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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 1,765 records · Page 98

Developing a Crew Time Model for Human Exploration Missions to Mars

Candidate human missions to Mars require mission lengths that could extend beyond those that have previously been demonstrated during crewed Lunar (Apollo) and International Space Station (ISS) missions. The nature of the architectures required for deep space human exploration will likely necessitate major changes in how crews operate and maintain the spacecraft. The uncertainties associated with these shifts in mission constructs - including changes to habitation systems, transit durations, and system operations - raise concerns as to the ability of the crew to complete required overhead activities while still having time to conduct a set of robust exploration activities. This paper will present an initial assessment of crew operational requirements for human missions to the Mars surface. The presented results integrate assessments of crew habitation, system maintenance, and utilization to present a comprehensive analysis of potential crew time usage. Destination operations were assessed for a short (approx. 50 day) and long duration (approx. 500 day) surface habitation case. Crew time allocations are broken out by mission segment, and the availability of utilization opportunities was evaluated throughout the entire mission progression. To support this assessment, the integrated crew operations model (ICOM) was developed. ICOM was used to parse overhead, maintenance and system repair, and destination operations requirements within each mission segment - outbound transit, Mars surface duration, and return transit - to develop a comprehensive estimation of exploration crew time allocations. Overhead operational requirements included daily crew operations, health maintenance activities, and down time. Maintenance and repair operational allocations are derived using the Exploration Maintainability and Analysis Tool (EMAT) to develop a probabilistic estimation of crew repair time necessary to maintain systems functionality throughout the mission.

Battfeld, Bryan↗

Workshop Summary: Bridging the Gap Between Atmospheric Science and Grid Integration

The need for dedicated, accurate, expertly curated weather data is increasingly important as the share of variable renewable energy increases on the power system. Projections for futures with very high (50+% annual energy) shares of variable generation require ongoing assessment of data requirements from industry stakeholders in their power system operation and planning contexts. In March 2024, NREL organized a workshop entitled "Bridging the Gap Between Atmospheric Science and Grid Integration Workshop", which brought atmospheric scientists and power system experts together to refine the requirements of atmospheric datasets for grid integration, and to describe a holistic approach to creating new and regularly updated national scale wind datasets for power system planning and operations. The results of this workshop are being used to inform the near-term development and a longer-term strategy for DOE to produce relevant wind resource datasets and inform wider use of wind/solar/load data sets in power system planning. This presentation provides an overview of a preworkshop survey, an assessment of current state of the art of national-scale datasets for wind resource assessment and grid integration, insights on appropriate uses of the WTK-LED, power system perspectives on data needs, as well as recommended next steps as discussed in the workshop and how these steps support longer-term strategies.

17 WIND ENERGY↗

The evaluation of critical rare earth element (REE) enriched treatment solids from coal mine drainage passive treatment systems

Rare earth elements (REE; lanthanides and Y) are essential for the development of clean energy technologies. Global demand for REE is expected to increase sharply in the coming decades, especially for certain energy-critical REE (e.g., Y and Nd), spurring investigations into novel sources of REEs. Polluted mine drainage from eastern U.S. coalfields contains elevated concentrations of dissolved Fe, Al, and Mn and is also enriched in REE by up to three orders of magnitude over unpolluted groundwater. Mine drainage remediation systems, designed to precipitate dissolved metals, can sequester >90% of dissolved REE into the precipitated solids (treatment solids). These solids, landfilled at cost to treatment system operators, are a promising REE source. Passive treatment systems with diverse geochemical environments were sampled to determine REE mobility in these systems and REE concentrations in treatment solids. Passive treatment systems were found to produce middle and heavy REE-enriched solids, relative to the North American Shale Composite, with up to 1950 ppm REE and 55% energy-critical REE. SEM-EDS and synchrotron μ-XRF analysis demonstrate the association of REE with Mn-oxide coatings on limestone from a passive treatment system. Calculated concentration factors indicate that passive treatment systems using natural processes (e.g., drainable limestone beds and vertical flow ponds) concentrate REE into treatment solids approximately three times more effectively compared to active treatment systems using caustic chemical additions (e.g., lime). This study suggests that passive treatment systems effectively concentrate REE into treatment solids and these solids could be an alternative and more environmentally friendly source of REE compared to conventional mining on land or the seafloor. Results of this study can also aid in the design of treatment systems engineered to remove and concentrate critical REE which could provide a financial incentive to treat polluted mine water.

