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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Three Orbital Burns to Molniya Orbit via Shuttle Centaur G Upper Stage

An unclassified analytical trajectory design, performance, and mission study was done for the 1982-86 joint NASA-USAF Shuttle/Centaur G upper stage development program to send performance-demanding payloads to high orbits such as Molniya using an unconventional orbit transfer. This optimized three orbital burn transfer to Molniya orbit was compared to the then-baselined two burn transfer. The results of the three dimensional trajectory optimization performed include powered phase steering data and coast phase orbital element data. Time derivatives of the orbital elements as functions of thrust components were evaluated and used to explain the optimization's solution. Vehicle performance as a function of parking orbit inclination was given. Performance and orbital element data was provided for launch windows as functions of launch time. Ground track data was given for all burns and coasts including variation within the launch window. It was found that a Centaur with fully loaded propellant tanks could be flown from a 37deg inclination low Earth parking orbit and achieve Molniya orbit with comparable performance to the baselined transfer which started from a 57deg inclined orbit: 9,545 lb vs. 9,552 lb of separated spacecraft weight respectively. There was a significant reduction in the need for propellant launch time reserve for a one hour window: only 78 lb for the three burn transfer vs. 320 lb for the two burn transfer. Conversely, this also meant that longer launch windows over more orbital revolutions could be done for the same amount of propellant reserve. There was no practical difference in ground tracking station or airborne assets needed to secure telemetric data, even though the geometric locations of the burns varied considerably. There was a significant adverse increase in total mission elapsed time for the three vs. two burn transfer (12 vs. 11/4 hrs), but could be accommodated by modest modifications to Centaur systems. Future applications were discussed. The three burn transfer was found to be a viable, arguably preferable, alternative to the two burn transfer.

Orbital trajectory design↗
NASA NTRS2015

Three Orbital Burns to Molniya Orbit Via Shuttle_Centaur G Upper Stage

An unclassified analytical trajectory design, performance, and mission study was done for the 1982 to 1986 joint National Aeronautics and Space Administration (NASA)-United States Air Force (USAF) Shuttle/Centaur G upper stage development program to send performance-demanding payloads to high orbits such as Molniya using an unconventional orbit transfer. This optimized three orbital burn transfer to Molniya orbit was compared to the then-baselined two burn transfer. The results of the three dimensional trajectory optimization performed include powered phase steering data and coast phase orbital element data. Time derivatives of the orbital elements as functions of thrust components were evaluated and used to explain the optimization's solution. Vehicle performance as a function of parking orbit inclination was given. Performance and orbital element data was provided for launch windows as functions of launch time. Ground track data was given for all burns and coasts including variation within the launch window. It was found that a Centaur with fully loaded propellant tanks could be flown from a 37 deg inclination low Earth parking orbit and achieve Molniya orbit with comparable performance to the baselined transfer which started from a 57 deg inclined orbit: 9,545 versus 9,552 lb of separated spacecraft weight, respectively. There was a significant reduction in the need for propellant launch time reserve for a 1 hr window: only 78 lb for the three burn transfer versus 320 lb for the two burn transfer. Conversely, this also meant that longer launch windows over more orbital revolutions could be done for the same amount of propellant reserve. There was no practical difference in ground tracking station or airborne assets needed to secure telemetric data, even though the geometric locations of the burns varied considerably. There was a significant adverse increase in total mission elapsed time for the three versus two burn transfer (12 vs. 1-1/4 hr), but could be accommodated by modest modifications to Centaur systems. Future applications were discussed. The three burn transfer was found to be a viable, arguably preferable, alternative to the two burn transfer.

