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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 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Model-based predictive control of multi-stage air-source heat pumps integrated with phase change material-embedded ceilings

This paper presents a model-based predictive control strategy to optimize the operations of phase change material (PCM) ceiling panels coupled with a multi-stage air-source heat pump. A three-stage prototype heat pump unit has been built and tested in the laboratory, with the low and medium stages designed for space heating/cooling and the high compression stage dedicated to charging of the PCM energy storage. To facilitate optimal control of the integrated heat pump system, a mixed-integer linear programming formulation is derived through linearization of the heat pump model and a mixed-integer reformulation of the PCM dynamic governing equations. A predictive control strategy is synthesized based on the resultant control formulation and implemented in a receding horizon scheme that optimizes the PCM charging and the zone temperature schedules simultaneously to leverage both the passive (associated with building construction materials) and active (PCM) storage capacities of a building. The control strategy has been tested along with three benchmarking control scenarios using a co-simulation platform for a prototypical detached house in Atlanta, GA. In this study, test results showed that application of the proposed control strategy to the PCM-integrated heat pump could provide 27.1% electricity cost savings while a fine tuned rule-based control strategy could achieve cost savings of 20.4%, compared to a baseline case without PCM storage, under a time-of-use rate tariff.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Slurry rheology of Hanford sludge

Here we evaluate the slurry viscosity of radioactive waste. Hanford waste is a motely mixture of particle sizes and densities composed of metal and oxide particles with constituents spanning much of the periodic table stored at high ionic strength and high pH. Hanford wastes have traditionally been represented as simply an ideal Bingham plastic, but this rheological approximation often provides a poor fit from 0 to 200 1/s, precisely the range of interest for engineering design of waste transport and mixing systems. Here we use a modified Cross formulation inclusive of a yield stress to fit stress-strain rate data for reconstituted Hanford REDOX sludge waste, measured by increasing shear-rate (up-ramp) and decreasing shear-rate (down-ramp) sweeps. We find that this continuous single equation formulation quantitatively matches experimental data better than other rheological models including the Bingham plastic and Herschel-Bulkley approximations. The increase of viscosity and yield stress from up ramp to down ramp indicates the formation of particle microstructure during shear due to attractive forces.

radioactive waste, high ionic strength slurries, y↗
DOE OSTI2022

In Situ Studies of the Formation of MoP Catalysts and Their Structure under Reaction Conditions for Higher Alcohol Synthesis: The Role of Promoters and Mesoporous Supports

Three formulations of a molybdenum phosphide (MoP) catalyst system were characterized for the higher alcohol synthesis (HAS) reaction using in situ X-ray absorption spectroscopy (XAS) and X-ray diffraction (XRD), monitoring the chemical phase evolution during activation and under reaction conditions. Here, the in situ study herein provides important insights into the effect of the support and of K that lead to high performance in HAS for K-promoted MoP supported on carbon, as evidenced by previous studies (ethanol selectivity: 29%; conversion: 5%). During the activation process, XAS shows that the carbon-supported samples reduce and reach a highly crystalline state at a lower temperature than the SBA-15-supported sample, indicating a substantial difference in catalyst activation. After activation, the samples are introduced to relevant reaction conditions resulting in spectra fairly similar to one another. XRD results corroborate the difference in the degree of crystallinity of these samples, in alignment with the XAS, and reveal the formation of crystalline potassium pyrophosphate (K 4 P 2 O 7 ) during the activation period of the K-promoted samples. This K 4 P 2 O 7 phase remains present under reaction conditions. Taken together, these results provide insights into the roles played by the carbon support and K promotion, connecting activity to electronic and crystal structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Tsirelson's problem and asymptotically commuting unitary matrices

In this paper, we consider quantum correlations of bipartite systems having a slight interaction, and reinterpret Tsirelson's problem (and hence Kirchberg's and Connes's conjectures) in terms of finite-dimensional asymptotically commuting positive operator valued measures. We also consider the systems of asymptotically commuting unitary matrices and formulate the Stronger Kirchberg Conjecture.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Control of simulation of a particle accelerator as a spatially distributed system

The work deals with the construction of strategy for finding optimal control of systems for spatially distributed systems on an example of problems in physics beams. The suggested approach is based on use of exact and approximate invariants as a controlling mechanism for control of modelling process of beam lines. The classical problem of optimal control of similar systems as an optimal control problem is formulated in a functional space. This approach is based on algebraic methods Lie and the corresponding matrix formalism that allows you to build not only the formal procedures for finding optimal solutions, but also provide the necessary constructive computational procedures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

On extending Kohn-Sham density functionals to systems with fractional number of electrons

