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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Ten questions concerning reinforcement learning for building energy management

As buildings account for approximately 40% of global energy consumption and associated greenhouse gas emissions, their role in decarbonizing the power grid is crucial. The increased integration of variable energy sources, such as renewables, introduces uncertainties and unprecedented flexibilities, necessitating buildings to adapt their energy demand to enhance grid resiliency. Consequently, buildings must transition from passive energy consumers to active grid assets, providing demand flexibility and energy elasticity while maintaining occupant comfort and health. This fundamental shift demands advanced optimal control methods to manage escalating energy demand and avert power outages. Reinforcement learning (RL) emerges as a promising method to address these challenges. Here, in this paper, we explore ten questions related to the application of RL in buildings, specifically targeting flexible energy management. We consider the growing availability of data, advancements in machine learning algorithms, open-source tools, and the practical deployment aspects associated with software and hardware requirements. Our objective is to deliver a comprehensive introduction to RL, present an overview of existing research and accomplishments, underscore the challenges and opportunities, and propose potential future research directions to expedite the adoption of RL for building energy management.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Effect of graphite nanoplatelets and carbon nanofibers on rheology, hydration, shrinkage, mechanical properties, and microstructure of UHPC

This study evaluates the effects of two types of graphite nanoplatelet (GNP-C and GNP-M) and one type of carbon nanofiber (CNF) on rheological properties, hydration kinetics, autogenous shrinkage, and pore structure of ultra-high-performance concrete (UHPC). The dispersion method was optimized to secure uniform dispersion of the nanomaterials in the UHPC. The plastic viscosity decreased with the nanomaterials content as the content was increased from 0 to 0.05%. As the nanomaterials content increased from 0 to 0.3%, the duration of induction period was extended by the addition of CNF, but shortened by use of GNP-C or GNP-M; cumulative hydration heat release was increased by introduction of nanomaterials; the autogenous shrinkage of UHPC with CNF, GNP-C, and GNP-M was increased by 30%, 20%, and 20%, respectively. The use of 0.3% CNFs reduced the total porosity of the UHPC by approximately 35%, indicating that the presence of CNFs refined the microstructure of UHPC.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Model predictive control for optimal dispatch of chillers and thermal energy storage tank in airports

Cost of energy consumption is one of the biggest operational cost for airports, and it is increasing from time to time as airports expand to support growing number of passengers. Various factors affect the energy consumption including efficiency of airport Heating Ventilation and Air conditioning (HVAC) systems, which in turn depends on the efficiency of individual subsystems. Here, in this paper, we present an optimal scheduling method for the central plant system at Dallas Fort Worth airport, involving chillers, pumps, and a thermal energy storage (TES) system. A model predictive control (MPC) problem is formulated to minimize both energy and demand charge costs while satisfying the cooling needs of the airport. The proposed Mixed-Integer Nonlinear Programming (MINLP) formulation includes performance curve based models for chillers and pumps and a simplified state of charge model for TES. The formulation also includes predictions of cooling load and chilled water return temperature. Simulation results for a month in summer show savings around 10% compared to the baseline. Initial recommendations based on insights from simulation results to the manual operation procedures resulted in significant savings. Field test results show a 7% chiller efficiency improvement.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Assumed non-persistent environmental chemicals in human adipose tissue; matrix stability and correlation with levels measured in urine and serum

The aim of this study was to (1) optimize a method for the measurement of parabens and phenols in adipose tissue, (2) evaluate the stability of chemical residues in adipose tissue samples, and (3) study correlations of these compounds in urine, serum, and adipose tissue. Samples were obtained from adults undergoing trauma surgery. Nine phenols and seven parabens were determined by isotope diluted TurboFlow-LC-MS/MS. The analytical method showed good accuracy and precision. Limits of detection (LOD) for parabens and phenols ranged from 0.05 to 1.83 ng/g tissue. Good recovery rates were found, even when biological samples remained defrosted up to 24 h. Benzophenone-3 (BP-3; range of values: 70% of adipose tissue samples, while bisphenol-A (BPA; 40% of adipose tissue samples. In general, levels were similar between adipose tissue and serum, while a correlation between adipose tissue and urine was only found for BP-3. In conclusion, adipose tissue samples in this study were found to contain environmental chemicals considered to be non-persistent, whose levels were weakly or not at all correlated with the urine burden. Therefore, adipose tissue may potentially provide additional information to that obtained from other biological matrices. Further investigations are warranted to explore whether adipose tissue might be a suitable matrix for assessment of the consequences for human health of mid/long-term exposure to these chemicals. - Highlights: • We analyzed levels of endocrine disruptors in adipose tissue, serum and urine. • We found BPA, TCS, BP-3, 2-PP and MeP in >40% of the adipose tissue samples. • Adipose tissue levels of npEDCs did not correlate with those in urine or serum. • Adipose tissue levels may have a different biological meaning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Oxygen enrichment combustion to reduce fossil energy consumption and emissions in hot rolling steel production

