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Results for “Energy Modeling”

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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1974

Dissipation of energy in model experiments

Interaction studies of a plasma stream with a magnetic dipole have shown that the thickness of the plasma/field interlayer is considerably greater than the characteristic plasma dimension c/omega sub 0. Broadening of the layer is due to the formation of a collisionless shock wave. To demonstrate collisionless dissipation, the Joulean losses were calculated using the conductivity value obtained from the skin layer thickness. Analysis of the various physical processes showed that the hypothesis of collisionless dissipation of the directional plasma flow is justified.

Podgornyy, I. M.↗
NASA NTRS1987

Estimating regional evapotranspiration from remotely sensed data by surface energy balance models

Spatial and temporal variations of surface radiative temperatures of the burned and unburned areas of the Konza tallgrass prairie were studied. The role of management practices, topographic conditions and the uncertainties associated with in situ or airborne surface temperature measurements were assessed. Evaluation of diurnal and seasonal spectral characteristics of the burned and unburned areas of the prairie was also made. This was accomplished based on the analysis of measured spectral reflectance of the grass canopies under field conditions, and modelling their spectral behavior using a one dimensional radiative transfer model.

Asrar, Ghassem↗
NASA NTRS1989

Turbulence energy redistributive model

A study is made to improve the predictions of turbulent flows through modifications of the pressure-strain correlation of the Reynolds stress equations. The mean-strain term of the pressure-strain correlation is formulated by incorporating the tensor with the Reynolds stresses that account for a non-isotropic turbulence effect in the flows which are accompanied by a turbulent separating flow. This model is compared with other existing models and results are verified with existing experimental results for turbulent shear flows.

Amano, R. S.↗
NASA NTRS2004

The Precession Index, A Nonlinear Energy Balance Model, And Seversmith Psychroterms

An important component of Milankovitch's astronomical theory of climate change is the precession index. The precession index, along with the Earth's tilt and orbital eccentricity, are believed to be the major controlling factors of climate change in the last few million years. The precession index is e sin omega(sub s) where e is the Earth's orbital eccentricity and omega(sub s) measures how close the Sun is to the Earth at midsummer. When omega(sub s) = 90deg the Sun is close to the Earth during northern summer, and at 270deg it is far from the Earth during northern summer. The precession index varies with time, because both the eccentricity e and the parameter omega(sub s) are constantly changing due to disturbances in the Earth's orbit by other planets, and due to the precession of the Earth, The change is largely periodic, with a period of about 23,000 years.

Rubincam, David Parry↗
NASA NTRS2019

A Model for Energy Buildup and Eruption Onset in Coronal Mass Ejections

Coronal mass ejections (CMEs) and eruptive flares (EFs) are the most energetic explosions in the solar system. Their underlying origin is the free energy that builds up slowly in the sheared magnetic field of a filament channel. We report the first end-to-end numerical simulation of a CME/EF, from zero-free-energy initial state through filament channel formation to violent eruption, driven solely by the magnetic-helicity condensation process. Helicity is the topological measure of linkages between magnetic flux systems, and is conserved in the corona, building up inexorably until it is ejected into interplanetary space. Numerous investigations have demonstrated that helicity injected by small-scale vortical motions, such as those observed in the photosphere, undergoes an inverse cascade from small scales to large, “condensing” at magnetic-polarity boundaries. Our new results verify that this process forms a filament channel within a compact bipolar region embedded in a background dipole field, and show for the first time that a fast CME eventually occurs via the magnetic-breakout mechanism. We further show that the trigger for explosive eruption is reconnection onset in the flare current sheet that develops above the polarity inversion line: this reconnection forms flare loops below the sheet and a CME flux rope above, and initiates high-speed outward flow of the CME. Our findings have important implications for magnetic self organization and explosive behavior in solar and other astrophysical plasmas, as well as for understanding and predicting explosive solar activity.

filaments↗
NASA NTRS2022

Computing Halo Orbits In Bicircular Model Using Energy Balancing Method

The orbits around the Lagrange points L1 and L2 of the Sun-Earth-Moon system are chaotic and unstable by nature. In this work, we describe a simple method to control Halo Orbits with a single maneuver at the XZ-plane crossing for each revolution of the orbit in the Bicircular Problem. Examples of up to 500 revolutions of the Halo Orbit are controlled using this method. With optimization and adjustment of the maneuver design, the 𝚫V can be significantly reduced. The simplicity of the method and the infrequency of the maneuvers make this a good candidate for future autonomous control of libration orbits.