Here, we analyze four ways of formulating the Kohn-Sham (KS) density functionals with a fractional number of electrons, through extending the constrained search space from the Kohn-Sham and the generalized Kohn-Sham (GKS) non-interacting $\mathcal{v}$-representable density domain for integer systems to four different sets of densities for fractional systems. In particular, these density sets are (I) ensemble interacting N -representable densities, (II) ensemble non-interacting N -representable densities, (III) non-interacting densities by the Janak construction, and (IV) non-interacting densities whose composing orbitals satisfy the Aufbau occupation principle. By proving the equivalence of the underlying first order reduced density matrices associated with these densities, we show that sets (I), (II), and (III) are equivalent, and all reduce to the Janak construction. Moreover, for functionals with the ensemble v-representable assumption at the minimizer, (III) reduces to (IV) and thus justifies the previous use of the Aufbau protocol within the (G)KS framework in the study of the ground state of fractional electron systems, as defined in the grand canonical ensemble at zero temperature. By further analyzing the Aufbau solution for different density functional approximations (DFAs) in the (G)KS scheme, we rigorously prove that there can be one and only one fractional occupation for the Hartree Fock functional, while there can be multiple fractional occupations for general DFAs in the presence of degeneracy. This has been confirmed by numerical calculations using the local density approximation as a representative of general DFAs. This work thus clarifies important issues on density functional theory calculations for fractional electron systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Neural network representability of fully ionized plasma fluid model closures

The closure problem in fluid modeling is a well-known challenge to modelers aiming to accurately describe their systems of interest. Over many years, analytic formulations in a wide range of regimes have been presented but a practical, generalized fluid closure for magnetized plasmas remains an elusive goal. Here, as a first step toward constructing a novel data-based approach to this problem, we apply ever-maturing machine learning methods to assess the capability of neural network architectures to reproduce crucial physics inherent in known magnetized plasma closures. We find encouraging results, indicating the applicability of neural networks to closure physics, but also arrive at recommendations on how one should choose appropriate network architectures for the given locality properties dictated by the underlying physics of the plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Optimizing protic ionic liquid electrolyte for pre-intercalated Ti 3 C 2 T x MXene supercapacitor electrodes

Electrical double-layer capacitors (EDLCs) are of increasing importance in energy storage from renewable sources. The properties of the electrode and electrolyte materials influence the energy and power densities of EDLCs. We examined the specific capacitance and ion dynamics of a protic ionic liquid confined in pre-intercalated Ti 3 C 2 T x MXene. Our electrochemical measurements demonstrated that the creation of a protic ionic liquid, 1-butyl-3-H-imidazolium bis(trifluoromethanesulfonyl)imide (BuIMH-NTf2), using a mixture of ionic liquid, 1-butyl imidazole (BuIM), and salt, bis(trifluoromethanesulfonyl)imide (HNTf2), in a ratio of 0.8:0.2 led to the optimal capacitance. Remarkably, quasi-elastic neutron scattering measurements revealed increased particle mobility at this composition, attributed to the more efficient accumulation of BuIMH + on the electrode surface. This deposit of additional ions results in fewer BuIM molecules away from the surface, enhancing their mobility due to reduced crowding. This composition-dependent electrochemical behavior will guide the formulation of more efficient protic ionic liquid systems, enabling faster ion transport in energy storage devices.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Integrated rheology model: Explosive Composition B-3

Composition B-3 (Comp B-3) is a high explosive formulation composed of 60/40wt% RDX (1,3,5-trinitroperhydro-1,3,5-triazine) /TNT (2,4,6 trinitrotoluene). Above approximately 78°C this formulation partially melts to form a multiphase system with solid RDX particles in a molten TNT matrix. This multiphase system presents a number of phenomena that influence its apparent viscosity. In an earlier study explosive Composition B-3 (Comp B-3, 60/40wt% RDX/TNT) was examined for evidence of yield stress using a non-isothermal falling ball viscometer and a yield stress model was proposed in this paper. An integrated viscosity model suitable for use in computational fluid dynamics (CFD) simulations is developed to capture the transition from a heterogeneous solid to a Bingham viscoplastic fluid. This viscosity model is used to simulate the motion of imbedded spheres falling through molten Comp B-3. Finally, comparison of the simulations to physical tests show agreement between the positions predicted by the model and the measured locations of the spheres as a function of temperature between 90C and 165C.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Generalized Kapchinskij-Vladimirskij Distribution and Beam Matrix for Phase-Space Manipulations of High-Intensity Beams

