Search NASA⌕ Search

SEARCH · Search NASA

Results for “ENERGY BALANCE”

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.

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

At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Dynamic response of photorespiration in fluctuating light environments

Abstract Photorespiration is a dynamic process that is intimately linked to photosynthetic carbon assimilation. There is a growing interest in understanding carbon assimilation during dynamic conditions, but the role of photorespiration under such conditions is unclear. In this review, we discuss recent work relevant to the function of photorespiration under dynamic conditions, with a special focus on light transients. This work reveals that photorespiration is a fundamental component of the light induction of assimilation where variable diffusive processes limit CO2 exchange with the atmosphere. Additionally, metabolic interactions between photorespiration and the C3 cycle may help balance fluxes under dynamic light conditions. We further discuss how the energy demands of photorespiration present special challenges to energy balancing during dynamic conditions. We finish the review with an overview of why regulation of photorespiration may be important under dynamic conditions to maintain appropriate fluxes through metabolic pathways related to photorespiration such as nitrogen and one-carbon metabolism.

Plant Sciences↗
DOE OSTI2022

Constraining Physical Understanding of Aerosol Loading, Biogeochemistry, and Snowmelt Hydrology from Hillslope to Watershed Scale in the East River Scientific Focus Area

The mountain snowpack is a critical component of regional hydrology, ecology, biogeochemistry, and climate in the Western US. This project leveraged the East River Scientific Focus Area (SFA), as an outdoor laboratory to address a significant gap in our understanding of the mountain snowpack; namely, how atmospheric constituent deposition on snowpack influences snow energy balance and nutrient/chemical cycling, and how snowmelt timing and intensity exerts controls on emergent biogeochemical and ecohydrologic behavior. This aligned with East River SFA goals to integrate landscape scale measurements and physical based modeling tools to improve understanding of controls on runoff production, ecohydrology, biogeochemical cycling, and land surface energy partitioning in high mountain watersheds. The project included observations of snowpack at multiple scales, measurements of snow and deposited aerosols properties, in situ time series of surface energy balance, and spatially distributed, process-based snowmelt modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Measuring Sustainability of Solar Modules for Energy Transition: Mass, Energy, and Circularity

Transition to a carbon-free energy system is crucial for global decarbonization and underpins Circular Economy (CE) goals. Photovoltaic (PV) technology is required for Energy Transition, but manufacturing and circular pathways can be material, energy, and carbon-intensive. Therefore, we need a prioritization of sustainability strategies for PV evolution and lifecycle management in the context of Energy Transition. This study employs a suite of quantitative metrics to compare different proposed sustainability strategies for PV modules on their ability to achieve Energy Transition. Proposals for sustainable PV range from high-yield, high-efficiency paradigms, to short-lived and fully recyclable, to long-lasting, indestructible modules. We leverage a global decarbonization deployment schedule through 2100 with the open-source PV in Circular Economy (PV ICE) tool to quantify the impacts of different evolving module design scenarios covering the range of proposed sustainability strategies. First, modules are compared on effective capacity and required replacements to meet and maintain decarbonization capacity targets through 2100. We demonstrate the effects of lifetime, degradation, and reliability on effective capacity. Next, we quantify and compare virgin material demands and lifecycle wastes, examining the impacts of lifetime and recycling rates. Finally, and critically for renewable energy technologies, we quantify the energy demands required to achieve the decarbonization capacity targets and calculate energy balance metrics (net energy, energy return on investment). These results are then summarized into a metric matrix, demonstrating tradeoffs and the importance of longevity. Our suite of mass and energy metrics provides stakeholders and decision-makers with quantitative data on circular economy choices for PV in the energy transition, enabling informed evaluation of tradeoffs of different PV module designs and CE pathways.

circular economy↗
DOE OSTI2024

Code Benchmark of Depressurized Conduction Cooldown Transient in the High Temperature Test Facility

