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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Carbon management technology pathways for reaching a U.S. Economy-Wide net-Zero emissions goal

The Carbon Management Study Group of the 37 th Energy Modeling Forum (EMF 37) designed seven scenarios to explore the role of three potentially key technology suites – point source carbon dioxide capture and storage (PSCCS), direct air capture of carbon dioxide (DACCS), and hydrogen systems (H 2 ) – in shaping the broader technology pathways to reaching net-zero carbon dioxide (CO 2 ) emissions in United States by 2050. Each scenario was run by up to 13 models participating in the EMF 37 study. Results show that carbon dioxide removal technologies were consistently a major part of successful pathways to net-zero U.S. CO 2 emissions in 2050. Achieving this net-zero CO 2 goal without any form of carbon dioxide capture and storage was found to be impossible for most models; some models also found it impossible to reach net-zero without DACCS. The marginal cost of achieving net-zero CO 2 emissions in 2050 was between two and 10 times higher without PSCCS and/or DACCS available. The carbon price at which DACCS was deployed as a backstop technology depended upon the assumed cost at which DACCS was available at scale. Carbon prices were between $\$$250 and $\$$500 per ton CO 2 when DACCS deployed as a backstop. The average CO 2 capture rate across all models in 2050 in the central net-zero scenario was 1.3 GtCO 2 /year, which implies a substantial upscaling of capacity to move and store CO 2 . Finally, hydrogen sensitivity scenarios showed that H 2 typically constituted a relatively small share of the overall U.S. energy system; however, H 2 deployed in applications that are considered hard to decarbonize, facilitating transition towards net-zero emissions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1980

Solar energy market penetration models - Science or number mysticism

The forecast market potential of a solar technology is an important factor determining its R&D funding. Since solar energy market penetration models are the method used to forecast market potential, they have a pivotal role in a solar technology's development. This paper critiques the applicability of the most common solar energy market penetration models. It is argued that the assumptions underlying the foundations of rigorously developed models, or the absence of a reasonable foundation for the remaining models, restrict their applicability.

Warren, E. H., Jr.↗
DOE OSTI2014

Smart and Green Energy (SAGE) for Base Camps Final Report

The U.S. Army Logistics Innovation Agency’s (LIA’s) Smart and Green Energy (SAGE) for Base Camps project was to investigate how base camps’ fuel consumption can be reduced by 30% to 60% using commercial off-the-shelf (COTS) technologies for power generation, renewables, and energy efficient building systems. Field tests and calibrated energy models successfully demonstrated that the fuel reductions are achievable.

energy↗
DOE OSTI2016

Advancing Replicable Solutions for High-Performance Homes in the Southeast

The work presented in this report advances the goals of the U.S. Department of Energy Building America program by improving the energy performance of affordable and market-rate housing. Southface Energy Institute (Southface), part of the U.S. Department of Energy Building America research team Partnership for Home Innovation, worked with owners and builders with various market constraints and ultimate goals for three projects in three climate zones (CZs): Savannah Gardens in Savannah, Georgia (CZ 2); JMC Patrick Square in Clemson, South Carolina (CZ 3); and LaFayette in LaFayette, Georgia (CZ 4). This report documents the design process, computational energy modeling, construction, envelope performance metrics, long-term monitoring results, and successes and failures of the design and execution of these high-performance homes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Probing Time-dependent Dark Energy with the Flux Power Spectrum of the Ly$α$ Forest

Herein we present new simulations of the flux power spectrum of the Ly$α$ forest as a means to investigate the effects of time-dependent dark energy on structure formation. We use a linearized parameterization of the time-dependence of the dark energy equation of state and sample the parameters ($w_0, w_a$) from the extrema of the allowed observational values as determined by the Planck results. Each chosen ($w_0, w_a$) pair is then used in a high-resolution, large-scale cosmological simulation run with a modified version of the publicly available SPH code GADGET-2 . From each of these simulations we extract synthetic Ly$α$ forest spectra and calculate the flux power spectrum. We use the $k$-sample Anderson–Darling test to analyze the effects of dark energy on the Ly$α$ forest. We compare each dark energy power spectrum to that due to a cosmological constant power spectrum. We find, however, that there is only a marginal effect of the choice of allowed dark energy models on the flux power spectrum.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Incorporating Electronic Information into Machine Learning Potential Energy Surfaces via Approaching the Ground-State Electronic Energy as a Function of Atom-Based Electronic Populations

