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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Selective formation of metastable polymorphs in solid-state synthesis

Metastable polymorphs often result from the interplay between thermodynamics and kinetics. Despite advances in predictive synthesis for solution-based techniques, there remains a lack of methods to design solid-state reactions targeting metastable materials. Here, we introduce a theoretical framework to predict and control polymorph selectivity in solid-state reactions. This framework presents reaction energy as a rarely used handle for polymorph selection, which influences the role of surface energy in promoting the nucleation of metastable phases. Through in situ characterization and density functional theory calculations on two distinct synthesis pathways targeting LiTiOPO 4 , we demonstrate how precursor selection and its effect on reaction energy can effectively be used to control which polymorph is obtained from solid-state synthesis. A general approach is outlined to quantify the conditions under which metastable polymorphs are experimentally accessible. With comparison to historical data, this approach suggests that using appropriate precursors could enable targeted materials synthesis across diverse chemistries through selective polymorph nucleation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Virtual Framework for Science Federations with Instruments Access and Control

Experimental science workflows require federations of geographically dispersed science instruments and computing systems connected over a wide-area network. We develop a Virtual Infrastructure Twin (VIT) framework, which is a digital twin of the physical infrastructure that utilizes network virtualization and containerization technologies to support the development and testing of science workflow codes. Using VIT, we illustrate the access to instruments via EPICS system and the orchestration of containerized computations across federation computing systems. We also present a machine learning method to convert VIT throughput measurements to closely match the corresponding physical testbed measurements.

Rao, Nageswara↗
DOE OSTI2023

Designing dynamically corrected gates robust to multiple noise sources using geometric space curves

Noise-induced gate errors remain one of the main obstacles to realizing a broad range of quantum information technologies. Dynamical error suppression using carefully designed control schemes is critical for overcoming this challenge. Such schemes must be able to correct against multiple noise sources simultaneously afflicting a qubit to reach error-correction thresholds. Here we present a general framework for designing control fields that simultaneously suppress both noise in the fields themselves as well as transverse dephasing noise. Using the recently developed space curve quantum control formalism, in which robust quantum evolution is mapped to closed geometric curves in a multidimensional Euclidean space, we derive the minimal conditions necessary to guarantee the simultaneous cancellation of both types of noise to leading order. In particular, we find that the cancellation of control field noise requires the derivative of the space curve to have zero-area projections, which is a much more subtle property compared to the closed-curve condition needed to suppress transverse dephasing. We present several techniques for solving both these conditions simultaneously and provide explicit examples of error-resistant control fields. Finally, our work also sheds light on the relation between holonomic evolution and the suppression of control field errors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

INECP Country Engagement Plans and Transformational Events [Slides]

The International Nonproliferation Export Control Program (INECP) harnesses the expertise of the U.S. Department of Energy (DOE) national laboratories to assist partners internationally in implementing and adopting strategic trade control measures that can effectively counter WMD procurement efforts. This presentation includes discussion of work with LANL INECP technical leads to update the engagement plan for Turkey, which involved researching Turkey’s WMD related legal framework, relevant export control agencies, and WMD-relevant industries (e.g. advanced manufacturing and aerospace).

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
NASA NTRS1993

Inertial-space disturbance rejection for space-based manipulators

The implementation of a disturbance rejection controller for a 6-DOF PUMA manipulator mounted on a 3-DOF platform was described. A control algorithm is designed to track the desired position and attitude of the end-effector in inertial space, subject to unknown disturbances in the platform axes. Experimental results are presented for step, sinusoidal, and random disturbances in the platform rotational axis and in the neighborhood of kinematic singularities. Robotic manipulators were proposed as a means of reducing the amount of extra vehicular activity time required for space station assembly and maintenance. The proposed scenario involves a robotic manipulator attached to some mobile platform, such as a spacecraft, satellite, or the space station itself. Disturbances in the platform position and attitude may prevent the manipulator from successfully completing the task. The possibility of using the manipulator to compensate for platform disturbances was explored. The problem of controlling a robotic manipulator on a mobile platform has received considerable attention in the past few years. Joshi and Desrochers designed a nonlinear feedback control law to carry out tasks (with respect to the robot base frame) in the presence of roll, pitch and yaw disturbances in the platform axes. Dubowsky, Vance, and Torres proposed a time-optimal planning algorithm for a robotic manipulator mounted on a spacecraft, subject to saturation limits in the attitude control reaction jets. Papadopoulos and Dubowsky developed a general framework for analyzing the control of free-floating space manipulator systems. Most recently, Torres and Dubowsky have presented a technique called the enhanced disturbance map to find manipulator trajectories that reduce the effect of disturbances in the spacecraft position and attitude. One common assumption in the literature is that the disturbance signal is exactly known. If this is the case, then the end-effector location can be calculated without relying on direct end-point sensing. However, this assumption is invalid if there is a significant delay in the platform position and attitude measurements, or if the kinematics of the platform are not well known, or if the platform is a non-rigid structure. In the more likely case that only the nominal platform location and upper bound on the disturbance signal are known, direct end-point sensing is needed to measure the end-effector location.

