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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 523 records · Page 29

Recyclable Design for Retaining High Solar Absorptivity of the Media in CSP

Efficient thermal energy storage is pivotal to lowering the levelized cost of electricity (LCOE) for Concentrating Solar Power (CSP) plants. In solid-particle systems, however, prolonged high-temperature service degrades particle solar absorptivity, eroding overall efficiency. This project demonstrates a hydrogen-assisted recovery process that reliably restores absorptivity to >90 %, offering a practical route to sustain long-term CSP performance. Bench-scale investigations mapped the reduction kinetics of optically faded particles across hydrogen concentrations, temperatures, and residence times. Coupling mass-spectrometric monitoring with machine-learning optimization minimized energy demand while maximizing absorptivity gain. The resulting process window—moderate hydrogen partial pressures, 15–30 min dwell times, and temperatures well below initial calcination levels—cuts energy consumption well below that of incumbent re-blackening methods. A prototype recovery reactor processed multiple 2 kg batches with repeatable outcomes, confirming scalability and operational robustness. Integrated techno-economic analysis indicates material and operating cost reductions exceeding 15 % relative to conventional particle replacement or chemical re-coating, translating directly into lower LCOE for next-generation CSP facilities. By uniting fundamental reaction-kinetics insight with pragmatic engineering, this work advances the solid-particle pathway, delivering a cost-effective, field-deployable solution to one of CSP’s key durability challenges and strengthening the commercial outlook for high-temperature renewable power.

14 SOLAR ENERGY↗

Operational Overview for UAS Integration in the NAS Project Flight Test Series 3

The National Aeronautics and Space Administration Unmanned Aircraft Systems Integration in the National Airspace System Project has conducted a series of flight tests intended to support the reduction of barriers that prevent unmanned aircraft from flying without the required waivers from the Federal Aviation Administration. The 2015 Flight Test Series 3, supported two separate test configurations. The first configuration investigated the timing of Detect and Avoid alerting thresholds using a radar equipped unmanned vehicle and multiple live intruders flown at varying encounter geometries. The second configuration included a surrogate unmanned vehicle (flown from a ground control station, with a safety pilot on board) flying a mission in a virtual air traffic control airspace sector using research pilot displays and Detect and Avoid advisories to maintain separation from live and virtual aircraft. The test was conducted over an eight-week span within the R-2508 Special Use Airspace. Over 200 encounters were flown for the first configuration, and although the second configuration was cancelled after three data collection flights, Flight Test 3 proved to be invaluable for the purposes of planning, managing, and execution of this type of integrated flight test.

unmanned aircraft systems↗

Operational Overview for UAS Integration in the NAS Project Flight Test Series 3

The National Aeronautics and Space Administration Unmanned Aircraft Systems Integration in the National Airspace System Project has conducted a series of flight tests intended to support the reduction of barriers that prevent unmanned aircraft from flying without the required waivers from the Federal Aviation Administration. The 2015 Flight Test Series 3, supported two separate test configurations. The first configuration investigated the timing of Detect and Avoid alerting thresholds using a radar equipped unmanned vehicle and multiple live intruders flown at varying encounter geometries.

UAS in the NAS↗

Air Traffic Management Technology Demonstration - 3 (ATD-3): Operational Concept for the Integration of ATD-3 Capabilities Version 1.0

ATD-3 has developed four capabilities to address its goal and objectives. The four ATD-3 capabilities include: Dynamic Weather Routes (DWR), Multi-Flight Common Routes (MFCR), Traffic Aware Strategic Aircrew Requests (TASAR), and Dynamic Routes for Arrivals in Weather (DRAW). This document describes the long-term, mature vision for the use and incorporation of the ATD-3 capabilities into the National Airspace System (NAS). This vision describes their complementary interaction and the benefit capture that accrues from use. Recognizing that all capabilities are unlikely to be implemented in unison, each of the capabilities is designed and able to be implemented independently. As discrete portions of the integrated capabilities are planned, additional integration efforts should be undertaken to validate the complementary interactions and benefit pool are realized from the selected subset.

ConOps↗

Autonomous Drone Integration in Prescribed Fire Operations

With the surge in wildfire frequency and severity, the risk to firefighters, communities, and forests has escalated dramatically. Climate change and increased amounts of fuel have intensified these challenges, making wildfire management more important than ever. Prescribed burns, a controlled manner of burning land, are a crucial strategy for wildfire prevention, ecosystem management, and forest health. Nonetheless, traditional methods of implementing prescribed burns are labor-intensive, slow, and risk-laden due to human involvement. Our innovative approach leverages autonomous drone swarms to revolutionize prescribed burning methods. These advanced drones collaborate to ignite fires strategically, gather real-time data, and suppress sections of the fire as needed. By minimizing human proximity to the flames, our solution has the potential to significantly enhance operational efficiency and safety.

