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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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DOE OSTI2017

Transactive Energy Simulation Platform

TESP combines existing domain simulators in the electric power grid, with new transactive agents, growth models and evaluation scripts. The existing domain simulators include GridLAB-D for the distribution grid and single-family residential buildings, MATPOWER for transmission and bulk generation, and EnergyPlus for large buildings. More are planned for subsequent versions of TESP. The new elements are: TEAgents - simulate market participants and transactive systems for market clearing. Some of this functionality was extracted from GridLAB-D and implemented in Python for customization by PNNL and others; Growth Model - a means for simulating system changes over a multiyear period, including both normal load growth and specific investment decisions. Customizable in Python code; and Evaluation Script - a means of evaluating different transactive systems through customizable post-processing in Python code. TESP provides a method for other researchers and vendors to design transactive systems, and test them in a virtual environment. It allows customization of the key components by modifying Python code.

Source record↗
DOE OSTI2013

Offshore Wind ENergy Simulation Toolkit

This structural dynamics finite element analysis tool is intended to be used for the analysis of vertical-axis wind turbine (VAWT) and is used in conjunction with the VAWTGen mesh generator. The core of the analysis software is a finite element formulation consisting of the beam element with rotational and stress stiffening effects. Arbitrary VAWT configurations may be constructed by an assembly of beam elements. The software has been designed with a modular approach to facilities interfacing aerodynamics and hydrodynamics software modules in future versions. The software allows for modal and transient analysis capabilities for a rotating VAWT configuration with arbitrary boundary conditions, initial condition, and loads.

Owens, Brian Christopher↗
DOE OSTI2018

Domestic Dishwasher Simulated Energy Efficiency Evaluation Using Thermoelectric Heat Pump for Water Heating and Dish Drying

A quasi-steady state, heat and mass transfer lumped-capacitance model was developed to predict the energy consumption and drying performance of domestic dishwashers. A numerical finite element solution was applied, assuming that the following components could each be treated as a lumped thermal capacitance: dish load, tub, wash water, and air in tub. The model was used to predict the energy consumption savings of heating water using a thermoelectric heat pump that extracts heat from a thermal storage medium, and the drying performance of circulating tub air through the cold and then hot side of TE modules.

Abuheiba, Ahmad↗
DOE OSTI2023

Developing and tuning a community scale energy model for a disadvantaged community

This work describes the development of a community-scale energy model for a mixed-use low-income community located in Huntington Beach, CA. An accurate community-scale energy model is useful for evaluating the use of limited capital resources used to invest in clean energy technologies. This work lays out the process of developing such a model while relying primarily on publicly available data and highlighting critical partnerships necessary for model development success. The primary contribution of this work is the demonstration of the process used to develop an accurate energy model for a disadvantaged community when minimal building and energy use data is available. The heart of the model is the physics-based community scale energy modeling platform URBANopt. Using a bottom-up load modeling approach, energy simulated energy use falls within 3% or less of aggregate annual utility data, and within 10% or less aggregate monthly utility data. The demonstrated model development and tuning process can be used by others to characterize other atypical communities, which may differ significantly from prototypical models.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Simulated building energy demand biases resulting from the use of representative weather stations

Numerical building models are typically forced with weather data from a limited number of “representative cities” or weather stations representing different climate regions. The use of representative weather stations reduces computational costs, but often fails to capture spatial heterogeneity in weather that may be important for simulations aimed at understanding how building stocks respond to a changing climate. We quantify the potential reduction in bias from using an increasing number of weather stations over the western U.S. The approach is based on deriving temperature and load time series using incrementally more weather stations, ranging from 8 to roughly 150, to capture weather across different seasons. Using 8 stations, one from each climate zone, across the western U.S. results in an average absolute summertime temperature bias of 7.2°F with respect to a spatially-resolved gridded dataset. The mean absolute bias drops to 2.8°F using all available weather stations. Temperature biases of this magnitude could translate to absolute summertime mean simulated load biases as high as 13.8%, a significant error for capacity expansion planners who may use these types of simulations. Increasing the size of the domain over which biases are calculated reduces their magnitude as positive and negative biases may cancel out. Using 8 representative weather stations can lead to a 20-40% overestimation of peak building loads during both summer and winter. Using weather stations close to population centers reduces both mean and peak load biases. This approach could be used by others designing aggregate building simulations to understand the sensitivity to their choice of weather stations used to drive the models.

