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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 1,045 records · Page 58

Experimental Demonstration of Alkalinity Concentration Swing for Direct Air Capture of CO 2

This work constitutes the first lab-scale experimental demonstration of the alkalinity concentration swing (ACS) for direct air capture (DAC) of CO 2 . ACS can be implemented by taking a dilute alkaline solution that has contacted ambient air, and then concentrating it using commercially available desalination technologies. The more concentrated solution has a higher partial pressure of CO 2 relative to the initial solution, allowing the CO 2 to be separated and stored. The ACS approach is based on simple thermodynamics but had never been verified experimentally in terms of extracting CO 2 from air until now. We tested two distinct methods for concentrating the alkaline liquid: reverse osmosis (RO) and capacitive deionization (CDI). We found that to complete the DAC cycle in feasible operating conditions, a bicarbonate-enrichment step needed to be introduced, which selects on bicarbonate ions over carbonate ions. Two approaches for CO 2 extraction to measure the CO 2 yield per amount of water processed by the ACS method were tested. The energy required per amount of CO 2 captured was quantified. We further applied an energy model to study how operating the ACS cycle under different conditions would affect energy requirements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Multi-Mission Maximum Likelihood framework (3ML)

The age of multi-wavelength and multi-messenger astronomy has arrived and with it, new tools are needed to analyze data from multiple instruments properly and with ease. The Multi-Mission Maximum Likelihood framework (3ML) provides this functionality via the novel use of instrument plugins which allow for every instrument’s unique data to be treated independently with an appropriate likelihood. Under the 3ML framework, users can design plugins that handle instrument specific data routines transparently in the background. When multiple instruments are used together, their independent likelihoods are treated under a common minimization or Bayesian sampling framework. 3ML provides a multitude of minimization algorithm for maximum likelihood estimation (MLE) as well as several popular Bayesian posterior samplers. The entire framework is provided via a modern Python interface providing the user with a modern and easily transportable analysis framework well suited for modern astronomy. New models can be added easily. It is also possible to perform time-energy modeling. We present the framework and its main functionalities.

79 ASTRONOMY AND ASTROPHYSICS↗

A simulation model for wind energy storage systems. Volume 1: Technical report

A comprehensive computer program for the modeling of wind energy and storage systems utilizing any combination of five types of storage (pumped hydro, battery, thermal, flywheel and pneumatic) was developed. The level of detail of Simulation Model for Wind Energy Storage (SIMWEST) is consistent with a role of evaluating the economic feasibility as well as the general performance of wind energy systems. The software package consists of two basic programs and a library of system, environmental, and load components. The first program is a precompiler which generates computer models (in FORTRAN) of complex wind source storage application systems, from user specifications using the respective library components. The second program provides the techno-economic system analysis with the respective I/O, the integration of systems dynamics, and the iteration for conveyance of variables. SIMWEST program, as described, runs on the UNIVAC 1100 series computers.

Warren, A. W.↗

Energy and Energy Cost Savings Analysis of the 2015 IECC for Commercial Buildings

As required by statute (42 USC 6833), DOE recently issued a determination that ANSI/ASHRAE/IES Standard 90.1-2013 would achieve greater energy efficiency in buildings subject to the code compared to the 2010 edition of the standard. Pacific Northwest National Laboratory (PNNL) conducted an energy savings analysis for Standard 90.1-2013 in support of its determination . While Standard 90.1 is the model energy standard for commercial and multi-family residential buildings over three floors (42 USC 6833), many states have historically adopted the International Energy Conservation Code (IECC) for both residential and commercial buildings. This report provides an assessment as to whether buildings constructed to the commercial energy efficiency provisions of the 2015 IECC would save energy and energy costs as compared to the 2012 IECC. PNNL also compared the energy performance of the 2015 IECC with the corresponding Standard 90.1-2013. The goal of this analysis is to help states and local jurisdictions make informed decisions regarding model code adoption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Energy and Energy Cost Savings Analysis of the 2015 IECC for Commercial Buildings (Rev.1)