Orbital trajectory design↗
NASA NTRS2015

Design Evolution of the Wide Field Infrared Survey Telescope using Astrophysics Focused Telescope Assets (WFIRST-AFTA) and Lessons Learned

The design of the Wide Field Infrared Survey Telescope using Astrophysics Focused Telescope Assets (WFIRST-AFTA) continues to evolve as each design cycle is analyzed. In 2012, two Hubble sized (2.4 m diameter) telescopes were donated to NASA from elsewhere in the Federal Government. NASA began investigating potential uses for these telescopes and identified WFIRST as a mission to benefit from these assets. With an updated, deeper, and sharper field of view than previous design iterations with a smaller telescope, the optical designs of the WFIRST instruments were updated and the mechanical and thermal designs evolved around the new optical layout. Beginning with Design Cycle 3, significant analysis efforts yielded a design and model that could be evaluated for Structural-Thermal-Optical-Performance (STOP) purposes for the Wide Field Imager (WFI) and provided the basis for evaluating the high level observatory requirements. Development of the Cycle 3 thermal model provided some valuable analysis lessons learned and established best practices for future design cycles. However, the Cycle 3 design did include some major liens and evolving requirements which were addressed in the Cycle 4 Design. Some of the design changes are driven by requirements changes, while others are optimizations or solutions to liens from previous cycles. Again in Cycle 4, STOP analysis was performed and further insights into the overall design were gained leading to the Cycle 5 design effort currently underway. This paper seeks to capture the thermal design evolution, with focus on major design drivers, key decisions and their rationale, and lessons learned as the design evolved.

Thermal Design↗
NASA NTRS2015

Design Evolution of the Wide Field Infrared Survey Telescope Using Astrophysics Focused Telescope Assets (WFIRST-AFTA) and Lessons Learned

The design of the Wide Field Infrared Survey Telescope using Astrophysics Focused Telescope Assets (WFIRST-AFTA) continues to evolve as each design cycle is analyzed. In 2012, two Hubble sized (2.4 m diameter) telescopes were donated to NASA from elsewhere in the Federal Government. NASA began investigating potential uses for these telescopes and identified WFIRST as a mission to benefit from these assets. With an updated, deeper, and sharper field of view than previous design iterations with a smaller telescope, the optical designs of the WFIRST instruments were updated and the mechanical and thermal designs evolved around the new optical layout. Beginning with Design Cycle 3, significant analysis efforts yielded a design and model that could be evaluated for Structural-Thermal-Optical-Performance (STOP) purposes for the Wide Field Imager (WFI) and provided the basis for evaluating the high level observatory requirements. Development of the Cycle 3 thermal model provided some valuable analysis lessons learned and established best practices for future design cycles. However, the Cycle 3 design did include some major liens and evolving requirements which were addressed in the Cycle 4 Design. Some of the design changes are driven by requirements changes, while others are optimizations or solutions to liens from previous cycles. Again in Cycle 4, STOP analysis was performed and further insights into the overall design were gained leading to the Cycle 5 design effort currently underway. This paper seeks to capture the thermal design evolution, with focus on major design drivers, key decisions and their rationale, and lessons learned as the design evolved.

WFIRST↗
NASA NTRS2014

Small Spacecraft System-Level Design and Optimization for Interplanetary Trajectories

The feasibility of an interplanetary mission for a CubeSat, a type of miniaturized spacecraft, that uses an emerging technology, the CubeSat Ambipolar Thruster (CAT) is investigated. CAT is a large delta-V propulsion system that uses a high-density plasma source that has been miniaturized for small spacecraft applications. An initial feasibility assessment that demonstrated escaping Low Earth Orbit (LEO) and achieving Earth-escape trajectories with a 3U CubeSat and this thruster technology was demonstrated in previous work. We examine a mission architecture with a trajectory that begins in Earth orbits such as LEO and Geostationary Earth Orbit (GEO) which escapes Earth orbit and travels to Mars, Jupiter, or Saturn. The goal was to minimize travel time to reach the destinations and considering trade-offs between spacecraft dry mass, fuel mass, and solar power array size. Sensitivities to spacecraft dry mass and available power are considered. CubeSats are extremely size, mass, and power constrained, and their subsystems are tightly coupled, limiting their performance potential. System-level modeling, simulation, and optimization approaches are necessary to find feasible and optimal operational solutions to ensure system-level interactions are modeled. Thus, propulsion, power/energy, attitude, and orbit transfer models are integrated to enable systems-level analysis and trades. The CAT technology broadens the possible missions achievable with small satellites. In particular, this technology enables more sophisticated maneuvers by small spacecraft such as polar orbit insertion from an equatorial orbit, LEO to GEO transfers, Earth-escape trajectories, and transfers to other interplanetary bodies. This work lays the groundwork for upcoming CubeSat launch opportunities and supports future development of interplanetary and constellation CubeSat and small satellite mission concepts.

