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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

GRIZZLY MODEL OF FULLY COUPLED HEAT TRANSFER, MOISTURE DIFFUSION, ALKALI-SILICA REACTION AND FRACTURING PROCESSES IN CONCRETE

Idaho National Laboratory (INL) has been developing a fully coupled thermo-hydro-mechanical-chemical (THMC) concrete model, referred as Grizzly, with the ultimate goal of reliably simulating and predicting the long-term performance of concrete structures subjected to various aging and degradation mechanisms. In this paper, we present a fully coupled concrete model implemented in our Grizzly code for simulating coupled moisture/heat transfer, stress-dependent ASR swelling and elastic/inelastic mechanics. Example simulation results and preliminary model validation results against experimental data reported in the literature will be provided also in this paper. The close matches between the simulation results and experiments clearly reveal the potential of the fully coupled solution strategy for solving tightly coupled THMC concrete models. We also present simulation results of using a rate-dependent damaging mechanics model for simulating the ASR swelling induced degradation of concrete structures and its feedback to moisture and heat transport processes.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2014

Tidal heating in multilayered terrestrial exoplanets

The internal pattern and overall magnitude of tidal heating for spin-synchronous terrestrial exoplanets from 1 to 2.5 R{sub E} is investigated using a propagator matrix method for a variety of layer structures. Particular attention is paid to ice-silicate hybrid super-Earths, where a significant ice mantle is modeled to rest atop an iron-silicate core, and may or may not contain a liquid water ocean. We find multilayer modeling often increases tidal dissipation relative to a homogeneous model, across multiple orbital periods, due to the ability to include smaller volume low viscosity regions, and the added flexure allowed by liquid layers. Gradations in parameters with depth are explored, such as allowed by the Preliminary Earth Reference Model. For ice-silicate hybrid worlds, dramatically greater dissipation is possible beyond the case of a silicate mantle only, allowing non-negligible tidal activity to extend to greater orbital periods than previously predicted. Surface patterns of tidal heating are found to potentially be useful for distinguishing internal structure. The influence of ice mantle depth and water ocean size and position are shown for a range of forcing frequencies. Rates of orbital circularization are found to be 10-100 times faster than standard predictions for Earth-analog planets when interiors are moderately warmer than the modern Earth, as well as for a diverse range of ice-silicate hybrid super-Earths. Circularization rates are shown to be significantly longer for planets with layers equivalent to an ocean-free modern Earth, as well as for planets with high fractions of either ice or silicate melting.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Impedance Emulation Control of Wave Energy Converters

Modeling and control of wave energy conversion (WEC) systems for maximum power extraction is challenging due to complex multiphysics that include fluids, mechanics, and machine drives. To uncover an intuitive model that clearly depicts WEC system operation, we utilize a force-current equivalent circuit framework which then enables us to design an impedance emulation control strategy. To provide context for our framework, we focus on a standard reference model-3 (RM3) point absorber device coupled to a permanent magnet synchronous generator. After the proposed extremum seeking controller is computed, we experimentally validate its performance on a platform that consists of two back-to-back connected inverters that emulate the WEC system.

wave energy conversion, impedance emulation, machi↗
DOE OSTI2012

Use of knowledge-based restraints in phenix.refine to improve macromolecular refinement at low resolution

Traditional methods for macromolecular refinement often have limited success at low resolution (3.0–3.5 Å or worse), producing models that score poorly on crystallographic and geometric validation criteria. To improve low-resolution refinement, knowledge from macromolecular chemistry and homology was used to add three new coordinate-restraint functions to the refinement program phenix.refine . Firstly, a `reference-model' method uses an identical or homologous higher resolution model to add restraints on torsion angles to the geometric target function. Secondly, automatic restraints for common secondary-structure elements in proteins and nucleic acids were implemented that can help to preserve the secondary-structure geometry, which is often distorted at low resolution. Lastly, we have implemented Ramachandran-based restraints on the backbone torsion angles. In this method, a φ,ψ term is added to the geometric target function to minimize a modified Ramachandran landscape that smoothly combines favorable peaks identified from nonredundant high-quality data with unfavorable peaks calculated using a clash-based pseudo-energy function. All three methods show improved MolProbity validation statistics, typically complemented by a lowered R free and a decreased gap between R work and R free .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Decentralized Filtering Adaptive Neural Network Control for Uncertain Switched Interconnected Nonlinear Systems

