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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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29 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Collection: TD-DFT and EOM-CCSD Calculations for the GDB-9-Ex Dataset

We present two datasets that contain quantum chemical electronic structure calculations for organic molecules from the GDB-9-Ex dataset. The “GDB-9-Ex_TD-DFT-PBE0” dataset contains calculations performed using the time-dependent density functional theory (TD-DFT) first principles method, and the “GDB-9-Ex_EOMCCSD” dataset contains calculations performed using the equation-of-motion coupled cluster (EOM-CCSD) method. Both types of calculations were performed using the ORCA software and provided ultraviolet-visible spectra with a high level of accuracy.

Mehta, Kshitij [Oak Ridge National Laboratory (ORN↗
DOE OSTI2024

Dispatch Optimization Variable Engine

The Dispatch Optimization Variable Engine (DOVE) is software tool written in python, developed at Idaho National Laboratory (INL) that provides an easily accessible application-programming-interface (API) to performing resource dispatch optimization analysis for integrated energy system (IES) configurations. DOVE is an integral part of the Framework for Optimization of Resources and Economics (FORCE) software suite and is leveraged by codes such as the Holistic Energy Resource Optimization Network (HERON) and the Optimization of Real-Time Capacity Allocation (ORCA). The philosophy behind DOVE is to provide a modular software solution to IES planning and operation by utilizing state-of-the-art algorithms and machine learning. The goal is to accurately capture the dispatching behavior of a complex energy system given varying time-dependent signals for demand and commodity pricing.

McDowell, DylanJ. [Idaho National Laboratory (INL)↗
DOE OSTI2026

Dataset for Role of electron correlation on the adenine dimer interaction for non-equilibrium geometries: a benchmark Quantum Monte Carlo study

Datasets for the calculations reported in "Role of electron correlation on the adenine dimer interaction for non-equilibrium geometries: A benchmark Quantum Monte Carlo study" by L. Washburn, A. Sedova, P. R. C. Kent. J. Chem. Phys. (2026) 165 (5): 054118. https://doi.org/10.1063/5.0332651. Includes the molecular geometries, QMCPACK, PySCF, and ORCA inputs and outputs, analysis scripts and files needed to reproduce all the figures and tables.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2008

The Aerosol/Cloud/Ecosystems Mission (ACE)

The goals and measurement strategy of the Aerosol/Cloud/Ecosystems Mission (ACE) are described. ACE will help to answer fundamental science questions associated with aerosols, clouds, air quality and global ocean ecosystems. Specifically, the goals of ACE are: 1) to quantify aerosol-cloud interactions and to assess the impact of aerosols on the hydrological cycle and 2) determine Ocean Carbon Cycling and other ocean biological processes. It is expected that ACE will: narrow the uncertainty in aerosol-cloud-precipitation interaction and quantify the role of aerosols in climate change; measure the ocean ecosystem changes and precisely quantify ocean carbon uptake; and, improve air quality forecasting by determining the height and type of aerosols being transported long distances. Overviews are provided of the aerosol-cloud community measurement strategy, aerosol and cloud observations over South Asia, and ocean biology research goals. Instruments used in the measurement strategy of the ACE mission are also highlighted, including: multi-beam lidar, multiwavelength high spectra resolution lidar, the ocean color instrument (ORCA)--a spectroradiometer for ocean remote sensing, dual frequency cloud radar and high- and low-frequency micron-wave radiometer. Future steps for the ACE mission include refining measurement requirements and carrying out additional instrument and payload studies.

Schoeberl, Mark↗
NASA NTRSDate not supplied

COBRA-DDP: Trajectory Generation and Collision Avoidance Augmentations for eVTOL Vehicles

This paper presents a receding horizon model predictive control variation of the combined Bernstein polynomial optimal reciprocal collision avoidance (ORCA) differential dynamic programming (COBRA-DDP) algorithm for AAM vehicles. Collision avoidance in combination with effective trajectory replanning are expected to be core components of AAM vehicles operating within a crowded airspace. This environment necessitates the use of real-time trajectory planning algorithms that are capable of planning around large amounts of stationary and moving obstacles. Previous work on COBRA-DDP demonstrated the capability of the algorithm to produce dynamically feasible trajectories for AAM vehicles and general collision avoidance. This paper improves upon the previous work by increasing the number of stationary and moving obstacles, implementing a variation of COBRA-DDP that lends itself to real-time application. These advancements are demonstrated on a vertical takeoff and landing (VTOL) vehicle simulation with highly nonlinear vehicle dynamics.