As required by statute (42 USC 6833), DOE recently issued a determination that ANSI/ASHRAE/IES Standard 90.1-2013 would achieve greater energy efficiency in buildings subject to the code compared to the 2010 edition of the standard. Pacific Northwest National Laboratory (PNNL) conducted an energy savings analysis for Standard 90.1-2013 in support of its determination. While Standard 90.1 is the model energy standard for commercial and multi-family residential buildings over three floors (42 USC 6833), many states have historically adopted the International Energy Conservation Code (IECC) for both residential and commercial buildings. This report provides an assessment as to whether buildings constructed to the commercial energy efficiency provisions of the 2015 IECC would save energy and energy costs as compared to the 2012 IECC. PNNL also compared the energy performance of the 2015 IECC with the corresponding Standard 90.1-2013. The goal of this analysis is to help states and local jurisdictions make informed decisions regarding model code adoption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Modeling the Laser Energy Supply in a Gas Flow

The results of numerical modeling of laser energy supply in a supersonic flow are presented. In contrast to the common approach, in the new calculation model, not only the absorbed power is taken into account, but also the plasma breakdown impulse in the domain of emission focusing does. The value of the impulse is determined using the model of radiation absorption behind the front of the laser-supported detonation wave. An analysis of the results is presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Decreasing Proton Single Event Effects in CubeSats with Shielding

Shields-1, NORAD ID 43850,has been operating in polar low earth orbit since December 2018. The shielding has resulted in a lower total ionizing dose over time than typical aluminum thin-walled CubeSat structures. The reduced ionizing dosage caused by Shields-1 increases the reliability of commercial parts and reduces internal charging. Furthermore, the Shields-1 shielding reduces the ionizing particle fluence inside the spacecraft that contributes to the ionizing dose. NOVICE Sigma shielding software, using the (Aerospace Proton) AP8 –(Aerospace Electron) AE8 solar minimum trapped belt environment for a 1-year mission, estimates a 21.3 g/cm2 aluminum effective shielding for the Shields-1 electronics enclosure. This high areal density reduces not only the total number of energetic protons, but also reduces the number of ionizing particles over all modeled energies from the estimated shielded fluence for a 1-year mission. NOVICE Adjoint CAD modeling of the Shields-1 structure, with the detector located within the electronics enclosure, estimates that the total number of particles is reduced from 2.20x 10exp9 protons/cm2 to 1.52x 10exp8 protons/cm2, which represents 6.90% of the remaining particles(figure 1). By slowing down approximations of the integral proton fluence, a minimum proton threshold is estimated at 151 MeV. In comparison, a 0.204-cm aluminum thin-walled 3-unit (U) structure, with a 0.907 g/cm2 effective shielding, has 25.0% remaining particles and a minimum proton threshold of 36.2 MeV(figure 1). Proton energies that contribute to single event effects in radiation tolerant or higher semiconductor hardness are typically 100 MeV and higher. The Shields-1 electronics enclosure is estimated to attenuate energies: 100 MeV by 76.5%, 200 MeV by 61.7%, and 500 MeV by 63.0%(figure 2), when comparing the space environment proton differential fluence with the shielded differential fluence. The aluminum thin-walled structure is estimated to attenuate proton energies: 100 MeV by 13.7%, 200 MeV by 12.4%, and 500 MeV by 12.6%(figure 2), which are lower than for the Shields-1 electronics enclosure. The significant differences in attenuation between the Shields-1 electronics enclosure and aluminum thin-walled 3U structure show the additional utility of increasing shielding effectiveness for reducing the numbers of energetic protons that contribute to single event effects.