This article presents a novel decentralized filtering adaptive neural network control framework for uncertain switched interconnected nonlinear systems. Each subsystem has its own decentralized controller based on the established decentralized state predictor. For each subsystem, the nonlinear uncertainties are approximated by a Gaussian radial basis function (GRBF) neural network incorporated with a piecewise constant adaptive law, where the adaptive law will update adaptive parameters from the error dynamics between the host system and the decentralized state predictor by discarding the unknowns, whereas a decentralized filtering control law is derived to cancel both local and mismatched uncertainties from other subsystems, as well as achieve the local objective tracking of the host system. The achievement of global objective depends on the achievement of local objective for each subsystem. The matched uncertainties are canceled directly by adopting their opposite in the control signal, whereas a dynamic inversion of the system is required to eliminate the effect of the mismatched uncertainties on the output. By exploiting the average dwell time principle, the error bounds between the real system and the virtual reference system, which defines the best performance that can be achieved by the closed-loop system, are derived. A numerical example is given to illustrate the effectiveness of the decentralized filtering adaptive neural network control architecture by comparing against the model reference adaptive control (MRAC).

Average dwell time, decentralized, filtering adapt↗
DOE OSTI2022

Calculating adsorption isotherms using the two-phase thermodynamic method and molecular dynamics simulations

We describe the calculation of adsorption isotherms from molecular dynamics simulations based on the two-phase thermodynamic (2PT) model. The 2PT model developed for bulk fluid phases treats the gas-like components as hard spheres (HSs), which correctly recovers the limiting behaviors of unconfined fluids. We showed that this treatment, however, does not always lead to the correct zero-loading behavior in strongly confining systems. For methane adsorption into zeolite MFI, the HS reference state underestimates entropy by up to 20% at low loadings and leads to an order-of-magnitude increase in the adsorption onset pressure. To fix these issues, we propose the use of ideal adsorbed gas (IAG) as the gas reference model, the properties of which can be computed using the Widom insertion method on an empty adsorbent. We further describe three routes to compute adsorption isotherms from the Helmholtz free energy at different loadings. Comparing against established Monte Carlo (MC) methods, we found that the adsorption isotherms obtained using the IAG reference state agrees to within 40%, which corresponds to deviations of <5% in adsorption free energy. The isotherms calculated using the HS reference state underestimate the adsorption uptake at low to medium loadings in strongly confining systems, but its accuracy improves at higher loadings and as the pore size increases relative to the sorbate diameter. The methods described here provide an alternative approach for computing adsorption isotherms when MC simulations in an open ensemble are undesirable and enable a direct comparison of computed adsorption thermodynamics with experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Identifying Meteorological Drivers for Errors in Modeled Winds along the Northern California Coast