COBRA-DDP↗
NASA NTRSDate not supplied

COBRA-DDP: Trajectory Generation and Collision Avoidance Augmentations for eVTOL Vehicles

This paper presents a receding horizon model predictive control variation of the combined Bernstein polynomial optimal reciprocal collision avoidance (ORCA) differential dynamic programming (COBRA-DDP) algorithm for AAM vehicles. Collision avoidance in combination with effective trajectory replanning are expected to be core components of AAM vehicles operating within a crowded airspace. This environment necessitates the use of real-time trajectory planning algorithms that are capable of planning around large amounts of stationary and moving obstacles. Previous work on COBRA-DDP demonstrated the capability of the algorithm to produce dynamically feasible trajectories for AAM vehicles and general collision avoidance. This paper improves upon the previous work by increasing the number of stationary and moving obstacles, implementing a variation of COBRA-DDP that lends itself to real-time application. These advancements are demonstrated on a vertical takeoff and landing (VTOL) vehicle simulation with highly nonlinear vehicle dynamics.

COBRA-DDP↗
DOE OSTI2024

FORCE Regression Testing

Via programs including the Light Water Reactor Sustainability and Integrated Energy Systems, the U.S. Department of Energy has invested in the Framework for Optimization of ResourCes and Economics (FORCE) software framework (Idaho National Laboratory 2024a) for the technical and economic analysis of nuclear-integrated energy systems (IES). Nuclear IES expand the use of nuclear from traditional baseload electricity generation to a flexible and adaptive source of combined heat and power. Nuclear heat can be used in the production of a variety of energy currencies such as hydrogen and ammonia as well as other heat applications including water desalination and district heating. FORCE is designed with the intent to provide interconnected analysis tools that enable the accurate technical and economic assessment of specific nuclear IES configurations for individual energy markets. FORCE consists of three main analysis pathways: HYBRID (Idaho National Laboratory 2024b), which contains high-resolution physical models for IES; Holistic Energy Resource Optimization Network (HERON) (Idaho National Laboratory 2024c), which analyzes IES long-term economic viability; and Optimization of Real-time Capacity Allocation (ORCA) (Idaho National Laboratory 2024d), designed for real-time control of IES via digital twins and optimal decision making, including autonomous and remote operation research. Development of the FORCE ecosystem is guided by three pillars: capability, which assures that the computational requirements of IES analysis are met by the software tools; reliability, which provides for consistent code performance and expected behaviors; and accessibility, which lowers the barrier to entry for using the software and accelerates analysis by users beyond the FORCE primary developers. Reliability of the FORCE ecosystem is established according to the American Nuclear Society?s Nuclear Quality Assurance (NQA-1) program [American Society of Mechanical Engineers 1982], with specific levels of software quality assurance (SQA) within NQA-1 applied to each software tool in FORCE. As the tools within FORCE have matured, some integration algorithms to accurately connect the software tools for holistic analysis have been developed and deployed within the FORCE software repository. In accordance with NQA-1 standards, regression tests are required to guarantee the software performs consistently even when new capabilities are added to the software. In this report, we document the deployment of both unit tests, which test the consistent behavior of small pieces of the FORCE code base, as well as integration tests, which test the consistent performance of full use cases for the FORCE integration algorithms. We further document the encapsulation of these tests within a test harness, which collectively checks for each successful test completion on demand. Finally, we document the automation of the test harness using GitHub Actions [GitHub 2024], which require all tests succeed before any new capability or other changes can be added to the FORCE integration software

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

The levelized cost of exergy: a technoeconomic framework for energy system comparison

While the levelized costs of electricity and heat have been quantified before, these two metrics cannot be directly compared, due to the different exergy content of heat and work. To address this, we develop a levelized cost of exergy (LCOEx) framework that enables direct comparisons between energy sources and processes. We find that moderate- and high-grade heat have an LCOEx that is comparable to electricity (5–10 ¢ per kWh ex ), while low-grade heat sources have much higher LCOEx values (>50 ¢ per kWh ex ). The LCOEx of a system's output is affected by (i) the LCOEx of the system input, (ii) the CAPEX of the system, and (iii) the exergetic efficiency of the system. We use our framework to identify which processes are already achieved with relatively high cost effectiveness (production of fuels, hydrogen, and ammonia) and which have room for improvement (dehumidification, food production).

08 HYDROGEN↗
NASA NTRSDate not supplied

HWO Technology Development

Explore the source record for details and available documents.

Habitable Worlds Observatory↗