This paper presents results from modeling of a depressurized conduction cooldown (DCC) transient at the High Temperature Test Facility (HTTF) as part of the OECD-NEA Thermal Hydraulics Code Validation Benchmark for High-Temperature Gas-Cooled Reactors using HTTF Data . This paper briefly describes the benchmark and the models being used. It then presents a comparison of steady state and transient results based on the Problem 2 Exercise 1A and 1B definitions. We compare block and helium temperature distributions, mass flow distribution, and energy balance in steady state. All models show comparable mass flow distributions and energy balances. The temperatures within the core and outer regions are comparable in all models too, but inner reflector temperatures can vary significantly. Despite that, we find that the models are in good agreement for the full-power steady state. In the DCC, we look at block temperature at the core midplane and RCCS water exit temperature. The INL and ANL models are found to be in excellent agreement with one another on block temperature over time, while the agreement when the KAERI and NRG models are added into consideration is good. Differences in the transient heat removal from the RCCS cause the differences in block temperature over time in these models. The CNL models show similar trends to the INL, ANL, KAERI, and NRG models, but the temperatures are high because the volumes used in calculating the average temperature include the heater rods in the CNL models only. The HUN-REN model shows results that suggest significantly lower heat removal in the RCCS which merit further investigation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Protein Extraction, Precipitation, and Recovery from Chlorella sorokiniana Using Mechanochemical Methods

Protein extraction, precipitation, and recovery methods were evaluated by this study using a green alga—Chlorella sorokiniana. A mechanochemical cell disruption process was applied to facilitate protein extraction from microalgal biomass. Optimization of the mechanochemical process resulted in milling conditions that achieved a protein extraction of 52.7 ± 6.45%. The consequent acid precipitation method was optimized to recover 98.7% of proteins from the microalgal slurry. The measured protein content of the protein isolate was 41.4% w/w. These results indicate that the precipitation method is successful at recovering the extracted proteins in the algal slurry; however, the removal of non-protein solids during centrifugation and pH adjustment is not complete. The energy balance analysis elucidated that the energy demand of the protein extraction and recovery operation, at 0.83 MJ/kg dry algal biomass, is much lower than previous studies using high-pressure homogenization and membrane filtration. This study concludes that mechanochemical protein extraction and recovery is an effective, low-energy processing method, which could be used by algal biorefineries to prepare algal proteins for value-added chemical production as well as to make algal carbohydrates and lipids in the residual biomass more accessible for biofuel production.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Biorefinery upgrading of herbaceous biomass to renewable hydrocarbon fuels, Part 1: Process modeling and mass balance analysis

Process simulation has long been a well-established tool to track key operational, design, and mass and energy balance metrics for pre-commercial technologies such as advanced lignocellulosic biofuels. While tools such as this are well-documented in the public literature around 2nd-generation cellulosic ethanol technologies (which have been scaled up to commercial deployment to some degree over the past decade), such models and analysis information remain more sparse for more complex biorefinery pathways focused on producing drop-in hydrocarbon fuels and blend-stocks, particularly regarding information required to support air emissions or other environmental analysis. In this work, we summarize key details for an established "design case" modeling the conversion of herbaceous lignocellulosic biomass into a renewable diesel hydrocarbon blend-stock based on a representative lipid pathway from oleaginous yeast. The process is based on a biochemical deconstruction and upgrading approach utilizing deacetylation and dilute acid pretreatment, followed by enzymatic hydrolysis, fermentation, and catalytic upgrading of hydrolysate sugars to fuels. We provide key mass and energy balance outputs from the process models, with accompanying stream tables and component-level flowrates. A total of 12 model scenarios are presented spanning two feedstocks, three biorefinery scales, and two processing approaches for the lignin/residual solids waste streams. This "Part 1" manuscript presents the resulting impacts across the 12 cases on fuel yields and key output streams, focused here on direct biorefinery air emissions for selected components including CO 2 as well as sulfur (SOx) and nitrogen oxides (NOx). In the context of cleaner production, the latter focus on selected biorefinery air emission outputs establishes an initial baseline estimate and accompanying framework of the model cases, upon which an accompanying "Part 2" study will build to refine the values for these and other air pollutants across these scenarios, also considering mitigation options to comply with applicable regulatory standards. We also highlight further optimization opportunities based on potential tradeoffs identified here between air emissions versus life-cycle greenhouse gas profiles attributed to the disposition of lignin/residual solids.

