. Some definitions of terms, recapitulated from related prior NASA Tech Briefs articles, are prerequisite to a meaningful description of the proposed improvement. In friction stir welding, one uses a tool that includes (1) a rotating shoulder on top (or front) of the workpiece and (2) a pin that rotates with the shoulder and protrudes from the shoulder into the depth of the workpiece. In conventional friction stir welding, the main axial force exerted by the tool on the workpiece is reacted through a ridged backing anvil under (behind) the workpiece. When conventional friction stir welding is augmented with an auto-adjustable pin-tool (APT) capability, the depth of penetration of the pin into the workpiece is varied in real time by a position- or forcecontrol system that extends or retracts the pin as needed to obtain the desired effect. In self-reacting (also known as self-reacted) friction stir welding as practiced heretofore, there are two shoulders: one on top (or front) and one on the bottom (or back) of the workpiece. In this case, a threaded shaft protrudes from the tip of the pin to beyond the back surface of the workpiece. The back shoulder is held axially in place against tension by a nut on the threaded shaft. Both shoulders rotate with the pin and remain aligned coaxially with the pin. The main axial force exerted on the workpiece by the tool and front shoulder is reacted through the back shoulder and the threaded shaft into the friction-stir-welding machine head, so that a backing anvil is no longer needed. A key transmits torque between the bottom shoulder and the threaded shaft, so that the bottom shoulder rotates with the shaft. This concludes the prerequisite definitions of terms.

Carter, Robert↗

NASA Earth eXchange (NEX) App Store

NASA Earth Exchange (NEX), and her public cloud version OpenNEX, have become platforms supporting scientific collaboration, knowledge sharing and research for the entire Earth science community. To date, a number of custom tools and capabilities have been integrated into the platforms. However, such integration has to undergo a case-by-case manual process thus lacks scalability. This timely project builds an App Store onto OpenNEX as a building block. Climate data analytics tools/programs can be easily uploaded, shared, organized, searched, and recommended like photos and videos on the YouTube. The foundation of our App Store is a provenance server, which not only records metadata but also execution history of climate data analytics apps including the input data and parameters, output data and products, who runs the app for which purpose, and how apps may be chained into workflows. Researchers can thus understand, reproduce, and repurpose existing apps and workflows. Machine learning approaches are applied to mine provenance to provide recommend-as-you-go services for Earth scientists, such as to recommend suitable apps and workflow snippets. A browser-based workflow tool is also provided for researchers to explore the provenance server and design value-added workflows. Scalability, sustainability, extensibility, usability, adaptability, security and privacy are considered in the App Store.

eXchange↗

Investigating Astromaterials Curation Applications for Dexterous Robotic Arms

The Astromaterials Acquisition and Curation office at NASA Johnson Space Center is currently investigating tools and methods that will enable the curation of future astromaterials collections. Size and temperature constraints for astromaterials to be collected by current and future proposed missions will require the development of new robotic sample and tool handling capabilities. NASA Curation has investigated the application of robot arms in the past, and robotic 3-axis micromanipulators are currently in use for small particle curation in the Stardust and Cosmic Dust laboratories. While 3-axis micromanipulators have been extremely successful for activities involving the transfer of isolated particles in the 5-20 micron range (e.g. from microscope slide to epoxy bullet tip, beryllium SEM disk), their limited ranges of motion and lack of yaw, pitch, and roll degrees of freedom restrict their utility in other applications. For instance, curators removing particles from cosmic dust collectors by hand often employ scooping and rotating motions to successfully free trapped particles from the silicone oil coatings. Similar scooping and rotating motions are also employed when isolating a specific particle of interest from an aliquot of crushed meteorite. While cosmic dust curators have been remarkably successful with these kinds of particle manipulations using handheld tools, operator fatigue limits the number of particles that can be removed during a given extraction session. The challenges for curation of small particles will be exacerbated by mission requirements that samples be processed in N2 sample cabinets (i.e. gloveboxes). We have been investigating the use of compact robot arms to facilitate sample handling within gloveboxes. Six-axis robot arms potentially have applications beyond small particle manipulation. For instance, future sample return missions may involve biologically sensitive astromaterials that can be easily compromised by physical interaction with a curator; other potential future returned samples may require cryogenic curation. Robot arms may be combined with high resolution cameras within a sample cabinet and controlled remotely by curator. Sophisticated robot arm and hand combination systems can be programmed to mimic the movements of a curator wearing a data glove; successful implementation of such a system may ultimately allow a curator to virtually operate in a nitrogen, cryogenic, or biologically sensitive environment with dexterity comparable to that of a curator physically handling samples in a glove box.