Holt, Kevin↗
DOE OSTI2021

SIRIUS: Science-Driven Data Management for Multi-Tiered Storage

The data sets being generated by large applications on very large-scale systems are increasing in both size and complexity. At the same time, there are new ways available to store and access these data sets. The goal in this project is to develop software that applications can use to make use of new and existing storage technologies in more sophisticated ways. One challenge in scientific data management is handling ‘hot’ vs ‘cold’ data. Data that is hot is data that is needed (or will be needed soon) in order for the program to continue progressing, while cold data is either output (and so will not be need further during the life of the program) or will not be needed until significantly later in the program’s run. Hot data should be stored in a way that allows fast access. On most systems, economic factors lead to an inverse relationship between storage performance and storage capacity and so fast access storage is limited. This makes it important to correctly place hot and cold data and avoid cold data unnecessarily consuming precious resources. In this reporting period, we addressed this challenge in various ways and at various levels. Data management frameworks offer only limited control to applications in how data is stored. We have added software capabilities for seamlessly moving data between layers of the storage technology using promote and demote functions to existing software frameworks. This gives direct control to applications in deciding what priority data receives. Additionally, we integrated different storage layer management frameworks in order to allow data to be exchanged and moved between storage layers in a consistent way across the application. Further, applications are not always able to directly decide what storage level makes sense for a given piece of data without an understanding of the underlying storage technologies. Data storage frameworks are often positioned to make these sorts of decisions in service of the application. We have added machine-learning based capabilities to data staging frameworks in order to make intelligent decisions about where data should be stored given learning about patterns in previous usage of similar data.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2001

Control and Observation in Distributed Environments

This viewgraph presentation gives an overview of the control and observation in distributed environments. No existing system meets all our needs (e.g., they cannot be embedded in tools or applications and have limited fault management functionality). The goals of our infrastructure include the following: (1) to develop a general framework for observation and control; (2) the framework should be extensible for specific tasks; and (3) it must be compatible with emerging standards.

Smith, Warren↗
DOE OSTI2025

A neural-network-enhanced parameter-varying framework for multi-objective model predictive control applied to buildings

Management of the electrical grid is becoming more complex due to the increased penetration of alternative energy generation technologies and a broadening diversity of electric loads. This complexity creates challenges in balancing demand and generation that can increase the potential for grid instabilities. One effective way to address this issue is to leverage previously unexploited demand flexibility through advanced control strategies. In this work, we propose an advanced control method, called adaptive neural parameter-varying model predictive control (ANPV-MPC), to control the temperature and energy consumption of a building via its Heating, Ventilation, and Air Conditioning system. ANPV-MPC combines key ideas in parameter-varying control, adaptive control, and online learning strategies to bridge the gap between computationally efficient linear model predictive control and more accurate nonlinear model predictive control. The novelty in ANPV-MPC is the use of a physics-inspired Bayesian neural network to estimate the coefficients of the parameter-varying linear control model. The Bayesian neural network additionally provides uncertainty estimates, triggering online training to capture evolving building system conditions. We show that ANPV-MPC can approximate the building system dynamics with a 28.39% higher accuracy than traditional linear model predictive control, resulting in 36.23% better control performance without increasing complexity of the optimal control problem. ANPV-MPC also adapts in real time to previously unseen conditions using online learning, further improving its performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Galerkin Neural Networks: A Framework for Approximating Variational Equations with Error Control

Herein, we present a new approach to using neural networks to approximate the solutions of variational equations, based on the adaptive construction of a sequence of finite-dimensional sub-spaces whose basis functions are realizations of a sequence of neural networks. Here, the finite-dimensional subspaces are then used to define a standard Galerkin approximation of the variational equation. This approach enjoys a number of advantages, including: the sequential nature of the algorithm offers a systematic approach to enhancing the accuracy of a given approximation; the sequential enhancements provide a useful indicator for the error that can be used as a criterion for terminating the sequential updates; the basic approach is largely oblivious to the nature of the partial differential equation under consideration; and, some basic theoretical results are presented regarding the convergence (or otherwise) of the method which are used to formulate basic guidelines for applying the method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