Larry Thomsen↗

Machine learning pipeline to predict defect behavior in metallic alloy systems

The interaction between defect and solute atoms is critical to the thermodynamic and kinetic behavior of metallic alloys under exposure to high-energy radiation, causing irradiation damage in materials. Radiation can generate non-equilibrium concentrations of point defects such as vacancies and interstitials. The excess point defects not only accelerate diffusional processes such as precipitation that cause radiation embrittlement, but also change the pathway of phase transformations, including nucleation processes. Understanding these defect behaviors is complicated by the challenge and complexity of addressing each possible local and discrete distribution of environments and chemical interactions around targeted defects-solute or solute-solute complexes. To resolve the challenge, machine learning regression techniques have emerged as powerful tools that can train and construct an energy model to accurately describe the chemical interactions of solutes and defects. In Fiscal Year 2022, the work focused on the workflow development and demonstration using machine learning regression, density functional theory, cluster expansion, and Monte Carlo simulation to predict the effects of ternary solute elements (e.g., aluminum and molybdenum) and point defects on the Cr-rich $\alpha^{\prime}$ precipitation in multicomponent FeCr model alloys. The computational outcomes include the prediction of the ternary phase diagram, vacancy formation energy for different compositions, and the effect of vacancies on the nucleation of Cr-rich clusters. The simulations predict a pronounced change of Cr solubility in bcc Fe by the addition of Al and the rejection of Al atoms from $\alpha^{\prime}$ precipitates. Additionally, the simulations show the formation of Cr-vacancy clusters as the initial nuclei for stable nucleation and growth of $\alpha^{\prime}$ particles. The results demonstrate important outcomes and applications of using machine learning pipeline to study model or commercial alloys with multicomponent solute species and point defects.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Full Modeling and parameter compression methods in configuration space for DESI 2024 and beyond

In the contemporary era of high-precision spectroscopic surveys, led by projects like DESI, there is an increasing demand for optimizing the extraction of cosmological information from clustering data. This work conducts a thorough comparison of various methodologies for modeling the full shape of the two-point statistics in configuration space. We investigate the performance of both direct fits (Full Modeling) and the parameter compression approaches (ShapeFit and Standard). We utilize the ABACUS-SUMMIT simulations, tailored to exceed DESI's precision requirements. Particularly, we fit the two-point statistics of three distinct tracers (LRG, ELG, and QSO), by employing a Gaussian Streaming Model in tandem with Convolution Lagrangian Perturbation Theory and Effective Field Theory. We explore methodological setup variations, including the range of scales, the set of galaxy bias parameters, the inclusion of the hexadecapole, as well as model extensions encompassing varying ns and allowing for w 0 w a CDM dark energy model. Throughout these varied explorations, while precision levels fluctuate and certain configurations exhibit tighter parameter constraints, our pipeline consistently recovers the parameter values of the mocks within 1σ in all cases for a 1-year DESI volume. Additionally, we compare the performance of configuration space analysis with its Fourier space counterpart using three models: PyBird, FOLPS and velocileptors, presented in companion papers. We find good agreement with the results from all these models.

79 ASTRONOMY AND ASTROPHYSICS↗

The exploration of nonlinear elasticity and its efficient parameterization for crystalline materials

Conventional approaches to analyzing the very large coherency strains that can occur during solid-state phase transformations are founded in linear elasticity and rely on infinitesimal strain metrics. Despite this, there are many technologically important examples where misfit strains of multi-phase mixtures are very large during their synthesis and/or application. Here in this paper, we present a framework for constructing strain-energy expressions and stress-strain relationships beyond the linear-elastic limit for crystalline solids. This approach utilizes group theoretical concepts to minimize both the number of free parameters in the strain-energy expression and amount of first-principles training data required to parameterize strain-energy models that are invariant to all crystal symmetries. Within this framework, the strain-energy and elastic stiffness can be described to high accuracy in terms of a set of conventional symmetry-adapted finite strain metrics that we define independent of crystal symmetry. As an illustration, we use first-principles electronic structure data to parameterize strain energy polynomials and employ them to explore the strain- energy surfaces of HCP Zr and Mg, as well as several important Zr-H and Mg-Nd phases that are known to precipitate coherently within the HCP matrices of Zr and Mg.