UAV systems↗

Integrating Cybersecurity with System Operations and Restoration

This presentation covers the interaction of the discipline of system operations with the discipline of cybersecurity. First is discussion of a number of fundamental concepts for system operators - organizational division of responsibilities, human and machine cooperation, goals, and priorities. The next section covers the importance of cybersecurity for a system operator organization and explains different risk management approaches based on the consequence and frequency of events. Finally the role of system operators in the security of the grid categorized by the NIST Cybersecurity Framework is discussed to present recommendations and ideas for future work.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Integrated System Health Management: Pilot Operational Implementation in a Rocket Engine Test Stand

This paper describes a credible implementation of integrated system health management (ISHM) capability, as a pilot operational system. Important core elements that make possible fielding and evolution of ISHM capability have been validated in a rocket engine test stand, encompassing all phases of operation: stand-by, pre-test, test, and post-test. The core elements include an architecture (hardware/software) for ISHM, gateways for streaming real-time data from the data acquisition system into the ISHM system, automated configuration management employing transducer electronic data sheets (TEDS?s) adhering to the IEEE 1451.4 Standard for Smart Sensors and Actuators, broadcasting and capture of sensor measurements and health information adhering to the IEEE 1451.1 Standard for Smart Sensors and Actuators, user interfaces for management of redlines/bluelines, and establishment of a health assessment database system (HADS) and browser for extensive post-test analysis. The ISHM system was installed in the Test Control Room, where test operators were exposed to the capability. All functionalities of the pilot implementation were validated during testing and in post-test data streaming through the ISHM system. The implementation enabled significant improvements in awareness about the status of the test stand, and events and their causes/consequences. The architecture and software elements embody a systems engineering, knowledge-based approach; in conjunction with object-oriented environments. These qualities are permitting systematic augmentation of the capability and scaling to encompass other subsystems.

Figueroa, Fernando↗

Operation Optimization Using Reinforcement Learning with Integrated Artificial Reasoning Framework

In large and complex systems, operational decision-making requires a systematic analysis with a vast amount of data from both process parameters and component status monitoring. In this paper, we present an integrated artificial reasoning approach for system state transition models that can help operational decision-making with explainable and traceable reasoning. The integrated artificial reasoning framework is a physics-based approach of defining the system structure in a Bayesian network, so we leveraged it in a Markov decision process (MDP) for finding optimal operational solutions. In our proposed framework, the MDP is implemented on a dynamic Bayesian network (DBN), which represents causalities in a system. The multilevel flow modeling was utilized in order to extract these causalities in a more efficient and objective manner. Since multilevel flow modeling is based on the fundamental energy and mass conservation laws, the target system is decomposed into several mass, energy, and information structures, which serve as the basis for a DBN. The MDP consists of the processes of finding a solution for the Bellman equation, which can be derived from the conditional probability equations of the constructed DBN. System operators can capture stochastic system dynamics as multiple subsystem state transitions based on their physical relations and uncertainties coming from the component degradation process or random failures. We analyzed a simplified example system to illustrate finding an optimal operational policy with this approach.

Kim, Junyung↗

CONFIG: Integrated engineering of systems and their operation

This article discusses CONFIG 3, a prototype software tool that supports integrated conceptual design evaluation from early in the product life cycle, by supporting isolated or integrated modeling, simulation, and analysis of the function, structure, behavior, failures and operations of system designs. Integration and reuse of models is supported in an object-oriented environment providing capabilities for graph analysis and discrete event simulation. CONFIG supports integration among diverse modeling approaches (component view, configuration or flow path view, and procedure view) and diverse simulation and analysis approaches. CONFIG is designed to support integrated engineering in diverse design domains, including mechanical and electro-mechanical systems, distributed computer systems, and chemical processing and transport systems.

Malin, Jane T.↗

VFR Trajectory Forecasting using Deep Generative Model for Autonomous Airspace Operations

To enable the airspace integration of autonomous operations, such as uncrewed aircraft conducting cargo deliveries, there is a need to forecast the positions of the surrounding traffic with which they may interact. This paper focuses on forecasting Visual Flight Rules traffic, a significant source of uncertainty and risk in the airspace, especially around small regional airports, due to the unplanned and often untracked nature of such flights. A deep generative model is developed, trained on historical traffic data at example towered and non-towered airports, and used to predict flight trajectories. Experimental results are presented comparing the performance of variational autoencoder and classical machine learning forecasting when applied to both the towered and non-towered airports over varying time horizons. The results show the advantages of the variational autoencoder in producing accurate probabilistic forecasts over varying time horizons.

uncrewed aircraft↗

VFR Trajectory Forecasting using Deep Generative Model for Autonomous Airspace Operations