Machine learning (ML) approximations to density functional theory (DFT) potential energy surfaces (PESs) are showing great promise for reducing the computational cost of accurate molecular simulations, but at present, they are not applicable to varying electronic states, and in particular, they are not well suited for molecular systems in which the local electronic structure is sensitive to the medium to long-range electronic environment. With this issue as the focal point, we present a new machine learning approach called "BpopNN" for obtaining efficient approximations to DFT PESs. Conceptually, the methodology is based on approaching the true DFT energy as a function of electron populations on atoms; in practice, this is realized with available density functionals and constrained DFT (CDFT). Additionally, the new approach creates approximations to this function with neural networks. These approximations thereby incorporate electronic information naturally into a ML approach, and optimizing the model energy with respect to populations allows the electronic terms to self-consistently adapt to the environment, as in DFT. We confirm the effectiveness of this approach with a variety of calculations on LinHn clusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Constraining the cosmic deceleration-acceleration transition with type Ia supernova, BAO/CMB and H(z) data

We revisit the kink-like parametrization of the deceleration parameter q(z) [1], which considers a transition, at redshift z{sub t}, from cosmic deceleration to acceleration. In this parametrization the initial, at z >> z{sub t}, value of the q-parameter is q{sub i}, its final, z=−1, value is q{sub f} and the duration of the transition is parametrized by τ. By assuming a flat space geometry we obtain constraints on the free parameters of the model using recent data from type Ia supernovae (SN Ia), baryon acoustic oscillations (BAO), cosmic microwave background (CMB) and the Hubble parameter H(z). The use of H(z) data introduces an explicit dependence of the combined likelihood on the present value of the Hubble parameter H{sub 0}, allowing us to explore the influence of different priors when marginalizing over this parameter. We also study the importance of the CMB information in the results by considering data from WMAP7, WMAP9 (Wilkinson Microwave Anisotropy Probe—7 and 9 years) and Planck 2015. We show that the contours and best fit do not depend much on the different CMB data used and that the considered new BAO data is responsible for most of the improvement in the results. Assuming a flat space geometry, q{sub i}=1/2 and expressing the present value of the deceleration parameter q{sub 0} as a function of the other three free parameters, we obtain z{sub t}=0.67{sup +0.10}{sub −0.08}, τ=0.26{sup +0.14}{sub −0.10} and q{sub 0}=−0.48{sup +0.11}{sub −0.13}, at 68% of confidence level, with an uniform prior over H{sub 0}. If in addition we fix q{sub f}=−1, as in flat ΛCDM, DGP and Chaplygin quartessence that are special models described by our parametrization, we get z{sub t}=0.66{sup +0.03}{sub −0.04}, τ=0.33{sup +0.04}{sub −0.04} and q{sub 0}=−0.54{sup +0.05}{sub −0.07}, in excellent agreement with flat ΛCDM for which τ=1/3. We also obtain for flat wCDM, another dark energy model described by our parametrization, the constraint on the equation of state parameter −1.22 < w < −0.78 at more than 99% confidence level.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Results and Lessons Learned From the DOE Commercial Building Partnerships: Preprint

Over the course of 5 years, NREL worked with commercial building owners and their design teams in the DOE Commercial Building Partnerships (CBP) to cut energy consumption by 50% in new construction (versus code) and by 30% in existing building pilot projects (versus code or pre-retrofit operational energy use depending on the preference of the Partner) using strategies that could be replicated across their building portfolios. A number of different building types were addressed, including supermarket, retail merchandise, combination big box (general merchandise and food sales), high rise office space, and warehouse. The projects began in pre-design and included a year of measurement data to evaluate performance against design expectations. Focused attention was required throughout the entire process to achieve a design with the potential to hit the energy performance target and to operate the resulting building to reach this potential. This paper will report quantitative results and cover both the technical and the human sides of CBP, including the elements that were required to succeed and where stumbling blocks were encountered. It will also address the impact of energy performance goals and intensive energy modeling on the design process innovations and best practices.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