MULTI-FIDELITY MODELING AND UNCERTAINTY QUANTIFICATION OF INVERTER BASED RESOURCES IN INTEGRATED T&D SYSTEMS

Uncertainty quantification plays a pivotal role in improving the accuracy and reliability of inverter operation within modern power systems that are increasingly dominated by inverter-based resources (IBRs). IBRs, especially those operating under grid forming (GFM) control, rely heavily on a complex set of control parameters and system measurements to maintain voltage, frequency, and power balance. Traditional deterministic modeling approaches often fail to capture these parameter deviations, potentially resulting in suboptimal control actions, reduced system stability, or even instability under high penetration of IBRs. In this paper, we demonstrate the application of model calibration and uncertainty quantification (UQ) principles to an integrated transmission and distribution (T&D) model involving a GFM converter and provide a framework for prioritizing control improvements, guiding robust design, and informing adaptive strategies that can accommodate real-time variability in system conditions. The proposed approach could be valuable in enhancing the robustness of current and future power systems under increased IBR penetrations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1989

Optimal trajectories for hypervelocity flight

Optimal trajectories for hypervelocity flight of interest in aeroassisted orbital transfer are discussed. Both coplanar and noncoplanar transfer are studied. More precisely, the geosynchronous-earth-orbit-, high-earth orbit- and low-earth-orbit-to-low earth-orbit transfers are considered in connection with a spacecraft that is controlled during the atmospheric pass by the angle of attack (coplanar case) or by the angle of attack and the angle of bank (noncoplanar case). Within the framework of classical optimal control, the following problems are studied: minimize the energy required for orbital transfer; maximize the time of flight during the atmospheric portion of the trajectory; and minimize the time integral of the square of the path inclination. Within the framework of minimax optimal control, the problem studied is to minimize the peak rate. Numerical solutions for the problems are obtained by means of the sequential gradient-restoration algorithm. The engineering implications of the results are discussed.

Miele, A.↗
NASA NTRS1990

Towards a methodology for robust parameter identification

Consideration is given to the problem of estimating, from experimental data, real parameters for a model with uncertainty in the form of both additive noise and norm-bounded perturbations. Such models frequently arise in robust control theory, and a framework is introduced for the consideration of experimental data in robust control analysis problems. If the analysis tools applied include robust stability tests for real parameter variations (real mu), the framework can be used to address the problem of robust parameter identification. While the techniques discussed can quickly become computationally overwhelming when applied to physical systems and real data, the approach introduces a novel way of looking at the identification problem and may be helpful in arriving at a more tractable methodology.

Smith, Roy S.↗
DOE OSTI2021

Applying design principles to improve hydrogen storage capacity in nanoporous materials

Hydrogen is an attractive option for energy storage because it can be produced from renewable sources and produces environmentally benign byproducts. However, the volumetric energy density of molecular hydrogen at ambient conditions is low compared to other storage methods like batteries, so it must be compressed to attain a viable energy density for applications such as transportation. Nanoporous materials have attracted significant interest for gas storage because they can attain high storage density at lower pressure than conventional compression. Here, we examine how to improve the cryogenic hydrogen storage capacity of a series of porous aromatic frameworks (PAFs) by controlling the pore size and increasing the surface area by adding functional groups. We also explore tradeoffs in gravimetric and volumetric measures of the hydrogen storage capacity and the effects of temperature swings using grand canonical Monte Carlo simulations. We also consider the effects of adding functional groups to the metal–organic framework NU-1000 to improve its hydrogen storage capacity. We find that highly flexible alkane chains do not improve the hydrogen storage capacity in NU-1000 because they do not extend into the pores; however, rigid chains containing alkyne groups do increase the surface area and hydrogen storage capacity. Finally, we demonstrate that the deliverable capacity of hydrogen in NU-1000 can be increased from 40.0 to 45.3 g/L (at storage conditions of 100 bar and 77 K and desorption conditions of 5 bar and 160 K) by adding long, rigid alkyne chains into the pores.

08 HYDROGEN↗
DOE OSTI2023

Kinetic Control via Binding Sites within the Confined Space of Metal Metalloporphyrin-Frameworks for Enhanced Shape-Selectivity Catalysis

One striking feature of enzyme is its controllable ability to trap substrates via synergistic or cooperative binding in the enzymatic pocket, which renders the shape-selectivity of product by the confined spatial environment. The success of shape-selective catalysis relies on the ability of enzyme to tune the thermodynamics and kinetics for chemical reactions. In emulation of enzyme's ability, we showcase herein a targeting strategy with the substrate being anchored on the internal pore wall of metal-organic frameworks (MOFs), taking full advantage of the sterically kinetic control to achieve shape-selectivity for the reactions. For this purpose, a series of binding site-accessible metal metalloporphyrin-frameworks (MMPFs) have been investigated to shed light on the nature of enzyme-mimic catalysis. They exhibit a different density of binding sites that are well arranged into the nanospace with corresponding distances of opposite binding sites. Furthermore, such a structural specificity results in a facile switch in selectivity from an exclusive formation of the thermodynamically stable product to the kinetic product. Thus, the proposed targeting strategy, based on the combination of porous materials and binding events, paves a new way to develop highly efficient heterogeneous catalysts for shifting selectivity.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