Abstract An accurate wind resource dataset is required for assessing the potential energy yield of floating offshore wind farms that are expected along the California outer continental shelf. The National Renewable Energy Laboratory has developed and disseminated an updated wind resource dataset offshore of California, using the Weather Research and Forecasting Model, referred to as the CA20 dataset. As compared to buoy lidar measurements that have become available recently, the CA20 dataset showed significant positive biases for 100-m wind speeds along Northern California wind energy lease areas. To investigate the meteorological drivers for the model errors, we first consider two 1-yr simulations run with two different planetary boundary layer (PBL) parameterizations: the Mellor–Yamada–Nakanishi–Niino (MYNN) PBL scheme (the chosen configuration in the CA20 dataset) and the Yonsei University PBL scheme (which significantly reduces the bias in modeled winds). By comparing the 1-yr simulations to the concurrent lidar buoy observations, we find that errors are larger with the MYNN PBL scheme in warm seasons. We then dive deeper into the analysis by running simulations for short-term (3-day) case studies to evaluate the sensitivity of initial/boundary condition forcings on model results. By analyzing the short-term simulations, we find that during synoptic-scale northerly flows driven by the North Pacific high and inland thermal low, a coastal warm bias in the MYNN simulation is mainly responsible for the modeled wind speed bias by altering the boundary layer thermodynamics. The results of our analysis will help guide the creation of an updated version of the CA20 dataset.

17 WIND ENERGY↗
DOE OSTI2016

DREISS: Using State-Space Models to Infer the Dynamics of Gene Expression Driven by External and Internal Regulatory Networks

Gene expression is controlled by the combinatorial effects of regulatory factors from different biological subsystems such as general transcription factors (TFs), cellular growth factors and microRNAs. A subsystem’s gene expression may be controlled by its internal regulatory factors, exclusively, or by external subsystems, or by both. It is thus useful to distinguish the degree to which a subsystem is regulated internally or externally–e.g., how non-conserved, species-specific TFs affect the expression of conserved, cross-species genes during evolution. We developed a computational method (DREISS, dreiss.gerteinlab.org) for analyzing the Dynamics of gene expression driven by Regulatory networks, both External and Internal based on State Space models. Given a subsystem, the “state” and “control” in the model refer to its own (internal) and another subsystem’s (external) gene expression levels. The state at a given time is determined by the state and control at a previous time. Because typical time-series data do not have enough samples to fully estimate the model’s parameters, DREISS uses dimensionality reduction, and identifies canonical temporal expression trajectories (e.g., degradation, growth and oscillation) representing the regulatory effects emanating from various subsystems. To demonstrate capabilities of DREISS, we study the regulatory effects of evolutionarily conserved vs. divergent TFs across distant species. In particular, we applied DREISS to the time-series gene expression datasets of C. elegans and D. melanogaster during their embryonic development. We analyzed the expression dynamics of the conserved, orthologous genes (orthologs), seeing the degree to which these can be accounted for by orthologous (internal) versus species-specific (external) TFs. We found that between two species, the orthologs have matched, internally driven expression patterns but very different externally driven ones. This is particularly true for genes with evolutionarily ancient functions (e.g. the ribosomal proteins), in contrast to those with more recently evolved functions (e.g., cell-cell communication). This suggests that despite striking morphological differences, some fundamental embryonic-developmental processes are still controlled by ancient regulatory systems.

Biochemistry & Molecular Biology↗
DOE OSTI2015

SU-E-I-80: Quantification of Respiratory and Cardiac Motion Effect in SPECT Acquisitions Using Anthropomorphic Models: A Monte Carlo Simulation Study