The value of integrating a geothermal district heating system into a microgrid

As electrical grids increasingly rely on variable renewable energy, maintaining reliability and cost efficiency becomes more complex. To address these challenges, this study analyzed the integration of geothermal district heating as a grid-responsive thermal resource within a microgrid in Tuttle, Oklahoma. Building energy modeling using EnergyPlus estimated annual district heating demand at 2.9 GWh, with a peak load of 2.8 MW th . Techno-economic analyses were conducted to meet the heating demand under three geothermal scenarios, varying by production depth, flow rate, and thermal output, each supplemented by natural gas peaking boilers. In parallel, equivalent electrical load profiles were developed using typical coefficients of performance (COPs) for air-source heat pumps and electric boilers to establish an electrified baseline scenario. A complete end-use electrical load profile was also developed for the microgrid using Cambium dataset. The modeling results demonstrated reliable and economic operation of the geothermal systems over 30 years, with COPs ranging from 2.6 to 8.9 and the lowest levelized heating cost at $\$$54.6/MWh. Geothermal integration reduced electricity consumption by up to 94.7 % compared to the non-geothermal base case, yielding annual energy savings of up to $\$$803 k. Avoided grid costs ranged from $\$$65 k–$\$$147 k per year, with individual events avoiding up to $\$$4,863 per hour. Grid-responsive operation further reduced wholesale energy costs by 53–56 %. These findings demonstrate geothermal heating, traditionally treated as a non-grid-responsive thermal resource, can be reconfigured to support dynamic grid services, offering a scalable pathway to enhance reliability and reduce costs in renewable-rich microgrids and district heating networks.

15 GEOTHERMAL ENERGY↗
DOE OSTI2013

Energize New York -- Residential Energy Efficiency Market Transformation in New York

Energize New York (ENY) is focused on addressing known barriers to widespread energy efficiency (EE) adoption by property owners. In simple terms ENY works to; 1) increase homeowner trust by using known and trusted community leaders to communicate their own positive experiences with EE and ENY, 2) reduce friction points by integrating support staff and creative use of technology that ease a homeowner’s way forward through the EE upgrade process, 3) increase homeowner knowledge and trust of specific EE benefits through access to the ENY energy coach, 4) provide information on available financing options that show benefits (e.g. positive cash flow), and 5) provide tools and mechanisms that give homeowners greater comfort in evaluating and selecting the right contractor. These five fundamental program aspects are supported by a hyper-local communications and outreach model and a “lead by example” philosophy that requires community leaders to step forward and model energy efficiency behavior by example. In the communities where the program has successfully engaged local leadership and “trusted community sources” there has been a significant increase in the uptake of energy efficiency work. Quantitatively this growth translated into an increase of 240% in completed Home Performance projects from the two year pre-pilot period (2009-10) to the two year post-pilot period (2012-13). Additionally, the program has seen measureable increases in the output and performance of contractors who are members of the Energize Comfort Corps, a program innovation which included a subset of the NYSERDA approved and Building Performance Institute accredited home performance contractors. This innovation, launched in the later stages of the pilot, is paired with the Energize Contractor Ratings Index (CRI) and helps frame the provider market by giving homeowners a mechanism to provide and receive feedback on their contractor experience. The data incorporated into the CRI along with the ECC selection process, has measurably reduced a key decision barrier (“which contractor should I use”) for homeowners engaged in the EE decision making process.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Sustain

Current building energy simulation technology requires excessive labor, time and expertise to create building energy models, excessive computational time for accurate simulations and difficulties with the interpretation of the results. These deficiencies can be ameliorated using modern graphical user interfaces and algorithms which take advantage of modern computer architectures and display capabilities. To prove this hypothesis, we developed an experimental test bed for building energy simulation. This novel test bed environment offers an easy-to-use interactive graphical interface, provides access to innovative simulation modules that run at accelerated computational speeds, and presents new graphics visualization methods to interpret simulation results. Our system offers the promise of dramatic ease of use in comparison with currently available building energy simulation tools. Its modular structure makes it suitable for early stage building design, as a research platform for the investigation of new simulation methods, and as a tool for teaching concepts of sustainable design. Improvements in the accuracy and execution speed of many of the simulation modules are based on the modification of advanced computer graphics rendering algorithms. Significant performance improvements are demonstrated in several computationally expensive energy simulation modules. The incorporation of these modern graphical techniques should advance the state of the art in the domain of whole building energy analysis and building performance simulation, particularly at the conceptual design stage when decisions have the greatest impact. More importantly, these better simulation tools will enable the transition from prescriptive to performative energy codes, resulting in better, more efficient designs for our future built environment.