58 GEOSCIENCES↗

Formation and reconfiguration of tight multi-lane platoons

Advances in vehicular communication technologies are expected to facilitate cooperative driving in the future. Connected and Automated Vehicles (CAVs) are able to collaboratively plan and execute driving maneuvers by sharing their perceptual knowledge and future plans. In this paper, an architecture for autonomous navigation of tight multi-lane platoons traveling on public roads is presented. Using the proposed approach, CAVs are able to form single or multi-lane platoons of various geometrical configurations. They are able to reshape and adjust their configurations according to changes in the environment. The proposed architecture consists of two main components: an offline motion planner system and an online hierarchical control system. The motion planner uses an optimization-based approach for cooperative formation and reconfiguration in tight spaces. A constrained optimization scheme is used to plan smooth, dynamically feasible and collision-free trajectories for all the vehicles within the platoon. The paper addresses online computation limitations by employing a family of maneuvers precomputed offline and stored on a look-up table on the vehicles. The online hierarchical control system is composed of three levels: a traffic operation system (TOS), a decision-maker, and a path-follower. The TOS determines the desired platoon reconfiguration. The decision-maker checks the feasibility of the reconfiguration plan based on real-time information about the surrounding traffic. The reconfiguration maneuver is executed by a low-level path-following feedback controller in real-time. The effectiveness of the approach is demonstrated through simulations of three case studies: (1) formation reconfiguration (2) obstacle avoidance, and (3) benchmarking against behavior-based planning in which the desired formation is achieved using a sequence of motion primitives.

42 ENGINEERING↗

A review of active probing-based system identification techniques with applications in power systems

System identification is becoming a relevant research area for numerous applications in power grids due to the increasing complexity of the system. A paradigm shift in power system infrastructure driven by renewable energy resources, controllable loads, and new power electronics technologies have given rise to new challenges in power systems operation and control. This increased complexity of power systems and unavailability of physics-based models of most inverter-based resources requires that traditional modeling of power systems approaches be complemented by system identification-based black or grey box modeling techniques. In light of the importance of system identification and little attention paid to the applications of these techniques in transforming power systems, this paper provides a comprehensive review of active probing-based system identification methods in the context of power system applications. It reviews applications of both linear and nonlinear system identification with discussion on their potential and key takeaways. To motivate a further practical use in power systems, the paper provides an example of system identification, to develop a state space model of an unknown plant with step-by-step details. The paper highlights the advantages of using modern power electronics-based sources in the identification process and discusses the emerging research directions for future.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Trans-oceanic Remote Power Hardware-in-the-Loop: Multi-site Hardware, Integrated Controller, and Electric Network Co-simulation

Electric system operators are increasingly concerned with the potential system-wide impacts of the large-scale integration of distributed energy resources (DERs) including voltage control, protection coordination, and equipment wear. This prompts a need for new simulation techniques that can simultaneously capture all the components of these large integrated smart grid systems. This paper describes a novel platform that combines three emerging research areas: power systems co-simulation, power hardware in the loop (PHIL) simulation, and lab-lab links. The platform is distributed, real-time capable, allows for easy internet-based connection from geographically-dispersed participants, and is software platform agnostic. We demonstrate its utility by studying real-time PHIL co-simulation of coordinated solar PV firming control of two inverters connected in multiple electric distribution network models, prototypical of U.S. and Australian systems. Here, the novel trans-pacific closed-loop system simulation was conducted in real-time using a power network simulator and physical PV/battery inverter at power at the National Renewable Energy Laboratory in Golden, CO, USA and a physical PV inverter at power at the Commonwealth Scientific and Industrial Research Organisation's Energy Centre in Newcastle, NSW, Australia. This capability enables smart grid researchers throughout the world to leverage their unique simulation capabilities for multi-site collaborations that can effectively simulate and validate emerging smart grid technology solutions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Human Factors Considerations in Artificial Intelligence Applications for Nuclear Power Plants

In recent years, there has been a wave of artificial intelligence (AI) technologies that offer to solve problems from shopping habits to mortgage approvals to critical systems operations. The rapidity of the development of these systems has led to both excitement and apprehension about the roles these systems should play in our modern societies. Furthermore, this paper focuses on the critical infrastructure industry, in general, and nuclear power generation, in particular, and seeks to scrutinize how we can leverage these novel technologies in human-centered ways to maintain or enhance the established high levels of reliability and resilience in these industries. First, we discuss the broader aspects of cognitive systems and activities that are critical to understanding the human-AI space. Then we explore different approaches to explainability in AI and the notions of trust. We then move on to discuss several human factors concepts and methods and how they can support the design of human-AI teams. We then explore recent research related to nuclear power that has been undertaken and evaluate the current industry and regulatory landscapes. Finally, we discuss identified research gaps and recommendations for solving these for the critical infrastructure space.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