09 BIOMASS FUELS↗
DOE OSTI2024

On the predictability of turbulent fluxes from land: PLUMBER2 MIP experimental description and preliminary results

Accurate representation of the turbulent exchange of carbon, water, and heat between the land surface and the atmosphere is critical for modelling global energy, water, and carbon cycles in both future climate projections and weather forecasts. Evaluation of models' ability to do this is performed in a wide range of simulation environments, often without explicit consideration of the degree of observational constraint or uncertainty and typically without quantification of benchmark performance expectations. We describe a Model Intercomparison Project (MIP) that attempts to resolve these shortcomings, comparing the surface turbulent heat flux predictions of around 20 different land models provided with in situ meteorological forcing evaluated with measured surface fluxes using quality-controlled data from 170 eddy-covariance-based flux tower sites. Predictions from seven out-of-sample empirical models are used to quantify the information available to land models in their forcing data and so the potential for land model performance improvement. Sites with unusual behaviour, complicated processes, poor data quality, or uncommon flux magnitude are more difficult to predict for both mechanistic and empirical models, providing a means of fairer assessment of land model performance. When examining observational uncertainty, model performance does not appear to improve in low-turbulence periods or with energy-balance-corrected flux tower data, and indeed some results raise questions about whether the energy balance correction process itself is appropriate. In all cases the results are broadly consistent, with simple out-of-sample empirical models, including linear regression, comfortably outperforming mechanistic land models. In all but two cases, latent heat flux and net ecosystem exchange of CO 2 are better predicted by land models than sensible heat flux, despite it seeming to have fewer physical controlling processes. Land models that are implemented in Earth system models also appear to perform notably better than stand-alone ecosystem (including demographic) models, at least in terms of the fluxes examined here. The approach we outline enables isolation of the locations and conditions under which model developers can know that a land model can improve, allowing information pathways and discrete parameterisations in models to be identified and targeted for future model development.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

District EnErgy Planner (DEEP) v2

The District EnErgy Planner - DEEP is an Mixed Integer Linear Programming (MILP) optimization software tool to solve district energy system, technology configuration, operation strategies, and energy retail business schemes. DEEP takes user input energy demand on heating, cooling and electricity demand. Energy loss through pipeline is calculated for heating and cooling from central plants. The optimal system configuration to minimize the district energy system life cycle cost or minimize CO2 emission is calculated based on energy balance equations and various constraints. The recent update on DEEP include a feature of waste heat utilization energy balance based optimization to take into accounts of different temperature bands of heat into account to maximize system efficiency. Another feature is to optimize district energy retail by provide optimal pricing scheme for heating, cooling and electricity to end users to incorporate district to grid demand response.

Feng, Wei↗
DOE OSTI2020

The Role of Subsurface Flow on Evapotranspiration: A Global Sensitivity Analysis

Abstract Water resources are impacted by water‐energy balance fluxes at the land surface, most notably evapotranspiration ( ET ), the largest component of surface energy balance. While integrated hydrologic models show promise in quantifying the nonlinear dynamics at this interface, the model results are plagued by parametric uncertainties. Given the high computational demand of running multiple parameter spaces of these models, little is known about how these uncertainties propagate into land surface processes. In this work, we perform a global sensitivity analysis by computing Sobol and AMAE indices using a surrogate model constructed with a polynomial chaos expansion to assess the impacts of the subsurface physical properties on ET . We do so by modeling a semisynthetic test case. Our results show that the effects of vertical hydraulic conductivity, porosity, and the water retention curve parameter Van Genuchten α mainly control ET . However, we note that while evaporation ( E ) shows behavior similar to the ET with high sensitivity to the parameters controlling the flow in the unsaturated zone, transpiration ( T ) is very sensitive to the saturated zone parameters and groundwater flow, especially during periods without rain. Our results also show that heterogeneities in land cover impact the flow in the saturated zone. Furthermore, our work demonstrates that reduced‐order models can be developed to make integrated models more accessible for rigorous sensitivity analyses and calibration purposes.

