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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

Shuttle program. MCC Level C formulation requirements: Entry guidance and entry autopilot

A set of preliminary entry guidance and autopilot software formulations is presented for use in the Mission Control Center (MCC) entry processor. These software formulations meet all level B requirements. Revision 2 incorporates the modifications required to functionally simulate optimal TAEM targeting capability (OTT). Implementation of this logic in the MCC must be coordinated with flight software OTT implementation and MCC TAEM guidance OTT. The entry guidance logic is based on the Orbiter avionics entry guidance software. This MCC requirements document contains a definition of coordinate systems, a list of parameter definitions for the software formulations, a description of the entry guidance detailed formulation requirements, a description of the detailed autopilot formulation requirements, a description of the targeting routine, and a set of formulation flow charts.

Harpold, J. C.↗
NASA NTRS1989

Optimum data weighting and error calibration for estimation of gravitational parameters

A new technique was developed for the weighting of data from satellite tracking systems in order to obtain an optimum least-squares solution and an error calibration for the solution parameters. Data sets from optical, electronic, and laser systems on 17 satellites in GEM-T1 Goddard Earth Model-T1 (GEM-T1) were employed toward application of this technique for gravity field parameters. Also GEM-T2 (31 satellites) was recently computed as a direct application of the method and is summarized. The method employs subset solutions of the data associated with the complete solution to agree with their error estimates. With the adjusted weights the process provides for an automatic calibration of the error estimates for the solution parameters. The data weights derived are generally much smaller than corresponding weights obtained from nominal values of observation accuracy or residuals. Independent tests show significant improvement for solutions with optimal weighting. The technique is general and may be applied to orbit parameters, station coordinates, or other parameters than the gravity model.

Lerch, Francis J.↗
NASA NTRS1999

New Approaches to HSCT Multidisciplinary Design and Optimization

New approaches to MDO have been developed and demonstrated during this project on a particularly challenging aeronautics problem- HSCT Aeroelastic Wing Design. To tackle this problem required the integration of resources and collaboration from three Georgia Tech laboratories: ASDL, SDL, and PPRL, along with close coordination and participation from industry. Its success can also be contributed to the close interaction and involvement of fellows from the NASA Multidisciplinary Analysis and Optimization (MAO) program, which was going on in parallel, and provided additional resources to work the very complex, multidisciplinary problem, along with the methods being developed. The development of the Integrated Design Engineering Simulator (IDES) and its initial demonstration is a necessary first step in transitioning the methods and tools developed to larger industrial sized problems of interest. It also provides a framework for the implementation and demonstration of the methodology. Attachment: Appendix A - List of publications. Appendix B - Year 1 report. Appendix C - Year 2 report. Appendix D - Year 3 report. Appendix E - accompanying CDROM.

Schrage, Daniel P.↗
DOE OSTI2026

Optimizing Transportation Networks for E-Waste Reverse Logistics: A Multi-Modal Cost Allocation and Pricing Strategy

The exponential growth of electronic waste (e-waste) poses critical challenges for sustainable reverse logistics and transportation network optimization. This study develops a dual-channel transportation framework for e-waste logistics that integrates dynamic freight pricing, cost allocation mechanisms, and game-theoretic coordination. The model captures interactions between centralized hubs and distributed processing networks, accounting for freight rate elasticity, volume allocation, and capacity constraints. Using Stackelberg game theory and cost-sharing strategies, the framework optimizes transportation efficiency and profit distribution across logistics channels. Numerical simulations show that the dual-channel structure increases centralized hub profit by 226.8% compared to baseline single-channel operations, while boosting total transported volume by 1.2% and nearly doubling freight collector profit under cost-sharing. Scenario analyses across regional infrastructures reveal that network density, policy incentives, and logistics costs shape routing efficiency and profit allocation. These findings suggest that coordinated strategies combining dynamic pricing, targeted infrastructure investment, and strategic cost allocation are needed to design efficient, resilient, and regionally adaptable e-waste transportation systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Machine Learning-Based PV Reserve Determination Strategy for Frequency Control on the WECC System