Purpose: The purpose of the present study was to quantify, evaluate the impact of cardiac and respiratory motion on clinical nuclear imaging protocols. Common SPECT and scintigraphic scans are studied using Monte Carlo (MC) simulations, comparing the resulted images with and without motion. Methods: Realistic simulations were executed using the GATE toolkit and the XCAT anthropomorphic phantom as a reference model for human anatomy. Three different radiopharmaceuticals based on 99mTc were studied, namely 99mTc-MDP, 99mTc—N—DBODC and 99mTc—DTPA-aerosol for bone, myocardium and lung scanning respectively. The resolution of the phantom was set to 3.5 mm{sup 3}. The impact of the motion on spatial resolution was quantified using a sphere with 3.5 mm diameter and 10 separate time frames, in the ECAM modeled SPECT scanner. Finally, respiratory motion impact on resolution and imaging of lung lesions was investigated. The MLEM algorithm was used for data reconstruction, while the literature derived biodistributions of the pharmaceuticals were used as activity maps in the simulations. Results: FWHM was extracted for a static and a moving sphere which was ∼23 cm away from the entrance of the SPECT head. The difference in the FWHM was 20% between the two simulations. Profiles in thorax were compared in the case of bone scintigraphy, showing displacement and blurring of the bones when respiratory motion was inserted in the simulation. Large discrepancies were noticed in the case of myocardium imaging when cardiac motion was incorporated during the SPECT acquisition. Finally the borders of the lungs are blurred when respiratory motion is included resulting to a dislocation of ∼2.5 cm. Conclusion: As we move to individualized imaging and therapy procedures, quantitative and qualitative imaging is of high importance in nuclear diagnosis. MC simulations combined with anthropomorphic digital phantoms can provide an accurate tool for applications like motion correction techniques’ optimization. This research has been co-funded by the European Union (European Social Fund) and Greek national resources under the framework of the ‘Archimedes III: Funding of Research Groups in TEI of Athens’ project of the ‘Education & Lifelong Learning’ Operational Programme.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Prescribing the aerosol effective radiative forcing in the Simple Cloud-Resolving E3SM Atmosphere Model v1

Aerosol effective radiative forcing critically influences climate projections but remains poorly constrained. Using the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM) v1 configuration, we assess the sensitivity of the radiative forcing due to anthropogenic aerosol changes using a simplified prescribed aerosol scheme (SPA) derived from E3SM v3. Nudged simulations at 3 and 12 km horizontal grid spacings reveal a more negative aerosol forcing than the reference 100 km E3SM v3 whence the SPA properties are derived. The resulting globally averaged aerosol forcing signal is largely due to aerosol–cloud interactions and exhibits little overall resolution sensitivity, while hints of resolution sensitivity appear regionally between the 3 and 12 km runs. While the default SPA scheme overestimates cloud droplet dependence on aerosols, parameterization adjustments in the activation process reconcile forcing estimates with the reference model. Our results demonstrate the ability to use a prescribed aerosol scheme to hold aerosol forcing to a desired strength across resolutions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

A Faster-Than-Real-Time Framework for Reliability-Oriented Simulation of PV Inverters

Physics-of-Failure (PoF) based reliability assessment for photovoltaic (PV) inverters requires long-duration electrical and electrothermal stress histories, yet generating such stress histories with high-fidelity switching models over year long mission profiles is computationally prohibitive. Conventional methods either sacrifice modeling fidelity for speed or require runtimes that are impractical for design iteration and uncertainty studies. To address this bottleneck, this paper presents a High-Performance Computing (HPC) based simulation frame work for faster-than-real-time reliability-oriented simulation. The proposed framework integrates the Average-to-Switching (A2S) method with parallel computing techniques to accelerate switching-level waveform reconstruction. We further introduce optimization strategies, including cluster merging and sensitivity based mission profile screening, to reduce the computational burden. Evaluated using real-world mission profile inputs and a MATLAB/Simulink switching-model reference, the framework reduces the simulation time for a one-year mission from an intractable multi-year duration to approximately 7.3 minutes while maintaining low waveform error. This acceleration provides a practical reliability-oriented simulation engine that can be coupled with component-specific aging models for subsequent PV inverter PoF assessment.

High-performance Computing↗
DOE OSTI2023

Time-warping invariant quantum recurrent neural networks via quantum-classical adaptive gating

Adaptive gating plays a key role in temporal data processing via classical recurrent neural networks (RNNs), as it facilitates retention of past information necessary to predict the future, providing a mechanism that preserves invariance to time warping transformations. This paper builds on quantum RNNs (QRNNs), a dynamic model with quantum memory, to introduce a novel class of temporal data processing quantum models that preserve invariance to time-warping transformations of the (classical) input-output sequences. The model, referred to as time warping-invariant QRNN (TWI-QRNN), augments a QRNN with a quantum–classical adaptive gating mechanism that chooses whether to apply a parameterized unitary transformation at each time step as a function of the past samples of the input sequence via a classical recurrent model. The TWI-QRNN model class is derived from first principles, and its capacity to successfully implement time-warping transformations is experimentally demonstrated on examples with classical or quantum dynamics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