The reheating furnace operation in the hot mill is natural gas- and electricity-intensive. Oxygen enrichment combustion for reheating furnaces has been proposed to curb and replace natural gas use. In this study, heat transfer in steel slabs in the combustion environment of a push-type reheating furnace was simulated using a computational fluid dynamics (CFD) model. Two oxygen enrichment methods that optimized for performance were selected— a medium oxygen enrichment (MOE) case and an oxy-fuel (OF) case. A life cycle analysis (LCA) characterized the energy and emission profiles of an integrated iron and steel manufacturing process using the two oxygen enrichment cases for the hot mill. These conditions were evaluated for energy use and carbon intensity and compared with a baseline case. Results show that with oxygen enrichment, natural gas consumption can decrease by 19.6%–26.8%, total energy consumption (natural gas and electricity) can decrease by 15.1%–20.7% in the hot mill. Emissions of greenhouse gases can decrease by 11.1%–15.2% in the two optimized cases with 14%–27% reductions in regulated criteria pollutants (nitrogen oxides, carbon monoxide, particulate matter, volatile organic compounds, black carbon, organic carbon, and volatile organic carbons). There is a tradeoff between reducing natural gas consumption and increasing electricity demand from a life cycle perspective. Although the OF case resulted in higher energy- and emissions-related benefits, the MOE case showed the more desirable heat flux uniformity, which is key to maintaining product quality. The analysis suggests that oxygen enrichment in the reheating furnace process can have a significant impact on hot mill environmental performance and become a contributing factor in transitioning to low-carbon steel manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2016

A 4DCT imaging-based breathing lung model with relative hysteresis

To reproduce realistic airway motion and airflow, the authors developed a deforming lung computational fluid dynamics (CFD) model based on four-dimensional (4D, space and time) dynamic computed tomography (CT) images. A total of 13 time points within controlled tidal volume respiration were used to account for realistic and irregular lung motion in human volunteers. Because of the irregular motion of 4DCT-based airways, we identified an optimal interpolation method for airway surface deformation during respiration, and implemented a computational solid mechanics-based moving mesh algorithm to produce smooth deforming airway mesh. In addition, we developed physiologically realistic airflow boundary conditions for both models based on multiple images and a single image. Furthermore, we examined simplified models based on one or two dynamic or static images. By comparing these simplified models with the model based on 13 dynamic images, we investigated the effects of relative hysteresis of lung structure with respect to lung volume, lung deformation, and imaging methods, i.e., dynamic vs. static scans, on CFD-predicted pressure drop. The effect of imaging method on pressure drop was 24 percentage points due to the differences in airflow distribution and airway geometry. - Highlights: • We developed a breathing human lung CFD model based on 4D-dynamic CT images. • The 4DCT-based breathing lung model is able to capture lung relative hysteresis. • A new boundary condition for lung model based on one static CT image was proposed. • The difference between lung models based on 4D and static CT images was quantified.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Scalable preconditioning for the stabilized contact mechanics problem

We present a family of preconditioning strategies for the contact problem in fractured and faulted porous media. We combine low-order continuous finite elements to simulate the bulk deformation with piecewise constant Lagrange multipliers to impose the frictional contact constraints. This formulation is not uniformly inf-sup stable and requires stabilization. We improve previous work by Franceschini et al. (2020) by introducing a novel jump stabilization technique that requires only local geometrical and mechanical properties. We then design scalable preconditioning strategies that take advantage of the block structure of the Jacobian matrix using a physics-based partitioning of the unknowns by field type, namely displacement and Lagrange multipliers. The key to the success of the proposed preconditioners is a pseudo-Schur complement obtained by eliminating the Lagrange multiplier degrees of freedom, which can then be efficiently solved using an optimal multigrid method. Numerical results, including complex real-world problems, are presented to illustrate theoretical properties, scalability and robustness of the preconditioner. A comparison with other approaches available in the literature is also provided.