To enable the airspace integration of autonomous operations, such as uncrewed aircraft conducting cargo deliveries, there is a need to forecast the positions of the surrounding traffic with which they may interact. This paper focuses on forecasting Visual Flight Rules traffic, a significant source of uncertainty and risk in the airspace, especially around small regional airports, due to the unplanned and often untracked nature of such flights. A deep generative model is developed, trained on historical traffic data at example towered and non-towered airports, and used to predict flight trajectories. Experimental results are presented comparing the performance of variational autoencoder and classical machine learning forecasting when applied to both the towered and non-towered airports over varying time horizons. The results show the advantages of the variational autoencoder in producing accurate probabilistic forecasts over varying time horizons.

uncrewed aircraft↗

A comparison of artificial compressibility and fractional step methods for incompressible flow computations

We have applied and compared the efficiency and accuracy of two commonly used numerical methods for the solution of Navier-Stokes equations. The artificial compressibility method augments the continuity equation with a transient pressure term and allows one to solve the modified equations as a coupled system. Due to its implicit nature, one can have the luxury of taking a large temporal integration step at the expense of higher memory requirement and larger operation counts per step. Meanwhile, the fractional step method splits the Navier-Stokes equations into a sequence of differential operators and integrates them in multiple steps. The memory requirement and operation count per time step are low, however, the restriction on the size of time marching step is more severe. To explore the strengths and weaknesses of these two methods, we used them for the computation of a two-dimensional driven cavity flow with Reynolds number of 100 and 1000, respectively. Three grid sizes, 41 x 41, 81 x 81, and 161 x 161 were used. The computations were considered after the L2-norm of the change of the dependent variables in two consecutive time steps has fallen below 10(exp -5).

Chan, Daniel C.↗

Air Traffic Management Technology Demonstration-1 Concept of Operations (ATD-1 ConOps), Version 2.0

This document is an update to the operations and procedures envisioned for NASA s Air Traffic Management (ATM) Technology Demonstration #1 (ATD-1). The ATD-1 Concept of Operations (ConOps) integrates three NASA technologies to achieve high throughput, fuel-efficient arrival operations into busy terminal airspace. They are Traffic Management Advisor with Terminal Metering (TMA-TM) for precise time-based schedules to the runway and points within the terminal area, Controller-Managed Spacing (CMS) decision support tools for terminal controllers to better manage aircraft delay using speed control, and Flight deck Interval Management (FIM) avionics and flight crew procedures to conduct airborne spacing operations. The ATD-1 concept provides de-conflicted and efficient operations of multiple arrival streams of aircraft, passing through multiple merge points, from top-of-descent (TOD) to the Final Approach Fix. These arrival streams are Optimized Profile Descents (OPDs) from en route altitude to the runway, using primarily speed control to maintain separation and schedule. The ATD-1 project is currently addressing the challenges of integrating the three technologies, and their implantation into an operational environment. The ATD-1 goals include increasing the throughput of high-density airports, reducing controller workload, increasing efficiency of arrival operations and the frequency of trajectory-based operations, and promoting aircraft ADS-B equipage.

Baxley, Brian T.↗

Integrated operations/payloads/fleet analysis. Volume 5: Mission, capture and operations analysis

The current baseline mission model consists of the DOD Option B prepared for space transportation system mission analysis and a NASA model prepared for the integrated operations /payloads/ fleet analysis. Changes from the previous mission model are discussed, and additional benefits of the reusable space shuttle system are identified. The methodology and assumptions used in the capture analysis are described, and satellite and launch vehicle traffic models for the current and low cost expendable launch vehicle systems and the reusable space shuttle system are presented. The areas of fleet sizing, limitations and abort modes, system ground support requirements, and ground support systems assessment are covered. Current and extended launch azimuth limitations used for both ETR and WTR are presented for the current and low cost expendable vehicles and also the reusable space shuttle system. The results of a survey of launch support capability for the launch vehicle fleets are reported.

Source record↗

Integration of Automation Systems Flight Test Overview

This short presentation outlines an upcoming flight test to be performed as part of the Advanced Air Mobility (AAM) project. Referred to as the Integration of Automated Systems (IAS) flight test series, the objectives are to evaluate NASA research concepts and technologies for complex operations through integrated automation and candidate operational concepts and scenarios. The primary objective is to test mature AAM technologies in a relevant environment. The two primary systems under test are the Flight Path Management (FPM) and Hazard Perception and Avoidance (HPA) technology. This presentation focuses on the HPA technology developed by the FAA known as the Airborne Collision Avoidance System X for Rotorcraft (ACAS Xr) since the audience consists of committee members currently working on developing the minimum requirements for this system. The second half of the presentation explains the primary objectives and describes the scenarios expected to be tested in flight.

automation↗