Snead, C. J.↗

The Application of Remotely Sensed Data and Models to Benefit Conservation and Restoration Along the Northern Gulf of Mexico Coast

New data, tools, and capabilities for decision making are significant needs in the northern Gulf of Mexico and other coastal areas. The goal of this project is to support NASA s Earth Science Mission Directorate and its Applied Science Program and the Gulf of Mexico Alliance by producing and providing NASA data and products that will benefit decision making by coastal resource managers and other end users in the Gulf region. Data and research products are being developed to assist coastal resource managers adapt and plan for changing conditions by evaluating how climate changes and urban expansion will impact land cover/land use (LCLU), hydrodynamics, water properties, and shallow water habitats; to identify priority areas for conservation and restoration; and to distribute datasets to end-users and facilitating user interaction with models. The proposed host sites for data products are NOAA s National Coastal Data Development Center Regional Ecosystem Data Management, and Mississippi-Alabama Habitat Database. Tools will be available on the Gulf of Mexico Regional Collaborative website with links to data portals to enable end users to employ models and datasets to develop and evaluate LCLU and climate scenarios of particular interest. These data will benefit the Mobile Bay National Estuary Program in ongoing efforts to protect and restore the Fish River watershed and around Weeks Bay National Estuarine Research Reserve. The usefulness of data products and tools will be demonstrated at an end-user workshop.

Quattrochi, Dale↗

Automated and Accelerated Continuum Model Development for Electrochemical Systems (Abbreviated Report)

Despite the availability of computational resources and advancements in numerical computing capabilities, the multiscale models core to understanding, predicting the behaviors of, and designing energy and environmental systems involving porous media are still 1.) developed through by-hand derivations and 2.) limited by many methodological assumptions employed during model derivation. As a result, the advancement of effective media models for engineering DOE mission-critical systems (e.g., batteries, flow batteries, electrolyzers, geothermal systems, subsurface chemical storage systems, etc.) is slow (i.e., it takes years for models to traverse from stages of “development” to “practical utilization”), hindering our ability to effectively optimize such systems and stay at the cutting-edge of the energy frontier. In this work, we aimed to address these limitations by 1.) automating and accelerating multiscale model derivation via symbolic computing and 2.) develop a novel multiscale modeling methodology for flow and transport through porous media that avoids the typical assumptions hindering previous models. As a result of our efforts, we 1.) developed a hybrid symbolic-numeric code called Fouriera for fully-automating the implementation of multiphysical and phase-field models via the Fourier spectral method for materials science research, and 2.) advanced a multiscale modeling methodology called The Method of Finite Averages that rigorously predicts the behaviors of flow and transport through heterogeneous porous media under the influence of non-local effects and strong advection. Ultimately, these deliverables provide strong foundations from which further efforts can advance multiscale modeling tools and capabilities that do not intrinsically rely on 1.) the speed and mathematical capabilities of humans, nor 2.) the methodological assumptions limiting current models.

36 MATERIALS SCIENCE↗

Dynamic Acquisition and Retrieval Tool (DART) for Comet Sample Return : Session: 2.06.Robotic Mobility and Sample Acquisition Systems