Frequency control from photovoltaic (PV) power plants has great potential to address the frequency response challenge of the power system with high penetrations of renewable generation. Using model-based approaches to determine the optimal PV headroom reserve, however, requires significant online computation and is intractable for an interconnection level system. This paper proposes a machine learning based strategy, that is suitable for real-time operation, to determine the optimal PV reserve for frequency control. The proposed machine learning algorithm is trained and tested on 1,987 offline simulations of a 60% renewable penetration Western Electricity Coordinating Council (WECC) system. Furthermore, the proposed reserve determination strategy is applied on a realistic 1-day operation profile of the WECC system and demonstrates a savings of more than 40% PV headroom compared to a conservative approach. It is evident that the proposed strategy can efficiently and effectively determine the optimal PV frequency control reserve for realistic interconnection systems.

frequency control↗
DOE OSTI2023

Tuning Structural and Electronic Configuration of FeN 4 via External S for Enhanced Oxygen Reduction Reaction

The Fe–N–C material represents an attractive oxygen reduction reaction electrocatalyst, and the FeN 4 moiety has been identified as a very competitive catalytic active site. Fine tuning of the coordination structure of FeN 4 has an essential impact on the catalytic performance. Herein, we construct a sulfur‐modified Fe–N–C catalyst with controllable local coordination environment, where the Fe is coordinated with four in‐plane N and an axial external S. The external S atom affects not only the electron distribution but also the spin state of Fe in the FeN 4 active site. The appearance of higher valence states and spin states for Fe demonstrates the increase in unpaired electrons. With the above characteristics, the adsorption and desorption of the reactants at FeN 4 active sites are optimized, thus promoting the oxygen reduction reaction activity. This work explores the key point in electronic configuration and coordination environment tuning of FeN 4 through S doping and provides new insight into the construction of M–N–C‐based oxygen reduction reaction catalysts.

25 ENERGY STORAGE↗
NASA NTRS1973

Optimal detumbling of a large manned spacecraft using an internal moving mass

The use of a movable mass control system to stabilize an arbitrarily tumbling asymmetric vehicle about the maximum inertia axis is considered. A first-order gradient optimization technique is used to minimize angular velocity components along the intermediate and minimum inertia axes. This method permits a wide range of initial guesses for mass position history. Motion of the control mass is along a linear track fixed in the vehicle. The control variable is taken as mass acceleration with respect to body coordinates. Motion is limited to defined quantities and a penalty function is used to insure a given range of positions. Numerical solutions of the optimization equations verify that minimum time detumbling is achieved with the largest permissible movable mass, length of linear track, and positions of the mass on the two coordinates perpendicular to the linear motion.

Kunciw, B. G.↗
DOE OSTI2026

Safe Deep Reinforcement Learning for Active Distribution System Model Predictive Control with EVs and DERs

The temporal and spatial mismatch between PV generation and electric vehicle (EV) charging and discharging may cause voltage violations in active distribution networks. Despite the widespread use of deep reinforcement learning (DRL) in power system optimization and control, it lacks guarantees on constraint satisfaction during both training and deployment. This paper proposes a Lagrangian-based safe DRL approach for model predictive control (MPC) of active distribution systems with large-scale integration of PVs, EVs, and energy storage systems (ESSs). A Transformer-LSTM time-series model is proposed to forecast EV charging demand, which is then formulated as a constraint to ensure charging requirements are met. Using this prediction, a Lagrangian-based safe soft actor-critic (SAC) framework is developed for real-time control in a three-phase unbalanced distribution system, enforcing voltage safety constraints while optimizing the cumulative net reward. By integrating the forecasting model with multi-period constraints, the proposed framework jointly coordinates PV systems, EV charging and discharging, and ESS scheduling within the MPC horizon. Numerical experiments on a modified IEEE 123-bus system with real-world data show that, under a high PV penetration scenario, the proposed method increases the net reward by 30.74% and reduces average voltage violations from 0.0011 p.u. to 0.0002 p.u. compared with standard SAC. Compared with the optimal power flow (OPF) approach, it achieves similar voltage security while yielding lower line losses. It also maintains real-time control capability, reducing operation latency to 53.21 ms per 15-minute control interval. The proposed method remains effective under varying PV/EV penetrations and load conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2011

A Proposal to Localize Fermi GBM GRBs Through Coordinated Scanning of the GBM Error Circle via Optical Telescopes

We investigate the feasibility of implementing a system that will coordinate ground-based optical telescopes to cover the Fermi GBM Error Circle (EC). The aim of the system is to localize GBM detected GRBs and facilitate multi-wavelength follow-up from space and ground. This system will optimize the observing locations in the GBM EC based on individual telescope location, Field of View (FoV) and sensitivity. The proposed system will coordinate GBM EC scanning by professional as well as amateur astronomers around the world. The results of a Monte Carlo simulation to investigate the feasibility of the project are presented.

