SEARCH · Search NASA

Results for “Analytical energy balance model”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records

All sources NASA NTRS DOE OSTI

DOE OSTI2024

A generalized analytical energy balance model for evaluating agglomeration from a binary collision of wet particles

Agglomeration of wet particles, i.e., particles coated with a thin liquid layer, is a common phenomenon in many processes like fluidized bed combustion of low rank fuels. The availability of an agglomeration model that can evaluate the outcome of a binary collision between wet particles differing in solid particle properties, liquid layer thicknesses, and initial collision (impact) speeds is essential for obtaining a comprehensive understanding on the existing processes experiencing wet particle agglomeration or for a successful development of new processes with high chances of wet particle agglomeration. This study presents a generalized agglomeration model on the basis of energy conservation before and after collision when colliding wet particles may differ in solid particle properties, liquid layer thicknesses, and impact speeds. The model was established based on the approximate values of energy losses that may happen during the collision. It incorporates body forces, solid-solid contacting, liquid capillary, and viscous contributions, as well as the liquid bridge volume effect. Predictions of the new model for collision outcomes of identical wet particles were like those from an analytical energy balance model developed recently by the group for identical wet particles. We also validated the new model by experimental data from literature. The results of a collision direction analysis indicated that the direction often has a minimal effect on the collision outcome in many practical scenarios. The results of Monte Carlo uncertainty analyses with the new model revealed that proper estimations of impact speed, under capillary limiting conditions, and thickness of coating layers and asperity heights, under viscous limiting conditions, are critical for the realistic prediction of collision outcomes at impact speeds close to critical impact speed, i.e., the minimum particle speed required for the particles to rebound.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2026

Data for A Hybrid Biophysical-Machine Learning Framework for Diurnal Surface Energy Flux Estimation Using Proximal Sensing

Thermal infrared-based remote sensing of surface energy fluxes has traditionally relied on high spatial resolution satellite data with revisit frequencies on the order of weeks. In this study, we evaluate a biophysics-based analytical surface energy balance model for predicting latent energy (LE) and sensible heat (H) fluxes using proximal sensing observations. The Surface Temperature Initiated Closure (STIC1.2) model has been extensively validated across a wide range of spatial and temporal scales using various satellite-derived thermal infrared data sets. Here we extend this validation by applying STIC at sub-hourly temporal resolution over multiple growing seasons for four distinct agricultural systems. We further develop and evaluate novel STIC variants that incorporate machine learning (ML) techniques to eliminate the need for surface energy balance observations, specifically net radiation and soil heat flux, thereby enhancing model applicability in data-sparse settings. The integration of a ML component to estimate surface available energy is shown to have strong predictive performance for both LE (R2 = 0.81–0.94) and H (R2 = 0.46–0.72) across all agricultural systems examined here, demonstrating the potential of hybrid biophysical-machine learning approaches for surface energy balance modeling with minimal data requirements. This study concludes with a novel application of explainable machine learning (exML) to diagnose sources of model error. This exML framework attributes residual prediction errors to both model input variables and environmental drivers not explicitly included in the simulation experiments. This approach provides a new pathway for improving model design and integrating previously overlooked yet influential variables into future model iterations.

AI/ML↗

DOE OSTI2026

Data for: A hybrid biophysical-machine learning framework for diurnal surface energy flux estimation using proximal sensing

Thermal-based remote sensing of surface energy fluxes has traditionally relied on high spatial resolution satellite data with revisit frequencies on the order of weeks. In this study, we evaluate a biophysics-based analytical surface energy balance model for predicting latent energy (LE) and sensible heat (H) fluxes using proximal sensing observations. The Surface Temperature Initiated Closure (STIC1.2) model has been extensively validated across a wide range of spatial and temporal scales using various satellite-derived thermal datasets. Here we extend this validation by applying STIC at sub-hourly temporal resolution over multiple growing seasons for four distinct agricultural systems. We further develop and evaluate novel STIC variants that incorporate machine learning (ML) techniques to eliminate the need for specific surface energy balance observations, specifically net radiation and soil heat flux, thereby enhancing model applicability in data-sparse settings. The integration of an ML component to estimate surface available energy is shown to have strong predictive performance for both LE (R2 = 0.81-0.94) and H (R2 = 0.46-0.72) across all agricultural systems examined here, demonstrating the potential of hybrid biophysical – machine learning approaches for surface energy balance modeling with minimal data requirements. This study concludes with a novel application of explainable machine learning (exML) to diagnose sources of model error. This exML framework attributes residual prediction errors to both model input variables and environmental drivers not explicitly included in the simulation experiments. This approach provides a new pathway for improving model design and integrating previously overlooked yet influential variables into future model iterations.