Lo, Martin W.↗
DOE OSTI2025

High-resolution climate model datasets for energy infrastructure planning in a renewable-dependent future

Electrification and renewables deployment efforts are amplifying the interdependence of the climate and energy systems. Increases in climate model resolution, which is now approaching that of reanalysis datasets and operational weather forecast models, present a unique opportunity to use future climate projections for energy infrastructure planning. In this Perspective, we review recent developments in high-resolution climate modeling, which have been driven by increased computing power and advanced software tools. We then look ahead to discuss how high-resolution climate data can be used to plan for a renewable-dependent future, and envision a unified climate-energy model framework that captures the two-way feedbacks between these interdependent systems.

climate change↗
DOE OSTI2024

Physics-informed hybrid modeling methodology for building infiltration

Infiltration is responsible for one-third to one-half of the space conditioning load of a typical residential home, but the modeling of infiltration for building energy modeling is either represented by over-simplified equations or dependent on over-generalized rules of thumb. Here, this paper develops a physics-informed data-driven methodology for modeling infiltration using building-specific empirical measurements. The developed hybrid methodology combines machine-learning categorization and grey-box sub-modeling to improve the accuracy and generalization of commonly used grey-box infiltration models. The developed methodology excels at predicting infiltration by improving the ability to predict infiltration under unseen environmental conditions using machine learning algorithms with physical significance. In a case study conducted using the iUnit, a modular studio apartment experimental test facility located at the National Renewable Energy Laboratory, we use empirical airtightness measurements to fit an infiltration model using the developed methodology. We find that the developed methodology can improve the overall model accuracy by 43% and improve extrapolation by 38%, compared with the model based on the common grey-box infiltration equation. We also notice that the selected features can improve the performance of a pure machine-learning model, indicating that our methodology identifies the features with the most physical significance to infiltration modeling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Enhancing EnergyPlus capabilities to model dynamic building envelopes using python plugin

Nearly half of the energy consumption in the United States is related to buildings, resulting in an urgent need to develop innovative technologies to improve building energy efficiency. Dynamic building envelopes, comprising switchable insulation and thermal energy storage materials, have been proposed recently as a promising solution to reduce buildings' heating and cooling loads by thermally coupling the indoor environment with the ambient environment when beneficial while decoupling them when outdoor conditions are not favorable. Although various related technologies are still underway, the whole-building energy modeling tools, like EnergyPlus, do not have the capability to simulate the transient and dynamic nature of dynamic envelope materials and components to accurately predict their impact on building energy use. The objective of this study is to formulate a method in EnergyPlus simulation engine to model multilayer envelopes, comprising dynamic building materials with variable thermophysical properties, and discuss the changes made to the program using a Python plugin. Furthermore, the thermal performance of the dynamic envelopes using the proposed method is compared and verified with the results from a well-established commercial code, COMSOL Multiphysics. A parametric assessment is also conducted to evaluate the energy efficiency benefits of dynamic envelopes in a single-family residential building, demonstrating total annual energy savings up to 11.6 %, when a dynamic envelope operates alone, and up to 18.2 % when it is combined with a thin layer of phase change material as a thermal storage medium. Finally, a United States wide energy efficiency assessment is presented to showcase the geographical spread of the energy savings. The method designed and implemented in this study provides the researchers with the ability to implement their dynamic insulation methods in EnergyPlus and evaluate the whole building energy impact.