A Runtime Environment for Supporting Research in Resilient HPC System Software & Tools

The high-performance computing (HPC) community continues to increase the size and complexity of hardware platforms that support advanced scientific workloads. The runtime environment (RTE) is a crucial layer in the software stack for these large-scale systems. The RTE manages the interface between the operating system and the application running in parallel on the machine. The deployment of applications and tools on large-scale HPC computing systems requires the RTE to manage process creation in a scalable manner, support sparse connectivity, and provide fault tolerance. We have developed a new RTE that provides a basis for building distributed execution environments and developing tools for HPC to aid research in system software and resilience. This paper describes the software architecture of the Scalable runTime Component Infrastructure (STCI), which is intended to provide a complete infrastructure for scalable start-up and management of many processes in large-scale HPC systems. We highlight features of the current implementation, which is provided as a system library that allows developers to easily use and integrate STCI in their tools and/or applications. The motivation for this work has been to support ongoing research activities in fault-tolerance for large-scale systems. We discuss the advantages of the modular framework employed and describe two use cases that demonstrate its capabilities: (i) an alternate runtime for a Message Passing Interface (MPI) stack, and (ii) a distributed control and communication substrate for a fault-injection tool.

Computer Science↗

Bidding Curve Design for Hybrid Power Plants with Uncertain Solar Forecast

This paper presents a novel bidding curve design algorithm tailored for hybrid power plants (HPPs) to participate in the wholesale electricity market. Utilizing forecasts for photovoltaic (PV) generation and available battery power, our algorithm strategically computes the bidding curve to maximize HPP profit while adeptly managing the inherent uncertainty associated with PV power generation. In addition, the introduction of the penalty cost in HPP bidding curves provides the system operator a tool to effectively manage the system-level uncertainty that caused by HPPs. Numerical analysis through Monte Carlo simulations confirms that our bidding curve methodology outperforms the benchmark across various scenarios.

bidding curve↗

Grid-Forming Inverters: Project Demonstrations and Pilots

Power system operators around the world are pushing the limits of integrating inverter-based resources (IBRs) to very high levels, approaching 100% instantaneous penetration under certain operating conditions. This often applies to smaller power systems with very little or no ac interconnections to other neighboring regions or sometimes to fringes of large balancing areas, such as Denmark or Portugal, within the mainland European power system. These jurisdictions have identified the potential of grid-forming (GFM) technology as a key enabler to support the energy transition with very few or no synchronous generators online. Until recently, practical applications of GFM inverters were limited to microgrids and isolated grids and in smaller grid applications on the order of a few tens of megawatts (MW).

Australia↗

Experiences Integrating Transmission and Distribution Simulations for DERs with the Integrated Grid Modeling System (IGMS)

This paper discusses the development of, approaches for, experiences with, and some results from a large-scale, high-performance-computer-based (HPC-based) co-simulation of electric power transmission and distribution systems using the Integrated Grid Modeling System (IGMS). IGMS was developed at the National Renewable Energy Laboratory (NREL) as a novel Independent System Operator (ISO)-to-appliance scale electric power system modeling platform that combines off-the-shelf tools to simultaneously model 100s to 1000s of distribution systems in co-simulation with detailed ISO markets, transmission power flows, and AGC-level reserve deployment. Lessons learned from the co-simulation architecture development are shared, along with a case study that explores the reactive power impacts of PV inverter voltage support on the bulk power system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Real-World Distribution System Modeling Framework for Transmission-and-Distribution Cosimulation: Preprint

This paper presents a modeling methodology for realistic distribution system simulation and analysis. The methodology involves three major approaches: utility model conversion, feeder load modeling, and feeder model validation. The feeder models obtained from the utility are converted to the format that is more flexible for analysis and algorithm development. The load profiles down to each node are modeled in detail using advanced metering infrastructure data and supervisory control and data acquisition (SCADA) system measured load data. Then the distribution system models are validated by comparing the simulated feeder-head voltage results and SCADA measured voltage data. To better understand the bulk system operations and the interactions between transmission and distribution systems, the modeled realistic distribution systems are integrated into a transmission-and-distribution cosimulation framework to perform the system simulation from the bulk system down to each node in the distribution system.