Agricultural Sciences↗

DOE OSTI2026

A Hybrid Biophysical‐Machine Learning Framework for Diurnal Surface Energy Flux Estimation Using Proximal Sensing

Thermal infrared-based remote sensing of surface energy fluxes has traditionally relied on high spatial resolution satellite data with revisit frequencies on the order of weeks. In this study, we evaluate a biophysics-based analytical surface energy balance model for predicting latent energy ( LE ) and sensible heat ( H ) fluxes using proximal sensing observations. The Surface Temperature Initiated Closure (STIC1.2) model has been extensively validated across a wide range of spatial and temporal scales using various satellite-derived thermal infrared data sets. Here we extend this validation by applying STIC at sub-hourly temporal resolution over multiple growing seasons for four distinct agricultural systems. We further develop and evaluate novel STIC variants that incorporate machine learning (ML) techniques to eliminate the need for surface energy balance observations, specifically net radiation and soil heat flux, thereby enhancing model applicability in data-sparse settings. The integration of a ML component to estimate surface available energy is shown to have strong predictive performance for both LE (R 2 = 0.81–0.94) and H (R 2 = 0.46–0.72) across all agricultural systems examined here, demonstrating the potential of hybrid biophysical-machine learning approaches for surface energy balance modeling with minimal data requirements. This study concludes with a novel application of explainable machine learning (exML) to diagnose sources of model error. This exML framework attributes residual prediction errors to both model input variables and environmental drivers not explicitly included in the simulation experiments. This approach provides a new pathway for improving model design and integrating previously overlooked yet influential variables into future model iterations.

evapotranspiration↗

NASA NTRS2006

Analytical Ion Thruster Discharge Performance Model

A particle and energy balance model of the plasma discharge in magnetic ring-cusp ion thrusters has been developed. The model follows the original work of Brophy in the development of global 0-D discharge models that utilize conservation of particles into and out of the thruster and conservation of energy into the discharge and out of the plasma in the form of charged particles to the walls and beam and plasma radiation. The present model is significantly expanded over Brophy's original work by including self-consistent calculations of the internal neutral pressure, electron temperature, primary electron density, electrostatic ion confinement (due to the ring-cusp fields), plasma potential, discharge stability, and time dependent behavior during recycling. The model only requires information on the thruster geometry, ion optics performance and electrical inputs such as discharge voltage and currents, etc. to produce accurate performance curves of discharge loss versus mass utilization efficiency. The model has been benchmarked against the NEXIS Laboratory Model (LM) and Development Model (DM) thrusters, and successfully predicts the thruster discharge loss as a function of mass utilization efficiency for a variety of thrusters. The discharge performance model will be presented and results showing ion thruster performance and stability given.

discharge chambers↗

NASA NTRS1980

Energy-balance climate models

An introductory survey of the global energy balance climate models is presented with an emphasis on analytical results. A sequence of increasingly complicated models involving ice cap and radiative feedback processes are solved and the solutions and parameter sensitivities are studied. The model parameterizations are examined critically in light of many current uncertainties. A simple seasonal model is used to study the effects of changes in orbital elements on the temperature field. A linear stability theorem and a complete nonlinear stability analysis for the models are developed. Analytical solutions are also obtained for the linearized models driven by stochastic forcing elements. In this context the relation between natural fluctuation statistics and climate sensitivity is stressed.

North, G. R.↗

NASA NTRS1981

Energy balance climate models

An introductory survey of the global energy balance climate models is presented with an emphasis on analytical results. A sequence of increasingly complicated models involving ice cap and radiative feedback processes are solved, and the solutions and parameter sensitivities are studied. The model parameterizations are examined critically in light of many current uncertainties. A simple seasonal model is used to study the effects of changes in orbital elements on the temperature field. A linear stability theorem and a complete nonlinear stability analysis for the models are developed. Analytical solutions are also obtained for the linearized models driven by stochastic forcing elements. In this context the relation between natural fluctuation statistics and climate sensitivity is stressed.

North, G. R.↗

NASA NTRS1981

A class of analytic solutions for the thermally balanced magnetostatic prominence sheet

A theoretical study is presented for the nonlinear interplay between magnetostatic equilibrium and energy balance in a Kippenhahn-Schlueter type solar prominence sheet. A class of theoretical models is presented, expressed in closed analytic forms, thus facilitating the direct illustration of the nonlinear physical properties. The model couples the equilibrium between magnetic field, plasma pressure, and weight on the one hand, with the balance between a rho-squared T radiative loss, a rho wave heating (where rho equals plasma density, and T equals plasma temperature), and thermal conduction channeled along magnetic field lines on the other. The steady solutions are divided into three classes, and are characterized by the total wave heating in the prominence sheet which is greater than, equal to, or less than the total radiative loss. The compaction of the plasma along the field lines, under its own weight, and the energy transport effects determine which of the three basic behaviors obtains in a particular situation. A discussion is presented of the implications of the steady solutions for the formation of prominences.

