Search NASASearch

SEARCH · Search NASA

Results for “ORCA”

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.

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

At least 19 records

Optical Component Performance for the Ocean Radiometer for Carbon Assessment (ORCA)

The Ocean Radiometer for Carbon Assessment (ORCA) is a new design for the next generation remote sensing of ocean biology and biogeochemistry. ORCA is configured to meet all the measurement requirements of the Decadal Survey Aerosol, Cloud, and Ecology (ACE), the Ocean Ecosystem (OES) radiometer and the Pro-ACE climate data continuity mission (PACE). Under the auspices of a 2007 grant from NASA Research Opportunity in Space and Earth Science (ROSES) and the Instrument Incubator Program (IIP), a team at the Goddard Space Flight Center (GSFC) has been working on a functional prototype with flight-like fore and aft optics and scan mechanisms. As part of the development efforts to bring ORCA closer to a flight configuration and in order to reduce cost, we have conducted component-level optical testing using standard spectrophotometers and system-level characterizations using non-flight commercial off-the-shelf (COTS) focal plane array detectors. Although these arrays would not be able to handle flight data rates, they are adequate for optical alignment and performance testing. The purpose of this presentation is to describe the results of this testing performed at GSFC and the National Institute of Standards and Technology (NIST) at the component and system level. Specifically, we show results for ORCA's spectral calibration ranging from the near UV, visible, and near-infrared spectral region.

Quijada, Manuel A.

ORCAS - Keck Instrument Development - ORKID

A new breed of space-ground hybrid observatory, the Orbiting Configurable Artificial Star (ORCAS) mission is working with the W. M. Keck Observatory (WMKO) to demonstrate the viability of diffraction-limited visible imaging from large ground telescopes. To support that, we have built and delivered ORKID (The ORCAS Keck Instrument Demonstrator) as an early visible-wavelength performance demonstration with the Keck II Adaptive Optics (AO) system. By enabling AO and flux calibration observations, the low-cost ORCAS/ORKID mission will deliver highly detailed images to support many scientific advances. A community driven observation plan will provide Great Observatory quality capabilities open to all US observers. These observations will result in unique science for the mission, while also complementing and extending space-borne science.

Eliad Peretz

Optical Design of Multi-field Integral Field Unit Spectrograph for the ORCAS Keck Instrument Development II (ORKID II) Instrument

We have designed an Integral Field Unit Spectrometer for the ORCAS Keck Instrument Development II (ORKID II) Instrument. Building on the success of the ORKID instrument (which achieved 15.1 masec FWHM visible spectrum imaging), ORKID II will add Integral Field Spectroscopy to analyze Active Galactic Nuclei (AGN), Supernovae redshift and brightness, and other science observations. Several design options have been explored based on image slicers manufactured by the Canon Corporation’s machining process. Field layouts can include up to three disparate spatial sampling, with a lower limit of 6.7 masec. Spectral resolutions are considered from R 100 to R 10,000. The modular design of the concept allows for configuring the instrument for various observing campaigns.

Instrumentation and Photography

Optical Design of Multi-field Integral Field Unit Spectrograph for the ORCAS Keck Instrument Development II (ORKID II) Instrument

We have designed an Integral Field Unit for the ORCAS Keck Instrument Development II (ORKID II) Instrument. Building on the success of the ORKID camera which achieved 15.2 masec PSF FWHM visible light imaging, ORKID II will add Integral Field Spectroscopy to analyze Active Galactic Nuclei (AGN), supernovae redshift and brightness, and other observations. Several design options have been explored based on image slicers manufactured by the Canon Corporation’s machining process. Field layouts can include up to three disparate spatial sampling, with a lower limit of 6.7 masec. Spectral resolutions are considered from R 100 to R 10,000.