Spangelo, Sara↗
NASA NTRS2013

Woven TPS Enabling Missions Beyond Heritage Carbon Phenolic

WTPS is a new approach to producing TPS architectures that uses precisely engineered 3D weaving techniques to customize material characteristics needed to meet specific missions requirements for protecting space vehicles from the intense heating generated during atmospheric entry. Using WTPS, sustainable, scalable, mission-optimized TPS solutions can be achieved with relatively low life cycle costs compared with the high costs and long development schedules currently associated with material development and certification. WTPS leverages the mature state-of-the-art weaving technology that has evolved from the textile industry to design TPS materials with tailorable performance. Currently, missions anticipated encountering heat fluxes in the range of 1500 4000 Wcm2 and pressures greater than 1.5 atm are limited to using fully dense Carbon Phenolic. However, fully dense carbon phenolic is only mass efficient at higher heat fluxes greater than 4000 Wcm2), and current mission designs suffer this mass inefficiency for lack of an alternative mid-density TPS. WTPS not only bridges this mid-density TPS gap but also offers a replacement for carbon phenolic, which itself requires a significant and costly redevelopment effort to re-establish its capability for use in the high heat flux missions recently prioritized in the NRC Decadal survey, including probe missions to Venus, Saturn and Neptune. This presentation will overview the WTPS concept and present some results from initial testing completed comparing WTPS architectures to heritage carbon phenolic.

ablators↗
NASA NTRS2014

Diagnosability-Based Sensor Placement through Structural Model Decomposition

Systems health management, and in particular fault diagnosis, is important for ensuring safe, correct, and efficient operation of complex engineering systems. The performance of an online health monitoring system depends critically on the available sensors of the system. However, the set of selected sensors is subject to many constraints, such as cost and weight, and hence, these sensors must be selected judiciously. This paper presents an offline design-time sensor placement approach for complex systems. Our diagnosis method is built upon the analysis of model-based residuals, which are computed using structural model decomposition. Sensor placement in this framework manifests as a residual selection problem, and we aim to find the set of residuals that achieves single-fault diagnosability of the system, uses the minimum number of sensors, and corresponds to the best model decomposition for the best distribution of the diagnosis system. We present a set of algorithms for solving this problem and compare their performance in terms of computational complexity and optimality of solutions. We demonstrate the approach using a benchmark multi-tank system.

Daigle, Matthew↗
NASA NTRS2017

TPSAS-NF1676L-28149-DND

An Optimal Estimation (OE) inversion method has been developed to retrieve vertical profiles of aerosol size distributions, volume/surface concentrations, complex refractive indices, and single scattering albedos using the High Spectral Resolution Lidar (HSRL) and polarimeter measurements. By combining the active and passive remote sensing data, we can take advantages of the high vertical resolution of the lidar measurements and the high information content of the combined observations. There are three components to the new retrieval system: 1) simultaneous aerosol vertical profile retrieval using HSRL data, 2) standalone aerosol retrieval using Research Scanning Polarimeter (RSP), and 3) combined HSRL and RSP optimal estimation retrieval. For the LIDAR retrieval, we solve for number concentrations, mode fractions, aerosol size distributions, and real and imaginary part of refractive indices simultaneously. Based on this information, other parameters such as effective particle radius, surface and volume concentration, single scattering albedo can be derived. The combined HSRL-polarimeter algorithm will provide improved single scattering albedo and refractive index retrievals. The newly developed retrieval algorithm is very fast, and it provides an optimal estimation solution with associated error estimates. By solving for the aerosol vertical profiles using HSRL extinctions and backscattering coefficients from different layers, the new OE method can effectively reduce the impact of measurement noise on the retrieved aerosol microphysical properties. It also enables us to effectively combing HSRL and RSP data in the single OE retrieval system since the passive polarimeter instruments measure path-integrated intensity and polarizations. We have performed sensitivity studies using simulated data and applied the OE algorithms to NASA airborne field data measured by the HSRL-2 and the RSP instruments.