Low, B. C.↗

NASA NTRS2009

Microstructural, Magnetic Anisotropy, and Magnetic Domain Structure Correlations in Epitaxial FePd Thin Films with Perpendicular Magnetic Anisotropy

L1(sub 0)-ordered FePd epitaxial thin films were prepared using dc magnetron sputter deposition on MgO (001) substrates. The films were grown with varying thickness and degree of chemical order to investigate the interplay between the microstructure, magnetic anisotropy, and magnetic domain structure. The experimentally measured domain size/period and magnetic anisotropy in this high perpendicular anisotropy system were found to be correlated following the analytical energy model proposed by Kooy and Enz that considers a delicate balance between the domain wall energy and the demagnetizing stray field energy.

Skuza, J. R.↗

NASA NTRS1985

Current sheets in solar flares

Numerical simulations of current sheets in solar flares are described, including new features such as the presence of a shock in Petschek's mechanism and impulsive burst-like reconnection due to secondary tearing and coalescence. The general properties of magnetic reconnection are discussed in connection with the basic requirements of numerical current sheet models. Emphasis is given to the need for realistic criteria for energy balance, the Lundquist number, and line tying in calculations of tearing and reconnection modes. The need for analytical models of current sheet processes to compare with the numerical simulations is also stressed.

Priest, E. R.↗

NASA NTRS1996

Determination of Uncertainties for the New SSME Model

This report discusses the uncertainty analysis performed in support of a new test analysis and performance prediction model for the Space Shuttle Main Engine. The new model utilizes uncertainty estimates for experimental data and for the analytical model to obtain the most plausible operating condition for the engine system. This report discusses the development of the data sets and uncertainty estimates to be used in the development of the new model. It also presents the application of uncertainty analysis to analytical models and the uncertainty analysis for the conservation of mass and energy balance relations is presented. A new methodology for the assessment of the uncertainty associated with linear regressions is presented.

Coleman, Hugh W.↗

NASA NTRS2010

Using Leaf Chlorophyll to Parameterize Light-Use-Efficiency Within a Thermal-Based Carbon, Water and Energy Exchange Model

Chlorophylls absorb photosynthetically active radiation and thus function as vital pigments for photosynthesis, which makes leaf chlorophyll content (C(sub ab) useful for monitoring vegetation productivity and an important indicator of the overall plant physiological condition. This study investigates the utility of integrating remotely sensed estimates of C(sub ab) into a thermal-based Two-Source Energy Balance (TSEB) model that estimates land-surface CO2 and energy fluxes using an analytical, light-use-efficiency (LUE) based model of canopy resistance. The LUE model component computes canopy-scale carbon assimilation and transpiration fluxes and incorporates LUE modifications from a nominal (species-dependent) value (LUE(sub n)) in response to short term variations in environmental conditions, However LUE(sub n) may need adjustment on a daily timescale to accommodate changes in plant phenology, physiological condition and nutrient status. Day to day variations in LUE(sub n) were assessed for a heterogeneous corn crop field in Maryland, U,S.A. through model calibration with eddy covariance CO2 flux tower observations. The optimized daily LUE(sub n) values were then compared to estimates of C(sub ab) integrated from gridded maps of chlorophyll content weighted over the tower flux source area. The time continuous maps of daily C(sub ab) over the study field were generated by focusing in-situ measurements with retrievals generated with an integrated radiative transfer modeling tool (accurate to within +/-10%) using at-sensor radiances in green, red and near-infrared wavelengths acquired with an aircraft imaging system. The resultant daily changes in C(sub ab) within the tower flux source area generally correlated well with corresponding changes in daily calibrated LUE(sub n) derived from the tower flux data, and hourly water, energy and carbon flux estimation accuracies from TSEB were significantly improved when using C(sub ab) for delineating spatio-temporal variations in LUE(sub n). The results demonstrate the synergy between thermal infrared and shortwave reflective wavebands in producing valuable remote sensing data for operational monitoring of carbon and water fluxes.