58 GEOSCIENCES↗
DOE OSTI2023

Adjoint DSMC for nonlinear spatially-homogeneous Boltzmann equation with a general collision model

We derive an adjoint method for the Direct Simulation Monte Carlo (DSMC) method for the spatially homogeneous Boltzmann equation with a general collision law. This generalizes our previous results in Caflisch et al., which was restricted to the case of Maxwell molecules, for which the collision rate is constant. The main difficulty in generalizing the previous results is that a rejection sampling step is required in the DSMC algorithm in order to handle the variable collision rate. We find a new term corresponding to the so-called score function in the adjoint equation and a new adjoint Jacobian matrix capturing the dependence of the collision parameter on the velocities. The new formula works for a much more general class of collision models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Conjunctive management of surface and groundwater resources under projected future climate change scenarios

Our study introduces a mixed integer linear fractional programming (MILFP) method to optimize conjunctive use of future surface water and groundwater resources under projected climate change scenarios. The conjunctive management model maximizes the ratio of groundwater usage to reservoir water usage. Future inflows to the reservoirs were estimated from the future runoffs projected through hydroclimate modeling considering the Variable Infiltration Capacity model, and 11 sets of downscaled Coupled Model Intercomparison Project phase 5 global climate model projections. Bayesian model averaging was adopted to quantify uncertainty in future runoff projections and reservoir inflow projections due to uncertain future climate projections. Optimized conjunctive management solutions were investigated for a water supply network in northern Louisiana which includes the Sparta aquifer. Runoff projections under climate change scenarios indicate that runoff will likely decrease in winter and increase in other seasons. Ultimately, results from the developed conjunctive management model with MILFP indicate that the future reservoir water, even at 2.5% low inflow cumulative probability level, could counterbalance groundwater pumping reduction to satisfy demands while improving the Sparta aquifer through conditional groundwater head constraint.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Efficient screening of rare large pit anomalies on polished surfaces using a minimalist sampling scheme

Lawrence Livermore National Laboratory (LLNL) has made significant strides in generating clean energy through its inertial confinement fusion (ICF) experiments. These experiments rely on high-density carbon (HDC) coated shells to encapsulate the fusion fuel. The success of these experiments is heavily dependent on the surface quality of these shells, as even minor imperfections, such as deep pits, can negatively impact fusion yield. Ensuring the required smoothness involves an extensive surface-finishing process that spans approximately 20 stages, making it both time-intensive and resource-demanding. A critical challenge in this process is the need for high-resolution scans to detect rare deep pits, which can be costly and impractical if performed on every shell. This highlights the necessity of developing more efficient scanning methods to optimize time and cost without compromising accuracy. To address these challenges, we introduce a novel approach that employs the multivariate Dvoretzky–Kiefer–Wolfowitz (DKW) inequality to provide a probabilistic upper bound on the error in estimating pit distribution characteristics via a Kernel Density Estimator (KDE). This error bound enables efficient and reliable estimation of pit distribution characteristics at a specified statistical confidence level using a minimal number of surface scans. The integrated DKW-KDE approach was validated through surface-finishing experiments across two batches of HDC-coated shells, demonstrating consistent and robust performance across multiple stages of the surface-finishing experiments. The validation studies suggest that the integrated DKW-KDE approach achieves comparable accuracy in estimating the risk of deleterious large pits with six scans, thus conserving time and resources. Further evaluations show that performance remains consistent across batches and over multiple polishing stages. In conclusion, based on these findings, one can leverage the minimal-scan insights to strategically improve the bottleneck inspection process, thus enhancing the productivity and quality of shell polishing and similar challenging manufacturing processes.