On the use of genetic algorithm to optimize industrial assets lifecycle management under safety and budget constraints

The purpose of this paper is to describe the method and tool dedicated to optimize investments planning for industrial assets. These investments may either be preventive maintenance tasks, asset enhancements or logistic investments such as spare parts purchases. The two methodological points to investigate in such an issue are: 1. The measure of the profitability of a portfolio of investments 2. The selection and planning of an optimal set of investments 3. The measure of the risk of a portfolio of investments The measure of the profitability of a set of investments in the IPOP tool is synthesised in the Net Present Value indicator. The NPV is the sum of the differences of discounted cash flows (direct costs, forced outages...) between the situations with and without a given investment. These cash flows are calculated through a pseudo-Markov reliability model representing independently the components of the industrial asset and the spare parts inventories. The component model has been widely discussed over the years but the spare part model is a new one based on some approximations that will be discussed. This model, referred as the NPV function, takes for input an investments portfolio and gives its NPV. The second issue is to optimize the NPV. If all investments were independent, this optimization would be an easy calculation, unfortunately there are two sources of dependency. The first one is introduced by the spare part model, as if components are indeed independent in their reliability model, the fact that several components use the same inventory induces a dependency. The second dependency comes from economic, technical or logistic constraints, such as a global maintenance budget limit or a safety requirement limiting the residual risk of failure of a component or group of component, making the aggregation of individual optimum not necessary feasible. The algorithm used to solve such a difficult optimization problem is a genetic algorithm. After a description of the features of the software a test case is presented showing the influence of the optimization algorithm parameters on its efficiency to find an optimal investments planning. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

OC6 Phase III: Validation of Wind Turbine Aerodynamic Loading During Surge/Pitch Motion

The objective of Phase III of the Offshore Code Comparison Collaboration, Continued, with Correlation and unCertainty (OC6) project was to validate the accuracy of aerodynamic load predictions by offshore wind modeling tools for a floating offshore wind turbine as it experiences large surge-translational and pitch-rotational motion, as would occur during normal operation. The test data considered were generated at Politecnico di Milano – a wind tunnel with a robotic excitation system to emulate wave loading on the wind turbine. Testing was performed using a scaled version of the DTU 10-MW reference model, and motion was prescribed as harmonic oscillations in the surge and pitch directions, independently. A variety of models were examined in the project, performing a three-way validation between engineering-level tools, higher-fidelity tools, and measurement data from two wind tunnel experimental campaigns. The Load Cases (LC) considered in this testing are as follows: LC 1.X - Steady Wind LC 2.X - Unsteady Wind - Surge Motion LC 3.X - Unsteady Wind - Pitch Motion Details on the results of the OC6 Phase III campaign can be found in the following reference: Bergua R., et al. OC6 project Phase III: validation of the aerodynamic loading on a wind turbine rotor undergoing large motion caused by a floating support structure, Wind Energ. Sci., 8, 465–485, https://doi.org/10.5194/wes-8-465-2023, 2023.