Source record↗
DOE OSTI2023

The Energetic Origins of Pi–Pi Contacts in Proteins

Accurate potential energy models of proteins must describe the many different types of noncovalent interactions that contribute to a protein’s stability and structure. Pi–pi contacts are ubiquitous structural motifs in all proteins, occurring between aromatic and nonaromatic residues and play a nontrivial role in protein folding and in the formation of biomolecular condensates. Guided by a geometric criterion for isolating pi–pi contacts from classical molecular dynamics simulations of proteins, we use quantum mechanical energy decomposition analysis to determine the molecular interactions that stabilize different pi–pi contact motifs. We find that neutral pi–pi interactions in proteins are dominated by Pauli repulsion and London dispersion rather than repulsive quadrupole electrostatics, which is central to the textbook Hunter–Sanders model. This results in a notable lack of variability in the interaction profiles of neutral pi–pi contacts even with extreme changes in the dielectric medium, explaining the prevalence of pi-stacked arrangements in and between proteins. We also find interactions involving pi-containing anions and cations to be extremely malleable, interacting like neutral pi–pi contacts in polar media and like typical ion–pi interactions in nonpolar environments. Like-charged pairs such as arginine–arginine contacts are particularly sensitive to the polarity of their immediate surroundings and exhibit canonical pi–pi stacking behavior only if the interaction is mediated by environmental effects, such as aqueous solvation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Impact of Photon Recycling, Grain Boundaries, and Nonlinear Recombination on Energy Transport in Semiconductors

Energy carrier transport and recombination in semiconductors can be directly monitored with optical microscopy, revealing key insights into fundamental photophysics and informs efficient optoelectronic device design. Oftentimes, energy transport is measured by monitoring a time-resolved expanding carrier profile after optical excitation under a focused laser beam. Although this approach has gained widespread adoption, the presence of competing dynamic processes, such as diffusion and photon recycling, has made it difficult to accurately extract and understand important semiconductor properties. Here, we develop and apply a new framework for modeling energy transport in both excitonic and free carrier semiconductors. Here, we demonstrate that processes such as nonlinear recombination and photon recycling can have a significant impact on the apparent energy carrier profiles, especially for excitonic materials with short radiative lifetimes. Additionally, we find that film microstructure can lead to unique transport profiles that strongly depends on material boundary behavior and the difference between feature size and diffusion length. Here, these findings provide a deeper understanding of energy transport in semiconducting materials and provide new strategies for the design and optimization of electronic and optoelectronic devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Downfolding of many-body Hamiltonians using active-space models: Extension of the sub-system embedding sub-algebras approach to unitary coupled cluster formalisms

Here, we discuss the extension of the recently introduced subsystem embedding subalgebra coupled cluster (SES-CC) formalism to unitary CC formalisms. In analogy to the standard single-reference SES-CC formalism, its unitary CC extension allows one to include the dynamical (outside the active space) correlation effects in an SES induced complete active space (CAS) effective Hamiltonian. In contrast to the standard single-reference SES-CC theory, the unitary CC approach results in a Hermitian form of the effective Hamiltonian. Additionally, for the double unitary CC (DUCC) formalism, the corresponding CAS eigenvalue problem provides a rigorous separation of external cluster amplitudes that describe dynamical correlation effects—used to define the effective Hamiltonian—from those corresponding to the internal (inside the active space) excitations that define the components of eigenvectors associated with the energy of the entire system. The proposed formalism can be viewed as an efficient way of downfolding many-electron Hamiltonian to the low-energy model represented by a particular choice of CAS. In principle, this technique can be extended to any type of CAS representing an arbitrary energy window of a quantum system. The Hermitian character of low-dimensional effective Hamiltonians makes them an ideal target for several types of full configuration interaction type eigensolvers. As an example, we also discuss the algebraic form of the perturbative expansions of the effective DUCC Hamiltonians corresponding to composite unitary CC theories and discuss possible algorithms for hybrid classical and quantum computing. Given growing interest in quantum computing, we provide energies for H 2 and Be systems obtained with the quantum phase estimator algorithm available in the Quantum Development Kit for the approximate DUCC Hamiltonians.