Ukwatta, T. N.↗
DOE OSTI2023

Decarbonizing all-electric communities via carbon-responsive control of behind-the-meter resources

The progression of electrification in the building and transportation sectors brings new opportunities for energy decarbonization. With higher dependence on the grid power supply, the variation of the grid carbon emission intensity can be utilized to reduce the carbon emissions from the two sectors. Existing coordinated control methods for buildings with distributed energy resources (DERs) either consider electricity price or renewable energy generation as the input signal, or adopt optimization in the decision-making, which is difficult to implement in the real-world environment. This paper aims to propose and validate an easy-to-deploy rule-based carbon responsive control framework that facilitates coordination between all-electric buildings and electric vehicles (EVs). The signals of the grid carbon emission intensity and the local photovoltaics (PV) generation are used for shifting the controllable loads. Extensive simulations were conducted using a model of an all-electric mixed-use community in a cold climate to validate the control performance with metrics such as emissions, energy consumption, peak demand, and EV end-of-day state-of-charge (SOC). Our study identifies that 4.5% to 27.1% of annual emission reduction can be achieved with limited impact on energy costs, peak demand, and thermal comfort. Additionally, up to 32.7% of EV emission reduction can be obtained if the EV owners reduce the target SOC by less than 21.2%.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Real-Time Optimization and Control of Next-Generation Distribution Infrastructure

This presentation highlights the key developments of the ARAP-e NODES project, including the innovative real-time optimal power flow (RT-OPF) algorithm for distributed energy resource (DER) management, trip planning for T+D coordination, and extensive validation of the RT-OPF algorithm in NREL ESIF laboratory with 100+ physical hardware devices, controller-hardware-in-the-loop test at Southern California Edison (SCE), and two field demonstrations.

hardware-in-the-loop↗
NASA NTRS1992

Computational fluid dynamic design of rocket engine pump components

Integration of computational fluid dynamics (CFD) for design and analysis of turbomachinery components is needed as the requirements of pump performance and reliability become more stringent for the new generation of rocket engine. A fast grid generator, designed specially for centrifugal pump impeller, which allows a turbomachinery designer to use CFD to optimize the component design will be presented. The CFD grid is directly generated from the impeller blade G-H blade coordinates. The grid points are first generated on the meridional plane with the desired clustering near the end walls. This is followed by the marching of grid points from the pressure side of one blade to the suction side of a neighboring blade. This fast grid generator has been used to optimize the consortium pump impeller design. A grid dependency study has been conducted for the consortium pump impeller. Two different grid sizes, one with 10,000 grid points and one with 80,000 grid points were used for the grid dependency study. The effects of grid resolution on the turnaround time, including the grid generation and completion of the CFD analysis, is discussed. The impeller overall mass average performance is compared for different designs. Optimum design is achieved through systematic change of the design parameters. In conclusion, it is demonstrated that CFD can be effectively used not only for flow analysis but also for design and optimization of turbomachinery components.

Chen, Wei-Chung↗
DOE OSTI2023

FES 2023 Theory & Simulation Performance Target

The Report for the 2023 Theory & Simulation Performance Target (TSPT) is presented herein. The 1st, 2nd and 3rd Quarter Reports are given in Sec. I, Sec. II and Sec. III. These are unchanged from those previously submitted, except that in this final document the equations, figures and citations have been automatically renumbered. The 4th Quarter Report is given in Sec. IV. The following material presents verification calculations of several widely used three-dimensional (3D) magnetohydrodynamic (MHD) equilibrium codes in strongly shaped configurations; for both fixed and free-boundary equilibria; for the so-called vacuum case and for the case of high plasma pressure; and, for magnetic fields that have nested magnetic surfaces and for fields that have a magnetic island. The configurations studied includes the recently discovered “precise-QA” case [Phys. Rev. Lett., 128, 035001 (2002)] and other highly optimized configurations. Because of the strong (extreme) shaping, the latter of these pose challenges to the 3D MHD codes. A new method is introduced for constructing coordinates in arbitrarily shaped toroidal domains, and this can improve the robustness of 3D equilibrium calculations. Beyond the equilibrium calculation, this report demonstrates the capability of performing non-linear extended-MHD modelling of optimized stellarator equilibria. This capability allows the assessment not only of linear stability thresholds but also of the nonlinear evolution of unstable equilibria to new configurations that might be far from the original configuration, with significantly different transport properties and magnetic topology. They also enable the self-consistent determination of pressure profiles in non-integrable magnetic topology through the use of highly anisotropic thermal-transport equations. The calculations presented here represent the first demonstration of extended-MHD calculations in strongly-shaped, optimized quasi-symmetric configurations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Structure of a seeded palladium nanoparticle and its dynamics during the hydride phase transformation