36 MATERIALS SCIENCE↗

A perturbative approach to the redshift space correlation function: beyond the Standard Model

We extend our previous redshift space power spectrum code to the redshift space correlation function. Here we focus on the Gaussian Streaming Model (GSM). Again, the code accommodates a wide range of modified gravity and dark energy models. For the non-linear real space correlation function used in the GSM we use the Fourier transform of the RegPT 1-loop matter power spectrum. We compare predictions of the GSM for a Vainshtein screened and Chameleon screened model as well as GR. These predictions are compared to the Fourier transform of the Taruya, Nishimichi and Saito (TNS) redshift space power spectrum model which is fit to N-body data. We find very good agreement between the Fourier transform of the TNS model and the GSM predictions, with ≤ 6% deviations in the first two correlation function multipoles for all models for redshift space separations in 50Mpc h ≤ s ≤ 180Mpc/ h . Excellent agreement is found in the differences between the modified gravity and GR multipole predictions for both approaches to the redshift space correlation function, highlighting their matched ability in picking up deviations from GR. We elucidate the timeliness of such non-standard templates at the dawn of stage-IV surveys and discuss necessary preparations and extensions needed for upcoming high quality data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

TEMPEST (Thermo-Electric Model for Powering Energy Storage Technologies)

NREL's TEMPEST model combines electrical and thermal modeling for residential-scale battery systems. The model and default parameters are based off of two common commercial residential batteries. Key inputs to the model include house load, temperature of the battery location, and the solar profile. The key output of the TEMPEST model is the battery profile and internal battery temperature. If internal battery temperature exceeds limits, a derating will occur and this will be reflected in the battery profile. In addition to thermal modeling, the TEMPEST model uses realistic operating principals that are common in today's residential batteries. Mainly, the TEMPEST model incorporates "modes" of operation that constrain battery setpoint based on house load, solar output, and state of charge. The TEMPEST model can be used to analyze the effect of battery temperature, deratings, and mode setpoints on utility network loading and customer bills.

Blonsky, Michael↗

DOE Zero Energy Ready Manufactured Housing: Subject Matter Expert Technical Assistance Summary

Manufactured homes offer American consumers an affordable option for decent single-family detached housing. For working-class American families in many U.S. markets, manufactured homes are the first step toward home ownership. They now make up 10% of all new homes constructed in the United States, with higher percentages in the south and in rural communities. To help encourage the production of homes that are more durable, healthy, efficient, and disaster resistant, the U.S. Department of Energy is bringing its building science research to the manufactured housing industry through DOE’s Zero Energy Ready Manufactured Home (ZER-MH) program, which provides technical assistance and voluntary guidelines to manufactured home builders. Homes built to these guidelines are better able to handle power outages and less likely to experience moisture issues, offering a better product option for American families. This higher quality is evidenced by energy modeling which shows homes manufactured to these voluntary guidelines will typically use half the energy of manufactured homes built to the current minimum requirements of the U.S. Department of Housing and Urban Development (HUD)’s Manufactured Housing and Construction Safety Standard (MHCSS). These homes can also reduce critical energy demand during the busiest hours of the day, typically late afternoon and early evening in the summer when air conditioning demand is highest and mornings in the winter when furnaces and heaters are heating up. Reducing electricity demand during these peak periods when electricity rates are at their highest reduces costs for American families while freeing up capacity on overburdened energy distribution networks. Builders participating in the DOE ZER-MH program are eligible for a tax incentive via the 45L tax credit, which helps to offset the costs of ZER-MH upgrades, enabling builders to offer these certified homes at no additional cost. Together these factors enable manufactured homes to offer home buyers a housing option that is both affordable to finance and affordable to operate, with lower monthly mortgage payments and lower monthly energy bills.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Nonlinear triggered lightning models for use in finite difference calculations