In an uncoupled linear lattice system, the Kapchinskij-Vladimirskij (KV) distribution formulated on the basis of the single-particle Courant-Snyder invariants has served as a fundamental theoretical basis for the analyses of the equilibrium, stability, and transport properties of high-intensity beams for the past several decades. Recent applications of high-intensity beams, however, require beam phase-space manipulations by intentionally introducing strong coupling. Here in this Letter, we report the full generalization of the KV model by including all of the linear (both external and space-charge) coupling forces, beam energy variations, and arbitrary emittance partition, which all form essential elements for phase-space manipulations. The new generalized KV model yields spatially uniform density profiles and corresponding linear self-field forces as desired. Finally, the corresponding matrix envelope equations and beam matrix for the generalized KV model provide important new theoretical tools for the detailed design and analysis of high-intensity beam manipulations, for which previous theoretical models are not easily applicable.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

An Efficient Bayesian Method for Advancing the Application of Deep Learning in Earth Science

Despite their wide and successful applications, deep learning (DL) models are prone to overfitting for small training datasets, produce a poor predictive performance for uncertain data, and provide point estimations without any indication of the accuracy and credibility. These limitations of the deterministic DL models hinder their effective application in Earth system science where the labelled data are sparse, noisy and incomplete with large uncertainty and where the predictive uncertainty quantification is needed for scientific understanding and policy decision making. Integration of Bayesian inference into DL models adds an estimate of uncertainty and regularization in the predictions. However, traditional Bayesian methods are computationally unaffordable and inflexible for high-dimensional problems, which limits their application to DL systems that typically have millions of model parameters. In this effort, we propose an efficient and general-purpose Bayesian inference method to advance DL model optimization and uncertainty quantification, so as to facilitate the adoption of DL in Earth sciences. In a demonstration, we integrate the proposed Bayesian method with a feedforward neural network (NN) to build a fast-to-evaluate surrogate of the complex Energy Exascale Earth System Land Model for efficient modeling. The formulated Bayesian NN, using a small number of training data, produces an accurate prediction with high credibility, whereas with the same small training size, the deterministic NN cannot yield a reasonable estimation and does not provide confidence information. The proposed Bayesian method is computationally efficient and flexible, capable of integration with diverse network variants such as convolutional NNs and recurrent NNs to advance the application of DL in Earth sciences.

Lu, Dan↗
DOE OSTI2020

Methods and Experiences for Developing Abstractions for Data-intensive, Scientific Applications

Developing software for scientific applications that require the integration of diverse types of computing, instruments, and data present challenges that are distinct from commercial software. These applications require scale, and the need to integrate various programming and computational models with evolving and heterogeneous infrastructure. Pervasive and effective abstractions for distributed infrastructures are thus critical; however, the process of developing abstractions for scientific applications and infrastructures is not well understood. While theory-based approaches for system development are suited for well-defined, closed environments, they have severe limitations for designing abstractions for scientific systems and applications. The design science research (DSR) method provides the basis for designing practical systems that can handle real-world complexities at all levels. In contrast to theory-centric approaches, DSR emphasizes both practical relevance and knowledge creation by building and rigorously evaluating all artifacts. In this work, we show how DSR provides a well-defined framework for developing abstractions and middleware systems for distributed systems. Specifically, we address the critical problem of distributed resource management on heterogeneous infrastructure over a dynamic range of scales, a challenge that currently limits many scientific applications. We use the pilot-abstraction, a widely used resource management abstraction for high-performance, high throughput, big data, and streaming applications, as a case study for evaluating the DSR activities. For this purpose, we analyze the research process and artifacts produced during the design and evaluation of the pilot-abstraction. We find DSR provides a concise framework for iteratively designing and evaluating systems. Finally, we capture our experiences and formulate different lessons learned.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Enhancing Power Grid Resilience with Causal Loops Diagram and Bayesian Networks

Enhancing power grid resilience through improved analysis and planning of Distributed Energy Resources is a key for power system planner. This paper explores the integration of Causal Loop Diagrams (CLDs) and Bayesian Networks (BNs) for enhancing resilience in power systems, focusing on Distributed Energy Resources (DER) planning. By automating CLD analysis in Python's matplotlib, we present a tool for rapid model validation and structural accuracy, crucial for power system planners. This hybrid approach utilizes BNs for inferential depth and CLDs for dynamic system modeling, offering a comprehensive framework for policy formulation and collaborative strategy development against disruptions. Here, we highlight the tool's capability to identify and analyze interconnected feedback loops, facilitating a deeper understanding of DER integration's impact on network resilience. This work aims to bridge quantitative analysis and qualitative insights, addressing the limitations of each method while providing a robust model for power system resilience assessment.