Palladium absorbs large volumetric quantities of hydrogen at room temperature and ambient pressure, making the palladium hydride system a promising candidate for hydrogen storage. Here, we use Bragg coherent diffraction imaging to map the strain associated with defects in three dimensions before and during the hydride phase transformation of an individual octahedral palladium nanoparticle, synthesized using a seed-mediated approach. The displacement distribution imaging unveils the location of the seed nanoparticle in the final nanocrystal. By comparing our experimental results with a finite-element model, we verify that the seed nanoparticle causes a characteristic displacement distribution of the larger nanocrystal. During the hydrogen exposure, the hydride phase is predominantly formed on one tip of the octahedra, where there is a high number of lower coordinated Pd atoms. Our experimental and theoretical results provide an unambiguous method for future structure optimization of seed-mediated nanoparticle growth and in the design of palladium-based hydrogen storage systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Adaptive Reinforcement Learning Control for Power Distribution in Multi-Output Resonant Converters

This paper presents an adaptive reinforcement learning (ARL)-based control framework for efficient power distribution in a multi-output resonant converter for UAV applications. The proposed system is based on a high-frequency isolated resonant architecture, where a single energy source supplies multiple propulsion loads through independently controlled output rectifiers, addressing the need for coordinated multi-motor power management. The ARL framework dynamically allocates output power by learning optimal phase-shift control actions under varying load demands and operating conditions. The agent autonomously determines control parameters that maximize conversion efficiency while ensuring accurate power sharing among multiple outputs. In addition, the proposed approach enables adaptive operation without requiring detailed system modeling or manual tuning. Experimental results demonstrate stable and efficient performance over a wide range of operating conditions, confirming the effectiveness and robustness of the learning-based control strategy for multi-output resonant converter system.

Asa, Erdem [ORNL] (ORCID:0000000190884812)↗
NASA NTRS1981

Minimum fuel horizontal flightpaths in the terminal area

The problem of minimum fuel airplane trajectories from arbitrary initial states to be fixed final state is considered. There are four state variables (two position coordinates, heading, and constrained velocity) and two constrained controls (thrust and bank angle). The fuel optimality of circular and straight line flightpaths is examined. Representative extremals (trajectories satisfying the necessary conditions of the minimum principle) of various types are computed and used to evaluate trajectories generated by an on line algorithm. Attention is paid to the existence of Darboux points (beyond which an extremal ceases to be globally optimal). One fuel flow rate model includes a term quadratic in thrust; hence, the optimal thrust is continuous and nonsingular. The other fuel flow rate model is linear in thrust, and consequently the optimal thrust is discontinuous and singular.

Kreindler, E.↗
NASA NTRS1983

Interaction of metal ions and amino acids - Possible mechanisms for the adsorption of amino acids on homoionic smectite clays

A semiempirical molecular orbital method is used to characterize the binding of amino acids to hexahydrated Cu(2+) and Ni(2+), a process presumed to occur when they are adsorbed in the interlamellar space of homoionic smectite clays. Five alpha-amino acids, beta-alanine, and gamma-aminobutyric acid were used to investigate the metal ion and amino acid specificity in binding. It was assumed that the alpha, beta, and gamma-amino acids would bind as bidentate anionic ligands, forming either 1:1 or 1:2 six-coordinated five, six, and seven-membered-ring chelate complexes, respectively. Energies of complex formation, optimized geometries, and electron and spin distribution were determined; and steric constraints of binding of the amino acids to the ion-exchanged cations in the interlamellar spacing of a clay were examined. Results indicate that hexahydrated Cu(2+) forms more stable complexes than hexahydrated Ni(2+) with all the amino acids studied. However, among these amino acids, complex formation does not favor the adsorption of the biological subset. Calculated energetics of complex formation and steric constraints are shown to predict that 1:1 rather than 1:2 metal-amino acid complexes are generally favored in the clay.

Gupta, A.↗