Maina, Fadji Zaouna↗
DOE OSTI2021

Climate Change Impacts on the South American Monsoon System and Its Surface–Atmosphere Processes Through RegCM4 CORDEX-CORE Projections

Here, we evaluate projected changes in surface water and energy balances and surface–atmosphere coupling in the South American Monsoon System (SAMS) for the end of the century (2080–2099). The analyses are based on two ensemble datasets, which follow Representative Concentration Pathway 8.5 in the future period, and cover four subdomains (Northern and Southern—NAMZ and SAMZ—Amazon, La Plata Basin—LPB, and Southern Southeast Brazil—SSB). One ensemble consists of three Global Climate Models (HadGEM2-ES, MPI-ESM-MR and NorESM1-M), while the other consists of their dynamically downscaled version at 25 km horizontal grid spacing using Regional Climate Model version 4 (RegCM4). As both ensembles are able in reproducing the annual cycle of the components of the surface water and energy balances in the present climate, they can be used in the study of future climate. During the wet season (November–March), both ensembles project a decrease in precipitation over NAMZ and SAMZ (an exception is RegCM4 that projects a slight increase in SAMZ), and an increase across the LPB and SSB. These changes do not cause retreat or expansion of the monsoon area over the continent, which is similar to the present climate (1995–2014). For the wet season, the ensembles are in line with the presence of a strong surface–atmosphere coupling in LPB and SSB, weak coupling in SAMZ and very weak coupling in NAMZ. For future climate, the coupling is even weaker in NAMZ, which may be a driver for the negative changes in precipitation. For the other subdomains, while the ensembles project similar signals of precipitation changes, they disagree with the surface-atmosphere coupling highlighting the uncertainties in future climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A rigorous physics-based enhanced parameter estimation (EPE) methodology for calibration of building energy simulations

Buildings rarely perform as designed/simulated and there are numerous tangible benefits if this gap is reconciled. A new scientifically rigorous yet pragmatic methodology for calibrating building energy simulations - called Enhanced Parameter Estimation (EPE) - is proposed that allows physically relevant parameter estimation rather than a blind force-fit to energy use data. Starting with a rapidly created simulation model, calibration is performed in two stages: (a) building shell calibration with the HVAC system replaced by an ideal system that meets the loads (b) HVAC system calibration with the building shell and all internal loads replaced by a box with only process loads. In the first stage, EPE identifies a small number of high-level heat flows in the energy balance, calculates them with specifically tailored individual driving functions, introduces physically significant parameters to best accomplish energy balance, and, estimates the parameters and their uncertainty bounds. Calibration is thus done with corrective heat flows without any arbitrary tuning of input parameters. Calibration accuracy is enhanced by machine learning of the residual errors. The EPE methodology is demonstrated by means of: a synthetic building and an actual 75,000 sq. ft. building in Pennsylvania. Future work needed for widespread application is discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Internal Material Melting Development Progress [Slides]

Slides for an AFC workshop giving a brief overview of the current status of Bison code development for correct energy balance of melting material. The slides provide background information of why the development is needed. The planned approach of casting the energy balance as a change in enthalpy is described. Status of current code additions is outlined. Extra slides are provided with more mathematical details of the approach derivation and verification.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Thermal quench induced by a composite pellet-produced plasmoid