Two nonlinear triggered lightning models have been developed for use in finite difference calculations. Both are based on three species of air chemistry physics and couple nonlinearly calculated air conductivity to Maxwell's equations. The first model is suitable for use in three-dimensional modeling and has been applied to the analysis of triggered lightning on the NASA F106B Thunderstorm Research Aircraft. The model calculates number densities of positive ions, negative ions, and electrons as a function of time and space through continuity equations, including convective derivative terms. The set of equations is closed by using experimentally determined mobilities, and the mobilities are also used to determine the air conductivity. Results from the model's application to the F106B are shown. The second model is two-dimensional and incorporates an enhanced air chemistry formulation. Momentum conservation equations replace the mobility assumption of the first model. Energy conservation equations for neutrals, heavy ions, and electrons are also used. Energy transfer into molecular vibrational modes is accounted for. The purpose for the enhanced model is to include the effects of temperature into the air breakdown, a necessary step if the model is to simulate more than the very earliest stages of breakdown. Therefore, the model also incorporates a temperature-dependent electron avalanche rate. Results from the model's application to breakdown around a conducting ellipsoid placed in an electric field are shown.

Rudolph, Terence↗

On analysis and stochastic modeling of the particle kinetic energy equation in particle-laden isotropic turbulent flows

In this study, we analyze three-dimensional particle-laden, isotropic turbulence to develop an understanding of inertial particle dynamics from a kinetic energy perspective. Data trends implying inhomogeneous sampling of the flow by particles are identified and used to support a proposed particle behavior: particles appear to accumulate in regions of low flow kinetic energy over time because they lose kinetic energy and slow down in such regions, ultimately causing them to spend more time there. To elucidate this behavior, we derive a particle kinetic energy equation from the particle momentum equation, which incorporates inertial effects through the Schiller–Naumann drag correlation. Upon extracting fundamental physics from this equation, hypotheses regarding the role of the Stokes number in the temporal change of particle kinetic energy and the previously proposed particle behavior are evaluated using simulation data considering three Stokes numbers. Finally, a Fokker–Planck equation is used to derive the steady-state probability density function of the particle kinetic energy. The model fits the simulation data well and provides a tool for further investigation into understanding preferential concentration, as well as a reduced order model for predicting particle kinetic energy in turbulent flows.

42 ENGINEERING↗

Improvements to PVWatts for Fixed and One-Axis Tracking Systems

This work presents improvements to the widely used NREL PVWatts photovoltaic system energy model to improve modeling accuracy for typical fixed and one axis system designs. The aim is to calculate losses in the PV system assuming typical modern system design practices, while maintaining simplicity by keeping the required set of input parameters small. These improvements allow users to more credibly and quickly evaluate competing system designs in early stage feasibility. Common submodels for module cover, spectral, snow, tracker, transformer, plant controller, and self-shading losses, in addition to a bifacial gain option, are incorporated into the PVWatts model, and are shown to improve PVWatts' system performance prediction capabilities without major impact to ease of use. We anticipate including these improvements in a future release of NREL's open source PVWatts code, and some of the features may become available in the System Advisor Model (SAM) desktop software as well as the popular PVWatts web application.

14 SOLAR ENERGY↗

National Climate Database (NCDB)

The National Climate Database (NCDB) is a high resolution, bias-corrected climate dataset consisting of the three most widely used variables of solar radiation- global horizontal (GHI), direct normal (DNI), and diffuse horizontal irradiance (DHI)- as well as other meteorological data. The goal of the NCDB is to provide unbiased high temporal and spatial resolution climate data needed for renewable energy modeling. The NCDB is modeled using a statistical downscaling approach with Regional Climate Model (RCM)-based climate projections obtained from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX; linked below). Daily climate projections simulated by the Canadian Regional Climate Model 4 (CanRCM4) forced by the second-generation Canadian Earth System Model (CanESM2) for two Representative Concentration Pathways (RCP4.5 or moderate emissions scenario and RCP8.5 or highest baseline emission scenario) are selected as inputs to the statistical downscaling models. The National Solar Radiation Database (NSRDB) is used to build and calibrate statistical models.

Array↗