Burleyson, Casey D.↗
DOE OSTI2024

Dark Energy Survey Year 3 results: Simulation-based cosmological inference with wavelet harmonics, scattering transforms, and moments of weak lensing mass maps. Validation on simulations

Beyond-two-point statistics contain additional information on cosmological as well as astrophysical and observational (systematics) parameters. In this methodology paper we provide an end-to-end simulationbased analysis of a set of Gaussian and non-Gaussian weak lensing statistics using detailed mock catalogs of the Dark Energy Survey (DES). Here, we implement: 1) second and third moments; 2) wavelet phase harmonics (WPH); 3) the scattering transform (ST). Our analysis is fully based on simulations, it spans a space of seven $νw$CDM cosmological parameters, and it forward models the most relevant sources of systematics of the data (masks, noise variations, clustering of the sources, intrinsic alignments, and shear and redshift calibration). We implement a neural network compression of the summary statistics, and we estimate the parameter posteriors using a likelihood-free-inference approach. We validate the pipeline extensively, and we find that WPH exhibits the strongest performance when combined with second moments, followed by ST, and then by third moments. The combination of all the different statistics further enhances constraints with respect to second moments, up to 25 percent, 15 percent, and 90 percent for S 8 , Ω m , and the figure-of-merit FoM S8;Ωm , respectively. We further find that non-Gaussian statistics improve constraints on w and on the amplitude of intrinsic alignment with respect to second moments constraints. The methodological advances presented here are suitable for application to Stage IV surveys from Euclid, Rubin-LSST, and Roman with additional validation on mock catalogs for each survey. In a companion paper we present an application to DES Year 3 data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

A comparison of explosion energies for simulated and observed core-collapse supernovae

ABSTRACT There are now 20 multidimensional core-collapse supernova (CCSN) simulations that explode. However, these simulations have explosion energies that are a few times 1050 erg, not 1051 erg. In this manuscript, we compare the inferred explosion energies of these simulations and observations of 40 SN IIP. Assuming a lognormal distribution, the mean explosion energy for these observations is $\mu _{\rm obs} = -0.23^{+0.08}_{-0.12}$ ($\log _{10}(E/10^{51}\, {\rm erg})$) and the width is $\sigma _{\rm obs} = 0.52^{+0.09}_{-0.08}$. Only three CCSN codes have sufficient simulations to compare with observations: CHIMERA, CoCoNuT-FMT, and FORNAX. Currently, FORNAX has the largest sample of simulations. The two-dimensional FORNAX simulations show a correlation between explosion energy and progenitor mass, ranging from linear to quadratic, Esim ∝ M1 − 2; this correlation is consistent with inferences from observations. In addition, we infer the ratio of the observed-to-simulated explosion energies, Δ = log10(Eobs/Esim). For the CHIMERA set, Δ = 0.25 ± 0.07; for CoCoNuT-FMT, Δ = 0.49 ± 0.07; for FORNAX2D, Δ = 0.62 ± 0.06, and for FORNAX3D, Δ = 0.85 ± 0.07. On average, the simulations are less energetic than inferred energies from observations (Δ ≈ 0.6), but we also note that the variation among the simulations [max(Δ) − min(Δ) ≈ 0.6] is as large as this average offset. This suggests that further improvements to the simulations could resolve the discrepancy. Furthermore, both the simulations and observations are heavily biased. In this preliminary comparison, we model these biases, but to more reliably compare the explosion energies, we recommend strategies to unbias both the simulations and observations.

79 ASTRONOMY AND ASTROPHYSICS↗