Space Instrumentation

Views from the 6 Aircraft Campaigns: ACT-America, HIPPO, CONTRAIL, ATom, ORCAS, and ABoVE

This presentation describes the assimilation of airborne measurements of carbon dioxide (CO2) into the Goddard Earth Observing System (GEOS) general circulation model. The main goal is to construct observationally constrained fields of CO2 starting from the bottom of the atmosphere and extending through the entire vertical column. These fields can then be compared directly to retrievals of column CO2 (XCO2) from the Greenhouse Gases Observing Satellite (GOSAT) and the Orbiting Carbon Observatory 2 (OCO-2) by using the averaging kernel and a priori profile. This approach does not equire a direct satellite overpass, but rather an overpass of the much broader region impacted by the assimilation, which alleviates some of the jeopardy of coordinating flights with satellite tracks. Furthermore, checking if the story stays the same or if it changes when the unassimilated fields are compared to the satellite soundings allows us to separate model errors from retrieval errors. This work attempts to answer a number of questions including: What are the possible causes of systematic differences between model and satellite XCO2 over the Pacific Ocean? What is the contribution of tratospheric uncertainty to XCO2 errors? What is the impact of errors in boundary layer physics on modeled XCO2?

Weir, B.

ORCAS – Orbiting Configurable Artificial Star Mission Architecture

In this paper, we establish the mission operation concept for the Orbiting Configurable Artificial Star mission, a hybrid space-ground observatory, which aims to enable ground observations of near-diffraction limited resolution and exquisite sensitivity. We present the mission requirements, introduce a potential orbit solution that can meet them, detail the concrete operational steps to be taken to enable such observations, and develop a mission planning tool which generates a mission schedule that meets all mission requirements and can be altered in real time in the case of disruptions to the mission. Finally, we show the the mission could enable 300 adaptive optics and 1500 flux calibration observations throughout its lifetime.

Eliad Peretz

Oak Ridge Computing Academy: An HPC cluster deployment and management pilot

The High Performance Computing Technologies (HPCT) course is a hands-on High Performance Computing (HPC) cluster deployment and management training program offered as part of the International School for Advanced Studies (SISSA) and the International Center for Theoretical Physics (ICTP) Master in High Performance Computing (MHPC) specialization. Here, this training program introduces students to key concepts in cluster configuration. which include networking, software stack provisioning, job scheduling, and monitoring. The publicly available course materials feature several examples and underlying methods that are broadly applicable to cluster deployment and management. This paper discusses the design of a new workforce development program at the Oak Ridge National Laboratory that is based on HPCT, the Oak Ridge Computing Academy (ORCA). The ORCA pilot program was hosted by the Oak Ridge Leadership Computing Facility (OLCF) in Summer 2025. As a part of this discussion, HPCT and ORCA course contents and infrastructure are outlined, ORCA participant experiences are detailed, and potential opportunities for improvement are discussed.

Education

Data-driven global ocean modeling for seasonal to decadal prediction

Accurate modeling of ocean dynamics is crucial for enhancing our understanding of complex ocean circulation processes, predicting climate variability, and tackling challenges posed by climate change. Although great efforts have been made to improve traditional numerical models, predicting global ocean variability over multiyear scales remains challenging. Here, we propose ORCA-DL (Oceanic Reliable foreCAst via Deep Learning), a data-driven three-dimensional ocean model for seasonal to decadal prediction of global ocean dynamics. ORCA-DL accurately simulates the three-dimensional structure of global ocean dynamics with high physical consistency and outperforms state-of-the-art numerical models in capturing extreme events, including El Niño–Southern Oscillation and upper ocean heat waves. Moreover, ORCA-DL stably emulates ocean dynamics at decadal timescales, demonstrating its potential even for skillful decadal predictions and climate projections. Our results demonstrate the high potential of data-driven models for providing efficient and accurate global ocean modeling and prediction.