Xu Liu↗
NASA NTRSDate not supplied

Gust Load Alleviation Control and Gust Estimation for a High Aspect Ratio Wing Wind Tunnel Model

This paper presents the gust load alleviation (GLA) study of the aspect ratio 13.5 Common Research Model (CRM) wind-tunnel model. This study details the design of the GLA controller in preparation for wind-tunnel testing in the Transonic Dynamics Tunnel at NASA Langley Research Center. An aeroservolastic (ASE) model is first reduced using a model reduction method that takes advantage of the sinusoidal steady-state response. Then, the reduced model is used to design an extended-state Kalman filter which estimates the states and the sinusoidal gust input. The GLA control is then derived using the optimal control solution to a multi-objective cost function. The results of the GLA controller indicate a 69.07% reduction in wing-root strain without sensor noise and 68.45% reduction with sensor noise, while maintaining robust stability margins. An adaptive GLA controller is developed for uncertain gust frequency and shows a 71.03% reduction in wing root strain compared to the non-adaptive control reduction of just 39.19%.

Christopher Forte↗
DOE OSTI2024

Data Analytics and Visualization of Energy Systems for Critical Infrastructure Insights

Modernization of energy systems including transportation facilities provides opportunities for increased efficiency, expansion of commerce and meeting industry and federal goals. A significant increase in electrical demand is projected to meet these needs, which concentrates at facilities such as airports. For example, Xcel Energy working with two airports in their service area recently published information projecting an up to fivefold increase in electricity demand in the next 25 years [1]. Concurrently, the US Government Accountability Office (GAO) recently surveyed 30 commercial service airports identifying more than 300 outages of more than 5 minutes between 2015 and 2022 [2]. Power, reliability, and resilience planning becomes more important to safely maintain operations and the flow of commerce with fewer energy carriers providing necessary energy to safely move passengers and goods. NREL proposes to develop methodologies to allow owners, utilities, and federal agencies to dynamically analyze, forecast, and manage energy loads at airports, focused upon maintaining the flow of commerce in an efficient, sustainable, and resilient way. To address these energy challenges, a suite of technologies and methodologies can be leveraged to validate concepts, inform design, de-risk solutions and optimize energy management during deployment. These technologies include digitalization of energy systems, microgrid methodologies, and related energy technologies for building and vehicle loads. [1] Electrifying Airport Ecosystems - https://www.enterprisemobility.com/content/dam/enterpriseholdings/marketing/innovation-in-mobility/vehicle-innovation/airport-electrification-study-full-report-2024.pdf [2] Airport Infrastructure: Selected Airport's Efforts to Enhance Electrical Resilience https://www.gao.gov/products/gao-23-105203.

critcal infrastructure↗
DOE OSTI2026

BEAM CORE: A Flexible Ecosystem for Freight, Demographics, and Vehicle Analysis

The Behavior, Energy, Autonomy, and Mobility Comprehensive Regional Evaluator (BEAM CORE) is an open-source, modular ecosystem of highly refined, agent-based modeling tools developed by Lawrence Berkeley National Laboratory and the National Laboratory of the Rockies. Organizations such as metropolitan planning organizations, agencies, and companies can use BEAM CORE to analyze freight movement and optimize logistics solutions, assess the impacts of emerging freight technologies or e-commerce trends, model dynamic population growth and evolution, and understand the drivers and impacts of electric vehicle adoption across households in a given region. Users can choose from a flexible suite of modeling modules according to their needs and priorities. The modules integrate with travel demand models to support enhanced analysis of diverse scenarios involving freight movement, vehicle technologies, and other key factors relevant to regional planning.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Distributed quantum approximate optimization algorithm on a quantum-centric supercomputing architecture