The 2011 Decadal Survey for planetary science released by the National Research Council of the National Academies identified Comet Surface Sample Return (CSSR) as one of five high priority potential New Frontiers-class missions in the next decade. The main objectives of the research described in this publication are: develop a concept for an end-to-end system for collecting and storing a comet sample to be returned to Earth; design, fabricate and test a prototype Dynamic Acquisition and Retrieval Tool (DART) capable of collecting 500 cc sample in a canister and eject the canister with a predetermined speed; identify a set of simulants with physical properties at room temperature that suitably match the physical properties of the comet surface as it would be sampled. We propose the use of a dart that would be launched from the spacecraft to impact and penetrate the comet surface. After collecting the sample, the sample canister would be ejected at a speed greater than the comet's escape velocity and captured by the spacecraft, packaged into a return capsule and returned to Earth. The dart would be composed of an inner tube or sample canister, an outer tube, a decelerator, a means of capturing and retaining the sample, and a mechanism to eject the canister with the sample for later rendezvous with the spacecraft. One of the significant unknowns is the physical properties of the comet surface. Based on new findings from the recent Deep Impact comet encounter mission, we have limited our search of solutions for sampling materials to materials with 10 to 100 kPa shear strength in loose or consolidated form. As the possible range of values for the comet surface temperature is also significantly different than room temperature and testing at conditions other than the room temperature can become resource intensive, we sought sample simulants with physical properties at room temperature similar to the expected physical properties of the comet surface material. The chosen DART configuration, the efforts to identify a test simulant and the properties of these simulants, and the results of the preliminary testing will be described in this paper.

Dynamic Acquisition and Retrieval Tool (DART)↗

A machine learning based approach to online electron reconstruction at CLAS12

Online reconstruction is key for monitoring purposes and real time analysis in High Energy and Nuclear Physics experiments. A necessary component of reconstruction algorithms is particle identification that combines information left by a particle passing through several detector components to identify the particle’s type. Of particular interest to electro-production Nuclear Physics experiments such as CLAS12 is electron identification which is used to trigger data recording. A machine learning approach was developed for CLAS12 to reconstruct and identify electrons by combining raw signals at the data acquisition level from several detector components. Here, this approach achieves an electron identification purity above 75% whilst retaining an efficiency close to 100%. The machine learning tools are capable of running at high rates exceeding the data acquisition rates and will allow electron reconstruction in real-time. This work enhances online analyses and monitoring and can contribute to improved triggering at CLAS12. This machine learning driven approach will also be crucial for experiments aiming to transition to streaming readout operations where online reconstruction will be a key component of the data taking paradigm.

Artificial intelligence↗

Enhancing Power Grid Resilience with Causal Loops Diagram and Bayesian Networks

Enhancing power grid resilience through improved analysis and planning of Distributed Energy Resources is a key for power system planner. This paper explores the integration of Causal Loop Diagrams (CLDs) and Bayesian Networks (BNs) for enhancing resilience in power systems, focusing on Distributed Energy Resources (DER) planning. By automating CLD analysis in Python's matplotlib, we present a tool for rapid model validation and structural accuracy, crucial for power system planners. This hybrid approach utilizes BNs for inferential depth and CLDs for dynamic system modeling, offering a comprehensive framework for policy formulation and collaborative strategy development against disruptions. Here, we highlight the tool's capability to identify and analyze interconnected feedback loops, facilitating a deeper understanding of DER integration's impact on network resilience. This work aims to bridge quantitative analysis and qualitative insights, addressing the limitations of each method while providing a robust model for power system resilience assessment.

14 SOLAR ENERGY↗

Radio Frequency Field Programable Gate Array Implementation of Reflectometry Cable Monitoring

PNNL has developed an innovative cable testing system that leverages the Xilinx RF System-on-Chip (RFSoC) technology to create a more flexible and capable measurement tool than traditional approaches. The architecture is designed on the ZCU111 development board and takes advantage of the high-speed digital to analog converters (DAC) and analog to digital converters (ADC) to generate and capture digitally synthesized waveforms. The platform allows engineers to easily adjust power, frequency, duration and modulation on the fly rather than being locked into fixed hardware configurations

Tedeschi, Jonathan [Pacific Northwest National Lab↗

The Lithuania 100% Renewable Energy Study - Interim Results: Electricity System Scenarios for 2030 [Slides]