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

Thermo-Hydrological Modeling of Thermal Energy Storage in a Depleted Oil Reservoir

Thermal energy storage in oil and gas reservoirs leverages the existing surface and subsurface infrastructure, which can pave the way for economic production of geothermal energy. Existing studies on geothermal energy storage are focused mostly on the use of aquifers with more homogeneous rock and fluid properties. Coupling of heat and fluid flow in a multiphase-multicomponent system, such as an oil reservoir, is imperative especially if existing oil field assets need to be repurposed as required for a sustainable energy transition. The objective is to model the subsurface thermo-hydrological processes associated with reservoir performance and operational sustainability. The model evaluates formation pressure and temperature within the reservoir and at the injection/production wells during multiple charge and discharge cycles. Hot water (approximately 200 degrees C) heated by Concentrating Solar Power (CSP) at high pressure is injected into the existing oil reservoir for storage and produced as thermal energy for power generation, which will be accompanied by enhanced oil recovery. To demonstrate the coupled fluid and heat flow during the injection/production cycle in the subsurface reservoir, TOUGH3 (developed by Berkeley Lab) is used to simulate the thermo-hydrological (TH) processes in a multiphase, multicomponent system. Two well geometries are considered within the reservoir grid: 1) a single-well huff-n-puff system (same well is used for injection and production), and 2) an isolated injection-production well doublet. Seasonal charge and discharge cycling are implemented based on the scheduling specified in the model input file. The model reports pressure, temperature, enthalpy, liquid fluxes, heat fluxes, pore velocities, and changes in porosity & permeability due to temperature and pressure variations during the cyclic Reservoir Thermal Energy Storage (RTES) operations. The results from the simulations can be used to optimize the operational parameters (such as well spacing and injection/production rates) and round-trip efficiency for surface power-plants coupled with thermal energy storage over time. They can also serve as important inputs for levelized cost of storage estimations. The research will help to design and integrate surface renewable energy sources, such as concentrating solar power (CSP), with RTES to help balance out power supply and demand on the grid.

CSP↗
DOE OSTI2022

Electronic structure, magnetic properties, and pairing tendencies of the copper-based honeycomb lattice Na 2 Cu 2 TeO 6

Spin-1/2 chains with alternating antiferromagnetic (AFM) and ferromagnetic (FM) couplings have attracted considerable interest due to the topological character of their spin excitations. Here, using density functional theory and density-matrix renormalization-group (DMRG) methods, we have systematically studied the dimerized chain system Na 2 Cu 2 TeO 6 with a d 9 electronic configuration. Near the Fermi level, in the nonmagnetic phase the dominant states are mainly contributed by the Cu 3d x 2 -y 2 orbitals highly hybridized with the O 2p orbitals, leading to an “effective” single-orbital low-energy model. By calculating the relevant hoping amplitudes, we explain the size and sign of the exchange interactions in Na 2 Cu 2 TeO 6 . In addition, a single-orbital Hubbard model is constructed for this dimerized chain system where the quantum fluctuations are taken into account. Both AFM and FM couplings (leading to an ↑|-|↓-|↓-↑| state) along the chain were found in our DMRG and Lanczos calculations, in agreement with density functional theory and neutron-scattering results. The hole pairing binding energy ΔE is predicted to be negative at Hubbard U~ 11eV, suggesting incipient pairing tendencies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Multidisciplinary Constraints on the Thermal‐Chemical Boundary Between Earth's Core and Mantle

Abstract Heat flux from the core to the mantle provides driving energy for mantle convection thus powering plate tectonics, and contributes a significant fraction of the geothermal heat budget. Indirect estimates of core‐mantle boundary heat flow are typically based on petrological evidence of mantle temperature, interpretations of temperatures indicated by seismic travel times, experimental measurements of mineral melting points, physical mantle convection models, or physical core convection models. However, previous estimates have not consistently integrated these lines of evidence. In this work, an interdisciplinary analysis is applied to co‐constrain core‐mantle boundary heat flow and test the thermal boundary layer (TBL) theory. The concurrence of TBL models, energy balance to support geomagnetism, seismology, and review of petrologic evidence for historic mantle temperatures supports Q CMB ∼15 TW, with all except geomagnetism supporting as high as ∼20 TW. These values provide a tighter constraint on core heat flux relative to previous work. Our work describes the seismic properties consistent with a TBL, and supports a long‐lived basal mantle molten layer through much of Earth's history.

58 GEOSCIENCES↗