25 ENERGY STORAGE↗
NASA NTRSDate not supplied

Discrete Rotational Energy for Polyatomic Molecules in Direct Simulation Monte Carlo

The environments experienced by vehicles upon entry into planetary atmospheres generally result in severe aerothermodynamic loading. These flows are characterized by the formation of strong shock waves, behind which high temperatures and non-equilibrium environments are generated, and the accurate prediction of internal energy relaxation and chemical kinetics becomes important. This manuscript focuses on the internal relaxation of the rotational energy of polyatomic molecules. Previous work has described the implementation of a discrete rotational energy model for diatomic molecules (linear rotators). Later, Gimelshein et. al extended this model to include polyatomic molecular internal energies. However, they did not include details on how to generate the particles at equilibrium conditions and centrifugal distortion was not included in their model. The purpose of the present study is to extend the afore-mentioned models to the treatment of discrete rotational energy in polyatomic molecules with the addition of centrifugal distortion. An overview of the background theory needed for the implementation of the model will be given followed by the model itself and verification of the model. For example, sampled versus Boltzmann distributions are compared in Figure 1 for CH3 (oblate rotator – two quantum numbers) and examples of thermal relaxation behavior for linear and non-linear rotators are presented in Figure 2. In addition, comparisons of thermophysical properties will be presented, as well as examples of adiabatic relaxation and application to hypersonic flow.

Rarefied Gas Dynamics↗
NASA NTRS1975

Expansion of chromospheric matter in the gradual phase of solar flares

Interferometric observations at 17 GHz of several small X-ray flares are presented along with soft X-ray observations of preflare active regions to show that a large mass increase accompanies the formation of an X-ray hot region in the corona. The total amount of energy contained in a hot coronal region is estimated, and a model is proposed in which a significant amount of the hot matter is supplied to the corona from the chromosphere during each flare. According to this model, energy produced by some coronal instability is transported by thermal conduction to the chromosphere, where dense gas is heated and subsequently expands into the corona. It is shown that impulsive heating of the chromosphere by nonthermal electrons cannot be the energy source of this model because the total energy supplied to the hot region during the gradual phase must be much greater than that supplied during the impulsive phase.

Ohki, K.↗
NASA NTRS2011

Using Dark Matter Haloes to Learn about Cosmic Acceleration: A New Proposal for a Universal Mass Function

Structure formation provides a strong test of any cosmic acceleration model because a successful dark energy model must not inhibit or overpredict the development of observed large-scale structures. Traditional approaches to studies of structure formation in the presence of dark energy or a modified gravity implement a modified Press-Schechter formalism, which relates the linear overdensities to the abundance of dark matter haloes at the same time. We critically examine the universality of the Press-Schechter formalism for different cosmologies, and show that the halo abundance is best correlated with spherical linear overdensity at 94% of collapse (or observation) time. We then extend this argument to ellipsoidal collapse (which decreases the fractional time of best correlation for small haloes), and show that our results agree with deviations from modified Press-Schechter formalism seen in simulated mass functions. This provides a novel universal prescription to measure linear density evolution, based on current and future observations of cluster (or dark matter) halo mass function. In particular, even observations of cluster abundance in a single epoch will constrain the entire history of linear growth of cosmological of perturbations.

Prescod-Weinstein, Chanda↗
DOE OSTI2025

Performance evaluation of automated data-driven feature extraction and selection methods for practical and scalable building energy consumption prediction models

Here, this study quantifies the impact of automated feature engineering methods (feature extraction and selection) on the quality and accuracy of machine learning models that predict building energy consumption. The case study compares model performance for three main scenarios: baseline (no feature extraction and selection), feature extraction only, and feature extraction combined with feature selection (filter and/or wrapper methods) for fully trained machine learning models for 200 metered/sub-metered energy measurements across 118 real buildings. For consistency, the same machine learning model architecture (a black box deep learning neural network with probabilistic forecast output) was used for all scenarios. Based on results, all feature engineering methods provided noticeable prediction accuracy improvements (e.g., 29%-68% median prediction improvement) compared to baseline scenarios. However, in this application, feature selection methods provide little practical value due to their limited performance gains and high computational cost. Smarter algorithm development supported by better computational environments will be needed before feature selection methods can reliably and efficiently improve predictive model performance.

97 MATHEMATICS AND COMPUTING↗