Lithuania's Energy Vision aims to achieve self-sufficiency in electricity generation by 2035 and transition to 100% renewable energy as soon as possible while maintaining affordability, reliability, and energy security. The Lithuania Energy Agency (LEA) is partnering with the National Renewable Energy Laboratory (NREL) to conduct the Lithuania 100% Renewable Energy Study (Lithuania 100) to provide evidence-based analysis for development of Lithuania's National Energy Independence Strategy. The Lithuania 100 Study leverages unique tools and capabilities of NREL to provide rigorous technical analysis of clean energy policies to achieve 100% renewable energy, and assess impacts on electricity grid operations, hydrogen system development, electricity distribution networks, air quality, and human health outcomes. The study is supported by a stakeholder committee chaired by the Ministry of Energy of Lithuania and implemented by four technical working groups. This report provides highlights of key interim results from modeling of Lithuania's near-term electricity grid through the year 2030. Results show that Lithuania has sufficient renewable energy potential, flexible generation capacity, and interconnection with neighboring European Union countries to reliably meet projected 2030 electricity demand with 100% renewable energy. A range of scenarios were modeled, each of which achieves at least 100% renewable energy in electricity, on average over the year, by 2030. Potential demands for hydrogen across industrial and transportation sectors were also evaluated, as well as the cost of hydrogen produced in Lithuania by 2030.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Advancing 1D thermo-hydraulic tools for large cryogenic facilities

The Cryogenic Division at Fermilab develops large-scale cryogenic systems for particle accelerators and superconducting test facilities. To support design and diagnostics, a Python-based code was created to calculate pressure drops in components such as valves and pipes. This paper presents recent enhancements to the code, including new heat transfer functions that improve the accuracy of thermal and hydraulic predictions. The first application models pressure and temperature changes in PIP-II relief pipes, aiding pipe sizing and protecting relief valves. The second example analyzes heat load evolution in a pipe carrying sub-atmospheric helium, helping interpret temperature sensor data and understand gas return behavior to cold compressors. These improvements significantly expand the tool’s capabilities, offering a practical resource for designing and troubleshooting cryogenic systems under dynamic thermal and flow conditions.

Beckwith, Rosalyn [Fermilab]↗

Community Requirements Meta-Analysis: Characterizing Needs and Opportunities for HPDF

This High Performance Data Facility (HPDF) Project is creating a new scientific user facility to provide advanced infrastructure for data-intensive science, supporting the DOE’s Office of Science (SC) community. HPDF’s mission is to enable and accelerate scientific discovery by delivering state-of-the-art data management infrastructure, capabilities, and tools. This meta-analysis examines the needs of the breadth of the SC community, captured in publicly available community reports or mission documents. The meta-analysis identifies and provides initial characterization of fifteen core requirements for the HPDF Project team to consider during the conceptual design phase. The fifteen requirements illustrate how scientific work among SC communities requires modern, seamless user experiences across the ASCR Ecosystem to advance the use of large volumes of heterogeneous data. The scientific community requires support for the missing middle of compute between local and HPC to interactively and collaboratively use growing datasets. Data producers and end users will benefit from enhanced data catalogs and portals that improve data access through advanced search of well curated data. The fifteen requirements are examined here organized across five themes for discussion. Examples in each theme illustrate the array of scientific needs that convey the important role that the fully realized and operational High Performance Data Facility will be able to play as an integral part of the evolving ASCR Ecosystem. Our amalgamated data tables from ESnet reports demonstrate ranges to the volumes of data HPDF must be concerned with, but limitations are inherent to this meta-analysis (see Key Challenges & Limitations). Feedback and validation of these requirements along with additional details and emergent community requirements will be gathered through user research and design activities.

97 MATHEMATICS AND COMPUTING↗

Advanced Load Forecasting

This presentation presents information about electric utility load forecasting in the U.S. It provides an overview of load forecasting and describes the current state of the industry. Current load forecasting challenges, opportunities, and interests are presented, including feedback from a 2024 workshop on Integrated Distribution System Planning. The presentation also describes a variety of NREL tools and capabilities that support utility load forecasting efforts. This was presented as part of NREL's Utility Planning Resources for Energy Transition Webinar Series.

24 POWER TRANSMISSION AND DISTRIBUTION↗