Houlborg, Rasmus↗

NASA NTRS2011

Combining Observations in the Reflective Solar and Thermal Domains for Improved Mapping of Carbon, Water and Energy FLuxes

This study investigates the utility of integrating remotely sensed estimates of leaf chlorophyll (C(sub ab)) into a thermal-based Two-Source Energy Balance (TSEB) model that estimates land-surface CO2 and energy fluxes using an analytical, light-use-efficiency (LUE) based model of canopy resistance. Day to day variations in nominal LUE (LUE(sub n)) were assessed for a corn crop field in Maryland U.S.A. through model calibration with CO2 flux tower observations. The optimized daily LUE(sub n) values were then compared to estimates of C(sub ab) integrated from gridded maps of chlorophyll content weighted over the tower flux source area. Changes in Cab exhibited a curvilinear relationship with corresponding changes in daily calibrated LUE(sub n) values derived from the tower flux data, and hourly water, energy and carbon flux estimation accuracies from TSEB were significantly improved when using C(sub ab) for delineating spatio-temporal variations in LUE(sub n). The results demonstrate the synergy between thermal infrared and shortwave reflective wavebands in producing valuable remote sensing data for monitoring of carbon and water fluxes.

Houborg, Rasmus↗

NASA NTRS1981

Discrepancies between theoretical and empirical models of the flaring solar chromosphere and their possible resolution

Possible sources of pronounced discrepancy between empirical and theoretical models of the solar chromosphere during flares are discussed. It is noted that a principal source of uncertainty in empirical models is the inhomogeneity of the spectral data on which they are based. With theoretical models, probably the most important source of error is neglect of the radiative coupling of upper and lower chromospheric regions. A new procedure for studying flare energy input is suggested wherein the required input is derived from the empirical model chromosphere. This procedure is applied to the electron-heated case, and it is found that the integral equation defining the flare energy deposition rate can be inverted analytically to yield the injected electron flux energy spectrum from knowledge of the energy balance in the empirical atmosphere. Recent empirical model results are analyzed in this manner, and the calculated injected electron flux spectrum is compared with that needed for hard X-ray bursts in moderately large flares.

Emslie, A. G.↗

NASA NTRS1977

Analytical study of laser supported combustion waves in hydrogen

A one-dimensional energy equation, with constant pressure and area, was used to model the LSC wave. This equation balances convection, conduction, laser energy absorption, radiation energy loss and radiation energy transport. Solutions of this energy equation were obtained to give profiles of temperature and other properties, as well as the relation between laser intensity and mass flux through the wave. The flow through the LSC wave was then conducted through a variable pressure, variable area streamtube to accelerate it to high speed, with the propulsion application in mind. A numerical method for coupling the LSC wave model to the streamtube flow was developed, and a sample calculation was performed. The result shows that 42% of the laser power has been radiated away by the time the gas reaches the throat. It was concluded that in the radially confined flows of interest for propulsion applications, transverse velocities would be less important than in the unconfined flows where air experiments have been conducted.

Kemp, N. H.↗

NASA NTRS1980

A model for the burning rates of composite propellants

An analytical model of the steady-state burning of composite solid propellants is presented. An improved burning rate model is achieved by incorporating an improved AP monopropellant model, a separate energy balance for the binder in which a portion of the diffusion flame is used to heat the binder, proper use of the binder regression rate in the model, and a model for the combustion of the energetic binder component of CMDB propellants. Also, an improved correlation and model of aluminum agglomeration is developed which properly describes compositional trends.

Cohen, N. S.↗

NASA NTRS2015

Introduction to Heat Pipes

This is the presentation file for the short course Introduction to Heat Pipes, to be conducted at the 2015 Thermal Fluids and Analysis Workshop, August 3-7, 2015, Silver Spring, Maryland. NCTS 21070-15. Course Description: This course will present operating principles of the heat pipe with emphases on the underlying physical processes and requirements of pressure and energy balance. Performance characterizations and design considerations of the heat pipe will be highlighted. Guidelines for thermal engineers in the selection of heat pipes as part of the spacecraft thermal control system, testing methodology, and analytical modeling will also be discussed.

Heat Pipes↗

NASA NTRS2011

A Simple, Analytical Model of Collisionless Magnetic Reconnection in a Pair Plasma

A set of conservation equations is utilized to derive balance equations in the reconnection diffusion region of a symmetric pair plasma. The reconnection electric field is assumed to have the function to maintain the current density in the diffusion region, and to impart thermal energy to the plasma by means of quasi-viscous dissipation. Using these assumptions it is possible to derive a simple set of equations for diffusion region parameters in dependence on inflow conditions and on plasma compressibility. These equations are solved by means of a simple, iterative, procedure. The solutions show expected features such as dominance of enthalpy flux in the reconnection outflow, as well as combination of adiabatic and quasi-viscous heating. Furthermore, the model predicts a maximum reconnection electric field of E(sup *)=0.4, normalized to the parameters at the inflow edge of the diffusion region.

Hesse, Michael↗