Injecting shattered pellets is the critical concept of the envisaged ITER disruption mitigation system (DMS). Rapid deposition of large amounts of material should presumably result in controlled cooling of the entire plasma. A considerable transfer of thermal energy from the electrons of the background plasma to the ions accompanies a localized material injection due to the ambipolar expansion along the magnetic field line of the cold and dense plasmoid produced by the ablated pellet. Radiation initially plays the dominant role in the energy balance of a composite plasmoid containing high-Z impurities. A competition between the ambipolar expansion and the radiative losses defines the Thermal Quench scenario, including the amount of pre-quench thermal energy radiated on a short collisional timescale—possibly detrimental for the plasma-facing components. The present work quantifies plasmoid energy balance for disruption mitigation parameters. For pure hydrogen injection, up to 90% of the pre-pellet electron thermal energy may go to the newly injected ions. We also demonstrate that a moderate high-Z impurity content within the plasmoid can reduce highly localized radiation at the beginning of the expansion. The thermal energy will then dissipate on the much longer ion collisional timescale, which would be attractive for ITER DMS.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

On the Diffusivity of Moist Static Energy and Implications for the Polar Amplification Response to Climate Warming

Energy balance models (EBMs) have been widely used in a range of climate problems, but the assumption of constant diffusivity in the parameterization of the moist static energy (MSE) flux can be hardly justified. We demonstrate in this study that the diffusive MSE flux can be derived from the basic energy balance equation with a few tolerable assumptions. The estimated diffusivity is both spatially and seasonally dependent, and its midlatitude average is then tested against several scaling theories for the midlatitude eddy diffusivity. The result supports the diffusivity theory of Held and Larichev (1996) modified for the moist atmosphere, affording a dynamics-based parameterization of MSE diffusivity. The implementation of the parameterization in an EBM leads to an interactive MSE diffusivity that accounts for the midlatitude eddy response to climate forcing perturbations. Under a uniform radiative forcing, the EBM with a diffusivity so parameterized produces a weakening of the midlatitude diffusivity and a modestly polar-amplified surface temperature response as an inevitable outcome under the dual constraints of the nonlinear Clausius-Clapeyron relation and the temperature gradient-dependent diffusivity, even in the absence of any poleward amplifying radiative feedbacks. As the consequence of more isothermal temperature and reduced diffusivity, the variance of the midlatitude surface temperature also decreases with warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Where Are White Roofs More Effective in Cooling the Surface?

Solar reflective roofs (also called white or cool roofs) are a common heat mitigation strategy. By reflecting more sunlight than regular roofs, cool roofs experience lower surface temperatures and produce less heating of the surrounding air. The effectiveness of cool roofs, quantified by the surface temperature difference between cool roofs and regular roofs ??????, is known to vary spatially. A common perception is that ?????? is controlled by solar radiation that reaches the roof surface. Here we use an Earth System Model and a surface energy balance model to show that the spatial variability of ??????, when normalized by the albedo difference between cool roofs and regular roofs (????), is in fact more controlled by an energy distribution factor that encodes the efficiencies of surface energy balance components in dissipating heat. Our results suggest that painting the roof white is more effective in reducing the roof surface temperature when the roof has less water holding capacity and smaller thermal admittance and is located in places with more solar radiation, less precipitation, and lower wind speed.

Wang, Linying↗
DOE OSTI2023

Regional and Teleconnected Impacts of Solar Radiation‐Topography Interaction Over the Tibetan Plateau