load modeling↗

Wind Power Ramping Product for Increasing Power System Flexibility

With increasing penetrations of wind power, system operators are concerned about a potential lack of system flexibility and ramping capacity in real-time dispatch stages. In this paper, a modified dispatch formulation is proposed considering the wind power ramping product (WPRP). A swinging door algorithm (SDA) and dynamic programming are combined and used to detect WPRPs in the next scheduling periods. The detected WPRPs are included in the unit commitment (UC) formulation considering ramping capacity limits, active power limits, and flexible ramping requirements. The modified formulation is solved by mixed integer linear programming. Numerical simulations on a modified PJM 5-bus System show the effectiveness of the model considering WPRP, which not only reduces the production cost but also does not affect the generation schedules of thermal units.

17 WIND ENERGY↗

MarFS-Requirements-Design-Configuration-Admin

This document will be organized into sections that are defined by the requirements for a file system that presents a near-POSIX (Portable Operating System Interface) interface to the user, but whose data is stored in whatever form is most efficient for the type of data being stored. After defining the requirement the design for meeting the requirement will be explained. Finally there will be sections on configuring and administering this file system. More and more, data dominates the computing world. There is a “sea” of data out there in many different formats that needs to be managed and used. “Mar” means “sea” in Spanish. Thus, this product is dubbed MarFS, a file system for a sea of data.

97 MATHEMATICS AND COMPUTING↗

Adaptive Fault Detection Based on Neural Networks and Multiple Sampling Points for Distribution Networks and Microgrids

Smart networks such as microgrid (MG) and active distribution networks (ADN) have been recently playing an important role in power system operation. The design and implementation of appropriate protection systems for such networks must be addressed, which imposes new technical challenges. This paper presents the implementation and validation aspects of an adaptive fault detection strategy based on neural networks (NNs) and multiple sampling points for ADN and MG. The solution is implemented on an edge device. Artificial NNs are used to derive a data-driven model that uses only local measurements to detect fault states of the network without the need for communication infrastructure. Multiple sampling points are used to derive a data-driven model, which allows the generalization considering the implementation in physical systems. The adaptive fault detector model is implemented on a Jetson Nano system, which is a single-board computer (SBC) with a small Graphic Processing Unit (GPU) intended to run machine learning loads at the edge. The proposed method is tested in a physical, real-life, low-voltage network located at Universidad del Norte, Colombia. This testing network is based on the IEEE-13 Node Test Feeder scaled down to 220 V. The validation in a simulation environment shows the accuracy and dependability above 99.6%, while the real-time tests show the accuracy and dependability of 95.5% and 100%, respectively. Without hard-to-derive parameters, the easy-to-implement embedded model highlights the potential for real-life applications.

42 ENGINEERING↗

Study of alternate methods of disposal of propellants and gases at KSC

A comprehensive study was conducted at KSC launch support facilities to determine the nature and extent of potential hazards from propellant and gas releases to the environment. The results of the study, alternate methods for reducing or eliminating the hazards, and recommendations pertaining to these alternatives are presented. The operational modes of the propellant or hazardous gas systems considered include: system charging, system standby, system operation, and post-test operations. The results are outlined on an area-by-area basis.

Moore, W. I.↗

Portable Oxygen Subsystem (POS)

Concept selection, design, fabrication, and testing of a Portable Subsystem (POS) for use in space shuttle operations are described. Tradeoff analyses were conducted to determine the POS concept for fabrication and testing. The fabricated POS was subjected to unmanned and manned tests to verify compliance with statement of work requirements. The POS used in the development program described herein met requirements for the three operational modes -- prebreathing, contaminated cabin, and personnel rescue system operations.

Source record↗

Orbiter CCTV video signal noise analysis

The amount of steady state and transient noise which will couple to orbiter CCTV video signal wiring is predicted. The primary emphasis is on the interim system, however, some predictions are made concerning the operational system wiring in the cabin area. Noise sources considered are RF fields from on board transmitters, precipitation static, induced lightning currents, and induced noise from adjacent wiring. The most significant source is noise coupled to video circuits from associated circuits in common connectors. Video signal crosstalk is the primary cause of steady state interference, and mechanically switched control functions cause the largest induced transients.

Lawton, R. M.↗