Inertial confinement fusion↗
DOE OSTI2019

Effect of epitaxial strain on the optical properties of NaOsO 3

We study the electronic and optical properties of NaOsO 3 under epitaxial strain using first principles methods. Structural optimization shows important changes with strain in the structural parameters such as the Os O bond lengths and the octahedral rotation angles. The key change in the electronic structure is the band gap, which increases with compressive epitaxial strain and decreases with tensile strain. The computed optical absorption coefficient is more or less isotropic for the unstrained structure for light polarization along the three crystallographic directions, but for the strained structure, it is enhanced if the light polarization is along a compressed crystallographic direction due to strain. This is explained in terms of the admixture of Os ( p ) orbitals with the Os ( d ) states that form the valence and the conduction bands.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Structural manipulation approaches towards enhanced sodium ionic conductivity in Na-rich antiperovskites

High-performance solid electrolytes are critical for realizing all-solid-state batteries with enhance safety and cycling efficiency. However, currently available candidates (sulfides and the NASICON-typ ceramics) still suffer from drawbacks such as inflammability, high-cost and unfavorable machinability Here we present the structural manipulation approaches to improve the sodium ionic conductivity in series of affordable Na-rich antiperovskites. Experimentally, the whole solid solutions of Na 3 OX (X ¼ Cl Br, I) are synthesized via a facile and timesaving route from the cheapest raw materials (Na, NaOH an NaX). The materials are nonflammable, suitable for thermoplastic processing due to low melting temperature (<300° C) without decomposing. Notably, owing to the flexibility of perovskite-type structure it's feasible to control the local structure features by means of size-mismatch substitution an unequivalent-doping for a favorable sodium ionic diffusion pathway. Enhancement of sodium ioni conductivity by 2 magnitudes is demonstrated by these chemical tuning methods. The optimized sodiu ionic conductivity in Na 2.9 Sr 0.05 OBr 0.6 I 0.4 bulk samples reaches 1.9 10 - 3 S/cm at 200° C and even highe at elevated temperature. Here, we believe further chemical tuning efforts on Na-rich antiperovskites wil promote their performance greatly for practical all-solid state battery applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

On optimal control of hybrid dynamical systems using complementarity constraints

Optimal control for switch-based dynamical systems is a challenging problem in the process control literature. In this study, we model these systems as hybrid dynamical systems with finite number of unknown switching points and reformulate them using non-smooth and non-convex complementarity constraints as a mathematical program with complementarity constraints (MPCC). We utilize a moving finite element based strategy to discretize the differential equation system to accurately locate the unknown switching points at the finite element boundary and achieve high-order accuracy at intermediate non-collocation points. We propose a globalization approach to solve the discretized MPCC problem using a mixed NLP/MILP-based strategy to converge to a non-spurious first-order optimal solution. The method is tested on three dynamic optimization examples, including a gas–liquid tank model and an optimal control problem with a sliding mode solution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Secondary carbides in high chromium cast irons: An alternative approach to their morphological and spatial distribution characterization

Highlights: • Systematic characterization of second phase particles by combining a variety of techniques • Comparison of morphological parameters obtained from SEM, BSE, etching+CLSM and EBSD • Quantitative analysis and degree of distribution of secondary carbides • Particle size, distribution and morphology from image analysis of CLSM, SEM and EBS images - Abstract: Secondary carbides precipitated in high chromium cast irons during thermal treatments were characterized by means of different characterization techniques, including scanning electron microscopy, energy dispersive X-ray spectroscopy, electron backscattered diffraction and a combination of chemical etching with confocal scanning laser microscopy. This set of techniques provides a full morphological, chemical and crystallographic description of the analysed phases. This work evaluated different methods for optimizing the image acquisition for a further image analysis (IA) based on the threshold binarization. Finally, the carbide size, distribution and morphology were determined after IA of the images acquired by aforementioned characterization techniques. Although the different techniques report some dispersion in the value for the average particle size, the particle inter-spacing and aspect ratio meet within the error value. The proposed characterization methodology provides statistically reliable data for a further evaluation of related physical properties in composites.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Site-specific plan-view (S)TEM sample preparation from thin films using a dual-beam FIB-SEM