Science & Technology - Other Topics

FORCE Update 2024

The Framework for Optimization of Resources and Economics (FORCE) tool suite is the U.S. Department of Energy’s Nuclear Integrated Energy Systems (IES) Program flagship tool suite for technoeconomic IES analysis of IES. This tool suite is useful for analysis designed to evaluate and improve the technoeconomics of energy production systems, particularly for systems including nuclear technology. In this report, we document the development activity for the FORCE tool suite to extend its capabilities as performed during fiscal year 2024. In addition to reliability and accessibility, capability is one of the three standards guiding the development of the FORCE tool suite and the software codes that are its constituent parts. Extending the capabilities of the FORCE tool suite allows analysis both within the IES program as well as industry, university, and laboratory partners to perform analysis with more accuracy, insight, and impactful narrative. Four areas of capability development were the focus of activity this year: economic parameter uncertainty quantification, multiresolution analysis, components-to-optimization workflow automation, and statespace construction workflows for real-time optimal control. In economic parameter uncertainty quantification, the ability of HERON to capture risk due to scenarios (weather and energy demand uncertainty) was expanded to also include uncertainties in financial parameters such as capital cost or operation and maintenance costs. By including these sources of uncertainty, which are sometimes very large compared with scenario uncertainty, HERON is better able to capture the risk posed by investment in various IES technology. Because of this, analysts can also consider the reduction in risks that can be realized by choice of some technologies. In multiresolution analysis, development activity extended on work completed previously. In fiscal year 2023, methods for decomposing time series signals, such as demand, solar and wind availability, and price profiles, were analyzed and down-selected to those most effective at splitting signals into different resolutions. These resolutions allow considering the influence of different energy demand and supply behaviors across different time scales. For example, energy demand might be divided into seasonal, weekly, and hourly profiles. In fiscal year 2024, this preliminary work was extended and implemented within the Risk Analysis Virtual Environment (RAVEN) risk and uncertainty analysis platform, which is used throughout the FORCE framework. This development of the “multi-resolution time series analysis” (MR-TSA) module in RAVEN allows training synthetic history generators on complex time series. These synthetic history generators can then be used in HERON for generating scenarios that represent possible market and weather scenarios that can be analyzed on different time scales. We envision completing this work in the future, implementing multiresolution dispatch optimization strategies that can make the most beneficial use of these stratified time histories. In components-to-optimization workflow development, workflows for translating user inputs of components into algorithms for algebraic optimization were selected and implemented. Similar algorithms within the Holistic Energy Resource Optimization Network (HERON) were separated from the main code base of HERON and gathered with the components-to-optimization workflows in the new Dispatch Optimization Variable Engine (DOVE) software library. This modularization allows FORCE users to analyze dispatch optimization and energy system duty cycles independently of HERON, which previously was a burdensome task. Additionally, these dispatch optimization algorithms, set up in an independent library, can now be used across all software applications within FORCE, especially including the real-time optimal control software Optimization of Real-time Capacity Allocation (ORCA). Allowing FORCE software to share dispatch optimization algorithms within a single library allows for improved software maintenance and reliability. In statespace characterization workflow development, alternative workflows for optimizing dispatch with additional technical accuracy was the focus, particularly to improve the real-time optimization decision making in ORCA. Using algorithms and workflows initially developed for the Feasible Actuator Range Modifier (FARM), workflows for determining the statespace representation of IES were identified and demonstrated. The resulting dispatch optimization required a more robust optimization algorithm than that originally used in HERON (and moved to DOVE), which required adding an alternate workflow to DOVE that can more accurately match the behavior of physical systems using a partial differential equation representation. In conclusion, capability developments in the FORCE tool suite in fiscal year 2024 have improved the ability of the FORCE tool suite to perform

29 ENERGY PLANNING, POLICY, AND ECONOMY

Giant Dipole Moments: Remarkable Effects Mono‐, Di‐, and Tri‐ Hydrated 5,6‐Diaminobenzene‐1,2,3,4‐Tetracarbonnitrile

The molecule 5,6-diaminobenzene-1,2,3,4-tetracarbonnitrile (MOI) was first synthesized by Müllen and coworkers in 2016 and boasts an ultrastrong dipole moment of $14.1\pm 0.7$ Debye in THF. Gas phase DFT computations do not fully reflect this ultrastrong dipole moment, demonstrating the role of solvent in increasing this dipole moment. Here, we investigate the effect of solvent molecule position on the dipole moment of this species, computationally examining systems with giant dipole moments. These systems are optimized in the gas phase with the B3LYP functional, employing the aug-cc-pVTZ and def2-TZVP basis sets, as well as the B3LYP-D3BJ/aug-cc-pVTZ functional in Orca. Single point DLPNO-CCSD/aug-cc-pVDZ results were obtained from Orca and Psi4, as well as DLPNO-CCSD(T)/CBS information from Psi4. Additionally, these are compared to the dipole moments of di- and tri-hydrated systems, and the SMD models for THF and water at the B3LYP/aug-cc-pVTZ level of theory. The dissociation energies, HOMO-LUMO energy gaps, and dipole moments are presented. These metrics show the nh1nh1′ THF system boasts the largest dissociation energy and dipole moment of the singly solvated systems, due to its strong hydrogen bonding. The importance of solvent placement is highlighted and may guide the synthesis of macromolecules or organic frameworks incorporating the MOI or MOI-like subunits. Remarkably, a single solvent molecule provides a good model for the difference between the gas phase and solvated species. The predicted gas phase dipole moments computed with B3LYP/aug-cc-pVTZ for the MOI, its monohydrated complex, dihydrated complex, and its trihydrated complex are 9.6, 14.2, 16.0, and 16.8 Debye, respectively.