Abstract Solar radiation‐topography interaction plays an important role in surface energy balance over the Tibetan Plateau (TP). However, the impacts of such interaction over the TP on climate locally and in the Asian regions remain unclear. This study uses the Energy Exascale Earth System Model (E3SM) to evaluate the regional and teleconnected impacts of solar radiation‐topography interaction over the TP. Land‐atmosphere coupled experiments show that topography regulates the surface energy balance, snow processes, and surface climate over the TP across seasons. Accounting for solar radiation‐topography interaction improves E3SM simulation of surface climate. The winter cold bias in air temperature decreases from −4.57 to −3.79 K, and the wet bias in summer precipitation is mitigated in southern TP. The TP's solar radiation‐topography interaction further reduces the South and East Asian summer precipitation biases. Our results demonstrate the topographic roles in regional climate over the TP and highlight its teleconnected climate impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Development of Steady-State and Dynamic Mass and Energy Constrained Neural Networks for Distributed Chemical Systems Using Noisy Transient Data

The paper presents the development of algorithms for mass and energy constrained neural network models that can exactly conserve the overall mass and energy of distributed chemical process systems, even though the noisy transient data used for optimal model training violate the same. In contrast to approximately satisfying mass and energy balance constraints of a system by soft penalization of objective function, algorithms have been developed for solving equality-constrained nonlinear optimization problems, thus providing the guarantee of exactly satisfying the system mass and energy conservation laws. For developing dynamic mass-energy constrained network models for distributed systems, hybrid series and parallel dynamic-static neural networks have been leveraged. The developed algorithms for solving both the training and forward problems are validated using both steady-state and dynamic data in the presence of various noise characteristics. The developed data-driven algorithms are flexible to exactly satisfy mass and energy balance constraints for dynamic chemical processes if the system holdup information is available. The proposed network structures and algorithms are applied to the development of data-driven lumped and distributed models of an adiabatic superheater/reheater system, a nonisothermal continuous stirred tank reactor, as well as an electrically heated plug-flow reactor system where one form of energy gets transformed to another. It has been observed that the mass-energy constrained neural networks yield a root mean squared error of <1% with respect to the system truth for the case studies evaluated in this work.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A Surface Radiation Balance Dataset from Siple Dome in West Antarctica for Atmospheric and Climate Model Evaluation

Abstract A field campaign at Siple Dome in West Antarctica during the austral summer 2019/20 offers an opportunity to evaluate climate model performance, particularly cloud microphysical simulation. Over Antarctic ice sheets and ice shelves, clouds are a major regulator of the surface energy balance, and in the warm season their presence occasionally induces surface melt that can gradually weaken an ice shelf structure. This dataset from Siple Dome, obtained using transportable and solar-powered equipment, includes surface energy balance measurements, meteorology, and cloud remote sensing. To demonstrate how these data can be used to evaluate model performance, comparisons are made with meteorological reanalysis known to give generally good performance over Antarctica (ERA5). Surface albedo measurements show expected variability with observed cloud amount, and can be used to evaluate a model’s snowpack parameterization. One case study discussed involves a squall with northerly winds, during which ERA5 fails to produce cloud cover throughout one of the days. A second case study illustrates how shortwave spectroradiometer measurements that encompass the 1.6- μ m atmospheric window reveal cloud phase transitions associated with cloud life cycle. Here, continuously precipitating mixed-phase clouds become mainly liquid water clouds from local morning through the afternoon, not reproduced by ERA5. We challenge researchers to run their various regional or global models in a manner that has the large-scale meteorology follow the conditions of this field campaign, compare cloud and radiation simulations with this Siple Dome dataset, and potentially investigate why cloud microphysical simulations or other model components might produce discrepancies with these observations. significance statement Antarctica is a critical region for understanding climate change and sea level rise, as the great ice sheets and the ice shelves are subject to increasing risk as global climate warms. Climate models have difficulties over Antarctica, particularly with simulation of cloud properties that regulate snow surface melting or refreezing. Atmospheric and climate-related field work has significant challenges in the Antarctic, due to the small number of research stations that can support state-of-the-art equipment. Here we present new data from a suite of transportable and solar-powered instruments that can be deployed to remote Antarctic sites, including regions where ice shelves are most at risk, and we demonstrate how key components of climate model simulations can be evaluated against these data.

54 ENVIRONMENTAL SCIENCES↗