14 SOLAR ENERGY↗
DOE OSTI2015

Bayesian Calibration of the Community Land Model using Surrogates

We present results from the Bayesian calibration of hydrological parameters of the Community Land Model (CLM), which is often used in climate simulations and Earth system models. A statistical inverse problem is formulated for three hydrological parameters, conditioned on observations of latent heat surface fluxes over 48 months. Our calibration method uses polynomial and Gaussian process surrogates of the CLM, and solves the parameter estimation problem using a Markov chain Monte Carlo sampler. Posterior probability densities for the parameters are developed for two sites with different soil and vegetation covers. Our method also allows us to examine the structural error in CLM under two error models. We find that accurate surrogate models can be created for CLM in most cases. The posterior distributions lead to better prediction than the default parameter values in CLM. Climatologically averaging the observations does not modify the parameters’ distributions significantly. The structural error model reveals a correlation time-scale which can potentially be used to identify physical processes that could be contributing to it. While the calibrated CLM has a higher predictive skill, the calibration is under-dispersive.

Bayesian calibration↗
DOE OSTI2025

Exascale Julia Grid Optimization

Simple Julia scrips for solving AC power flow, AC optimal power flow, and security-constrained AC optimal power flow. These scripts are intended for experimentation with different (possibly, new) methods, formulations, and settings for solving these power system problem. Their implementation, therefore, intentionally avoids excessive encapsulation, which makes other packages difficult to modify by non-developers.

Petra, Cosmin [Lawrence Livermore National Laborat↗
DOE OSTI2023

Development of a dynamical model and energy analysis for wheel loader

The objective of this paper is to develop a fully integrated model for the wheel loader, including the subsystem dynamics of the engine, drivetrain, working circuit, steering circuit, and vehicle. It leads to a high-order strongly nonlinear system, and all state variables are coupled together to form a Multi-Input and Multi-Output (MIMO) system. A control architecture is proposed to decouple the MIMO system into several Single-Input and Single-Output (SISO) systems. Here, a tracking problem has been formulated to validate this fully integrated model with the field test data. The accuracy of the model is verified by the 2.3% difference between the measured and simulated fuel consumption. Meanwhile, an energy distribution analysis is conducted to reveal the energy consumption and energy loss of each portion of the wheel loader. Such a model can be used to plan the working pattern, guide the driving habits of human operators, or refine the underlying architecture, leading to the ultimate goal of reducing total fuel consumption and improving productivity.

42 ENGINEERING↗
DOE OSTI2012

New Experimental Data in DC745U [Slides]

The objectives of this project are: (1) study the molecular and mechanical properties of DC745U - (a) DC745U is a silicone elastomer used in several weapons systems, (b) depending on their chemistry and formulation, polymers can be susceptible to damage and failures due to weak chemical linkages and physical interactions, (c) inefficient production processes can generate heterogeneities throughout the material that can contribute negatively to the overall performance and lifetime of the polyer, (d) aging, long-term thermal and radioactive conditions, and mechanical strains can affect the materials network structure and contribute to the degradation of the production; (2) characterization of DC745U materials cured under different conditions to determine possible differences to the polymer structure; and (3) this work is relevant to mission-critical programs and for supporting programmatic work for weapon research.

36 MATERIALS SCIENCE↗
DOE OSTI2012

DHS Written Report

Recently, a new galactic cosmic-ray (GCR) source option [1] was implemented in the all-energy, all-particle transport code MCNP6 [2]. In this paper, we made use of this feature to calculate surface neutron and photon background fluxes on a terrestrial grid around the earth. These spectra have been incorporated into Release 2 of the 'background.dat' file, which is read and sampled by MCNP6 whenever a user invokes the background source option [2]. Cosmic radiation bombards Earth with various particles, such as protons and {alpha} particles, some of which are deflected by the Earth's shielding magnetic field. Particles that carry sufficient energy can overcome the deflection and penetrate into the atmosphere. The sufficient energy is dependent on the terrestrial coordinates due to the magnetic force's proportionality to the sine of the angle between the velocity vector of the incoming particle and the magnetic field. As the particles propagate through the atmosphere, collisions with atmospheric molecules generate new particles such as neutrons, protons, photons, muons, pions, and other exotic particles. These secondary often have sufficient energy to undergo additional nuclear interactions, and so on, forming what is known as a cascade shower. The tabulation of background particle fluxes on the surface of the earth is important for a variety of reasons, one of which is the design of nuclear material detection systems. The simulations used various models and formulations for the cosmic source spectra, atmosphere, and terrestrial conditions to correctly model the propagation of GCR particles through the atmosphere to surface level.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