To fully evaluate the atomic structure, and associated properties of materials using transmission electron microscopy, examination of samples from three non-collinear orientations is needed. This is particularly challenging for thin films and nanoscale devices built on substrates due to limitations with plan-view sample preparation. In this work, a new method for preparation of high-quality, site-specific, plan-view TEM samples from thin-films grown on substrates, is presented and discussed. Here, it is based on using a dual-beam focused ion beam scanning electron microscope (FIB-SEM) system. To demonstrate the method, the samples were prepared from thin films of perovskite oxide BaSnO 3 grown on a SrTiO 3 substrate and metal oxide IrO 2 on a TiO 2 substrate, ranging from 20–80 nm in thicknesses using molecular beam epitaxy. While the method is optimized for the thin films, it can be extended to other site-specific plan-view samples and devices build on wafers. Aberration-corrected STEM was used to evaluate the quality of the samples and their applicability for atomic-resolution imaging and analysis.

BaSnO3↗
DOE OSTI2019

Side Chain and Solvent Direction of Film Morphology in Small-Molecule Organic Solar Materials

Film morphology control is essential to materials development for efficient organic solar cells (OSCs). Unlocking methods to optimize the film morphology for materials without changing the fundamental electronic characteristics can enable previously unacceptable materials to achieve high performance. In this work, a series of acceptor-donor-acceptor (ADA) small molecule p-type OSC semiconductors having benzo[1,2-b:6,5-b0]dithiophene (bBDT) donor units and thiophene capped diketopyrrolopyrrole (TDPP) acceptor units are examined where the sole molecular design variation is in the electronically inactive side chains. Four bBDT(TDPP) 2 compounds with all possible combinations of either 2-ethelhexyl (EH), or 3,7-dimtheyloctyl (DMO) side chains on the bBDT core and TDPP units are discussed. When processed from a chloroform (CF)-only solution, blend films of the molecules with the PC 71 BM electron acceptor exhibit similar thin film properties and photovoltaic performance, regardless of the side chain composition. However, when the additive 1,8-diiodooctane (DIO) is included in the processing solution, the morphological properties and OSC performance diverge dramatically, with the side chain variations now dictating the film morphology, resulting in a >400% spread in power conversion efficiency (PCE). Donor molecules with a mixed side chain motif having the larger DMO side chain on the bBDT core unit deliver the best performance owing to greater donor:acceptor phase intermixing while maintaining contiguous and efficient charge transport pathways. Using in situ GIWAXS during spin-coating, it is shown that DIO extends crystallization times, thereby promoting more thermodynamically driven structures where the side chain compositions have greater impact. Lastly, general guidelines are presented for achieving morphological optimization via combined side chain engineering and processing additives.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Ditechnetium heptoxide revisited: Solid-state, gas-phase, and theoretical studies

Here, ditechnetium heptoxide was synthesized from the oxidation of TcO 2 with O 2 at 450 °C and characterized by single crystal X-ray diffraction (SCXRD), electron impact mass spectrometry (EI-MS) and theoretical methods. Refinement of the structure at 100 K indicates that Tc 2 O 7 crystallizes as a molecular solid in the orthorhombic space group Pbca (a = 7.312(3) Å, b = 5.562(2) Å, c = 13.707(5) Å, V = 557.5(3) Å 3 ). The Tc 2 O 7 molecule can be described as corner-sharing TcO4 tetrahedra (Tc---Tc = 3.698(1) Å and Tc-O Bri -Tc = 180.0°). The EI-MS spectrum of Tc 2 O 7 consists of both mononuclear and dinuclear species. The main dinuclear species in the gas-phase are Tc 2 O 7 (100%) and Tc 2 O 5 (56%), while the main mononuclear species are TcO 3 (33.9%) and TcO 2 (42.8%). The difference in the relative intensities of the M 2 O 5 (M = Tc, Re) fragments (1.7% for Re) indicate that these Group 7 elements exhibit different gas phase chemistry. The solid-state structure of Tc 2 O 7 was investigated by density functional theory (DFT) methods. The optimized structure of the Tc 2 O 7 molecule is in good agreement with the experimental one. Simulations indicate that the more favorable geometry for the Tc 2 O 7 molecule in the gas-phase is bent (Tc-O Bri -Tc = 156.5°), while linear (Tc-O Bri -Tc = 180.0°) is favored in the solid state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