17 WIND ENERGY↗
DOE OSTI2020

Filtering adaptive output feedback control for multivariable nonlinear systems with mismatched uncertainties and unmodeled dynamics

This article synthesizes a filtering adaptive output feedback controller for multivariable nonlinear systems with mismatched uncertainties and unmodeled dynamics. The multivariable nonlinear systems under consideration have both matched and mismatched uncertainties, which satisfy the semiglobal Lipschitz condition. The unmodeled dynamics are bounded-input bounded-output stable. By adopting an estimation/cancellation strategy, a piecewise constant adaptive law drives the estimation error to zero at every time instant, which yields the adaptive parameters; a disturbance rejection control law is designed to compensate the nonlinear uncertainties within the bandwidth of low-pass filters. The matched uncertainties are cancelled directly by adopting their opposite in the control signal, while a dynamic inversion of the system is required to eliminate the effect of the mismatched uncertainties on the output. A feedforward control law is designed to track a given command. Since the virtual reference system defines the best performance that can be achieved by the closed-loop system, the uniform performance bounds are derived for the states and control signals via comparison. Both numerical and practical examples are provided to illustrate the effectiveness of the proposed filtering adaptive output feedback control architecture, comparisons with the model reference adaptive control demonstrates the superiority of the proposed control method.

filtering adaptive control, mismatched uncertainit↗
DOE OSTI2024

Yet Another Discriminant Analysis (YADA): A Probabilistic Model for Machine Learning Applications

This paper presents a probabilistic model for various machine learning (ML) applications. While deep learning (DL) has produced state-of-the-art results in many domains, DL models are complex and over-parameterized, which leads to high uncertainty about what the model has learned, as well as its decision process. Further, DL models are not probabilistic, making reasoning about their output challenging. In contrast, the proposed model, referred to as Yet Another Discriminate Analysis(YADA), is less complex than other methods, is based on a mathematically rigorous foundation, and can be utilized for a wide variety of ML tasks including classification, explainability, and uncertainty quantification. YADA is thus competitive in most cases with many state-of-the-art DL models. Ideally, a probabilistic model would represent the full joint probability distribution of its features, but doing so is often computationally expensive and intractable. Hence, many probabilistic models assume that the features are either normally distributed, mutually independent, or both, which can severely limit their performance. YADA is an intermediate model that (1) captures the marginal distributions of each variable and the pairwise correlations between variables and (2) explicitly maps features to the space of multivariate Gaussian variables. Numerous mathematical properties of the YADA model can be derived, thereby improving the theoretic underpinnings of ML. Validation of the model can be statistically verified on new or held-out data using native properties of YADA. However, there are some engineering and practical challenges that we enumerate to make YADA more useful.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Solvation Energy of Ions in a Stockmayer Fluid

We calculate the solvation energy of monovalent and divalent ions in various liquids with coarse-grained molecular dynamics simulations. Our theory treats the solvent as a Stockmayer fluid, which accounts for the intrinsic dipole moment of molecules and the rotational dynamics of the dipoles. Despite the simplicity of the model, we obtain qualitative agreement between the simulations and experimental data for the free energy and enthalpy of ion solvation, which indicates that the primary contribution to the solvation energy arises mainly from the first and possibly second solvation shells near the ions. Our results suggest that a Stockmayer fluid can serve as a reference model that enables direct comparison between theory and experiment and may be invoked to scale up electrostatic interactions from the atomic to the molecular length scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

The effect of urban design parameters on the local microclimate

Two-dimensional steady-state simulations have been performed using the standard k-e turbulence model coupled with the heat transfer models available in the CFD software FLUENT 6.1, in order to examine the impact of radiation on the Urban Heat Island phenomenon. Specifically, the impact of radiation in three typical urban areas of Cyprus during the summer period is examined. The first geometry considered represents a typical suburban area and is termed as the reference geometry. The second geometry represents an area at the centre of a town with higher buildings and relatively narrower roads. The third geometry, on the other hand, describes a suburban area with wider roads and larger houses than the reference model. Computed values for air temperature in the urban street canyon have indicated that the increase in temperature associated with radiative heat transfer can be reduced by optimising the canyon geometry and, ultimately, help to mitigate the human thermal discomfort. The present study has also revealed that the selection of construction materials can be optimised to offer further reductions in the air temperature of the urban environment. It can be concluded that the combined effect of these remedies can lead to reductions in the energy consumption for building air-conditioning over the summer period.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