dipole

Remote Sensing of Ocean Color in the Arctic: Algorithm Development and Comparative Validation

The overall goal of this effort is to acquire a large bio-optical database, encompassing most environmental variability in the Arctic, to develop algorithms for phytoplankton biomass and production and other optically active constituents. A large suite of bio-optical and biogeochemical observations have been collected in a variety of high latitude ecosystems at different seasons. The Ocean Research Consortium of the Arctic (ORCA) is a collaborative effort between G.F. Cota of Old Dominion University (ODU), W.G. Harrison and T. Platt of the Bedford Institute of Oceanography (BIO), S. Sathyendranath of Dalhousie University and S. Saitoh of Hokkaido University. ORCA has now conducted 12 cruises and collected over 500 in-water optical profiles plus a variety of ancillary data. Observational suites typically include apparent optical properties (AOPs), inherent optical property (IOPs), and a variety of ancillary observations including sun photometry, biogeochemical profiles, and productivity measurements. All quality-assured data have been submitted to NASA's SeaWIFS Bio-Optical Archive and Storage System (SeaBASS) data archive. Our algorithm development efforts address most of the potential bio-optical data products for the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS), and GLI, and provides validation for a specific areas of concern, i.e., high latitudes and coastal waters.

Cota, Glenn F.

International Space Station (ISS) Oxygen High Pressure Storage Management

High pressure oxygen onboard the ISS provides support for Extra Vehicular Activities (EVA) and contingency metabolic support for the crew. This high pressure 02 is brought to the ISS by the Space Shuttle and is transferred using the Oxygen Recharge Compressor Assembly (ORCA). There are several drivers that must be considered in managing the available high pressure 02 on the ISS. The amount of O2 the Shuttle can fly up is driven by manifest mass limitations, launch slips, and on orbit Shuttle power requirements. The amount of 02 that is used from the ISS high pressure gas tanks (HPGT) is driven by the number of Shuttle docked and undocked EVAs, the type of EVA prebreath protocol that is used and contingency use of O2 for metabolic support. Also, the use of the ORCA must be managed to optimize its life on orbit and assure that it will be available to transfer the planned amount of O2 from the Shuttle. Management of this resource has required long range planning and coordination between Shuttle manifest on orbit plans. To further optimize the situation hardware options have been pursued.

Lewis, John R.

Orbiting Artificial Star for High-Resolution Coronal Imaging from the Ground

This paper establishes the scientific motivation of the Orbiting Artificial Star for High-resolution Coronal Imaging from the Ground (ORCAS-Helio), and presents the Preliminary Science Traceability Matrix (STM), defining the scientific objectives, the expected significance, and the impact of the mission. Furthermore, the paper describes the payload, mission configuration, and spacecraft architecture and shows it could meet its scientific and engineering requirements. By doing so, a viable mission configuration for the ORCAS-Helio mission is established.

Eliad Peretz

Combined Bernstein Polynomial, Optimal Reciprocal Collision Avoidance, Differential Dynamic Programming for Trajectory Replanning and Collision Avoidance for UAM Vehicles

This paper presents an integration of Differential Dynamic Programming (DDP) with the Optimal Reciprocal Collision Avoidance (ORCA) algorithm as the basis for a new algorithm, titled Combined Bernstein Polynomial Optimal Reciprocal Collision Avoidance DDP (COBRA-DDP), for trajectory replanning and collision avoidance for Urban Air Mobility (UAM) vehicles. State-constrained variants of DDP provide the ability to plan trajectories while avoiding obstacles, but these methods require a large increase in computational time per iteration which hinders the overall speed of the algorithm. ORCA utilizes simplified dynamics to recognize potential collisions along a trajectory and provides an optimal velocity for the avoidance of multiple vehicles. These velocity commands, however, may not result in a dynamically feasible trajectory for DDP to plan around. As such, a Bernstein polynomial curve that considers the general dynamic constraints of the vehicle is generated to approximate a trajectory based on the velocity commands. COBRA-DDP optimizes this suggested trajectory via unconstrained DDP to provide a dynamically feasible trajectory that provides collision avoidance. This new trajectory can be applied to the vehicle or used to warm start the state constrained DDP algorithms to decrease computation time. Its benefits and effectiveness of the algorithm are demonstrated on a UAM Vertical Takeoff and Landing (VTOL) vehicle simulation with highly nonlinear dynamics.