Quantum approximate optimization algorithm (QAOA) has shown promise in solving combinatorial optimization problems by providing quantum speedup on near-term gate-based quantum computing systems. However, QAOA faces challenges for high-dimensional problems due to the large number of qubits required and the complexity of deep circuits, limiting its scalability for real-world applications. In this study, we present a distributed QAOA (DQAOA), which leverages distributed computing strategies to decompose a large computational workload into smaller tasks that require fewer qubits and shallower circuits than are necessary to solve the original problem. These sub-problems are processed using a combination of high-performance and quantum computing resources. The global solution is iteratively updated by aggregating sub-solutions, allowing convergence toward the optimal solution. We demonstrate that DQAOA can handle considerably large-scale optimization problems (e.g., 1000-bit problem), achieving a high solution quality and short time-to-solution, outperforming existing strategies. Furthermore, we realize DQAOA on a quantum-centric supercomputing architecture, paving the way for practical applications of gate-based quantum computers in real-world optimization tasks. To extend DQAOA’s applicability to materials science, we further develop an active learning algorithm integrated with our DQAOA (AL-DQAOA), which involves machine learning, DQAOA, and active data production in an iterative loop. We successfully optimize photonic structures using AL-DQAOA, indicating that solving real-world optimization problems using gate-based quantum computing is feasible. We expect the proposed DQAOA to be applicable to a wide range of optimization problems and AL-DQAOA to find broader applications in material design.

Kim, Seongmin [ORNL] (ORCID:0000000159063004)↗
NASA NTRS1975

Techniques for trajectory optimization using a hybrid computer

The use of a hybrid computer in the solution of trajectory optimization problems is described. The solution technique utilizes the indirect method and requires iterative computation of the initial condition vector of the co-state variables. Convergence of the iteration is assisted by feedback switching and contour modification. A simulation of the method in an on-line updating scheme is presented.

Neely, P. L.↗
NASA NTRS1992

On the optimal two-impulse maneuver

An algorithm and a solution to the optimal two-impulse maneuver for the Ulysses spacecraft is presented. The option in which both maneuvers are designed using the critical plane strategy, which further reduces the propellant budget, is included. Results show savings of 12.4 and 16.7 m/s for full targeting and critical plane strategy, respectively. It is argued that this software will play an important role in the area of multimission maneuver design.

Bonneau, F. G.↗
NASA NTRS1995

Aerodynamic design optimization via reduced Hessian SQP with solution refining

An all-at-once reduced Hessian Successive Quadratic Programming (SQP) scheme has been shown to be efficient for solving aerodynamic design optimization problems with a moderate number of design variables. This paper extends this scheme to allow solution refining. In particular, we introduce a reduced Hessian refining technique that is critical for making a smooth transition of the Hessian information from coarse grids to fine grids. Test results on a nozzle design using quasi-one-dimensional Euler equations show that through solution refining the efficiency and the robustness of the all-at-once reduced Hessian SQP scheme are significantly improved.

Feng, Dan↗
NASA NTRS1995

Aerodynamic design optimization via reduced Hessian SQP with solution refining

An all-at-once reduced Hessian Successive Quadratic Programming (SQP) scheme has been shown to be efficient for solving aerodynamic design optimization problems with a moderate number of design variables. This paper extends this scheme to allow solution refining. In particular, we introduce a reduced Hessian refining technique that is critical for making a smooth transition of the Hessian information from coarse grids to fine grids. Test results on a nozzle design using quasi-one-dimensional Euler equations show that through solution refining the efficiency and the robustness of the all-at-once reduced Hessian SQP scheme are significantly improved.

Feng, Dan↗
DOE OSTI2024

Gains in operational flexibility, safety margins, and cost efficiencies via integrated Plant Reload Optimization platform

The U.S. Department of Energy Light Water Reactor Sustainability Program Risk-Informed Systems Analysis Pathway Plant Reload Optimization Project aims to develop an integrated, comprehensive framework offering an all-in-one solution for reload evaluations with a special focus on optimizing core design. Optimizing the fuel loading pattern is one of the most important considerations in reducing the amount of new fuel used in the core. Due to thousands of possible core configuration options, finding optimal solutions is an unachievable task for a human. The Plant ReLoad Optimization platform, which supports artificial-intelligence-based reactor core designing, is now fully capable of handling realistic problems. The Plant ReLoad Optimization platform development project aims to build a reactor core design tool that includes reactor safety and fuel performance analyses and uses artificial intelligence to support the optimization of core design solutions. The NSGA-II (Non-dominated Sorting Genetic Algorithm II) optimizer was developed and tested within RAVEN (Risk Analysis and Virtual ENvironment) to handle many constraints by using an augmented objectives methodology. The demonstration was performed with constrained multiobjective optimization of a 17 × 17 pressurized-water reactor core loading patterns to minimize fuel cost and maximize fuel cycle length.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