Optimal Reciprocal Collision Avoidance

Fragme∩t: An Open‐Source Framework for Multiscale Quantum Chemistry Based on Fragmentation

Fragment-based quantum chemistry offers a means to circumvent the nonlinear computational scaling of conventional electronic structure calculations, by partitioning a large calculation into smaller subsystems then considering the many-body interactions between them. Variants of this approach have been used to parameterize classical force fields and machine learning potentials, applications that benefit from interoperability between quantum chemistry codes. However, there is a dearth of software that provides interoperability yet is purpose-built to handle the combinatorial complexity of fragment-based calculations. To fill this void we introduce “Fragme∩t”, an open-source software application that provides a tool for community validation of fragment-based methods, a platform for developing new approximations, and a framework for analyzing many-body interactions. Fragme∩t includes algorithms for automatic fragment generation and structure modification, and for distance- and energy-based screening of the requisite subsystems. Checkpointing, database management, and parallelization are handled internally and results are archived in a portable database. Interfaces to various quantum chemistry engines are easy to write and exist already for Q-Chem, PySCF, xTB, Orca, CP2K, MRCC, Psi4, NWChem, GAMESS, and MOPAC. Applications reported here demonstrate parallel efficiencies around 96% on more than 1000 processors but also showcase that the code can handle large-scale protein fragmentation using only workstation hardware, all with a codebase that is designed to be usable by non-experts. Fragme∩t conforms to modern software engineering best practices and is built upon well established technologies including Python, SQLite, and Ray. The source code is available under the Apache 2.0 license.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Accurate and efficient open-source implementation of domain-based local pair natural orbital (DLPNO) coupled-cluster theory using a t1-transformed Hamiltonian

We present an efficient, open-source formulation for coupled-cluster theory through perturbative triples with domain-based local pair natural orbitals [DLPNO-CCSD(T)]. Similar to the implementation of the DLPNO-CCSD(T) method found in the ORCA package, the most expensive integral generation and contraction steps associated with the CCSD(T) method are linear-scaling. In this work, we show that the t1-transformed Hamiltonian allows for a less complex algorithm when evaluating the local CCSD(T) energy without compromising efficiency or accuracy. Our algorithm yields sub-kJ mol−1 deviations for relative energies when compared with canonical CCSD(T), with typical errors being on the order of 0.1 kcal mol−1, using our TightPNO parameters. We extensively tested and optimized our algorithm and parameters for non-covalent interactions, which have been the most difficult interaction to model for orbital (PNO)-based methods historically. To highlight the capabilities of our code, we tested it on large water clusters, as well as insulin (787 atoms).

Chemistry

Extending the dark matter reach of water Cherenkov detectors using Jupiter

We propose the first method for water Cherenkov detectors to constrain GeV-scale dark matter (DM) below the solar evaporation mass. While previous efforts have highlighted the Sun and Earth as DM capture targets, we demonstrate that Jupiter is a viable target. Jupiter’s unique characteristics, such as its lower core temperature and significant gravitational potential, allow it to capture and retain light DM more effectively than the Sun, particularly in the mass range below 4 GeV where direct detection sensitivity diminishes. Our calculations provide the first sensitivity estimates to GeV-scale annihilating DM within Jupiter, predicting Hyper-K can reach spin dependent cross sections as low as $𝜎^{SD}_{𝑝⁢𝜒}$ = 2×10 −35 cm 2 for DM masses below 2 GeV. This surpasses current solar limits and direct detection results. We additionally provide estimates for Super-K ORCA, and the IceCube-Upgrade, showing that these experiments could provide complimentary bounds to direct detection experiments.

79 ASTRONOMY AND ASTROPHYSICS

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