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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Key Drivers for Offshore Wind Deployment in the Western United States

The western coast of the United States has abundant natural resources, including wind, sun, and water. Despite strong ocean winds, offshore wind energy (OSW) in the Western United States is in the early stages of technology development due largely to the deep water off the coast, which requires floating platforms rather than fixed‐bottom turbines. Floating OSW increases the technical difficulty of installation and thus the cost relative to both fixed‐bottom OSW and land‐based turbines. OSW is a potential generation option to help meet increasing demand on the west coast of the United States because it likely has fewer land‐use conflicts than other technologies and complements sources in the existing electricity supply by providing energy during times of high system stress. This paper examines the possible drivers and barriers to OSW deployment on the West Coast using the National Laboratory of the Rockies' state‐of‐the‐art capacity expansion model and the Regional Energy Deployment System (ReEDS) model. We use ReEDS to explore a multitude of future scenarios looking at key drivers for OSW deployment, including variations on the cost of OSW, electricity demand growth, and the availability of competing technologies to examine the factors that may play a role in OSW growth. Assuming coastal state policies such as renewable portfolio and clean energy standards remain in place, we find that OSW can play a role in meeting electricity demand and provide energy during stressful grid conditions and find that deployment from the least‐cost investment model ranges from 7.6 to 38 GW by 2045.

17 WIND ENERGY↗
DOE OSTI2026

Impact of vertical and seasonal variation in leaf traits on simulating soybean canopy photosynthesis via 1D and 3D modeling

Accurate modeling of photosynthesis is crucial for predicting crop productivity and quantifying the carbon cycle in agroecosystems. Leaf traits are essential inputs for modeling canopy photosynthesis. Yet, many existing models still use fixed plant functional type (PTF)-based values to parameterize leaf traits under a big-leaf or two-big-leaf assumption, neglecting their vertical profiles and seasonal changes. This simplification may introduce significant uncertainties in estimating gross primary productivity (GPP). In this study, we simulated soybean GPP and tested the effects of vertical and seasonal variation in three key leaf photosynthetic traits: the maximum carboxylation rate at 25 °C (Vcmax 25 ), leaf chlorophyll content (LCC), and leaf mass per area (LMA) in the 1D-SCOPE and 3D-Helios models. Weekly field measurements were conducted during the growing season of 2024 to support the simulation. We designed ten leaf trait parameterization schemes by incorporating different combinations of vertical profiles and seasonal changes, while assuming homogeneous canopy architecture in both models. Our results revealed that Vcmax 25 vertical and seasonal variation had the strongest influence on simulated GPP in both 1D and 3D models, while LCC and LMA effects were minimal. Particularly, the scheme with an empirically parameterized Vcmax 25 profile achieved comparable performance to the scheme with the measured Vcmax 25 profile. Both 1D-SCOPE and 3D-Helios accurately modeled GPP (SCOPE: R 2 = 0.87, Bias = 0.55 µmol m⁻² s⁻¹; Helios: R 2 = 0.9, Bias = 0.22 µmol m⁻² s⁻¹) under the most complex scheme, and their responses to vertical and seasonal variation in leaf traits were consistent, demonstrating the robustness of our findings. Based on our findings, we propose a scalable framework for parameterizing leaf traits to improve GPP simulations. This study contributes to improving the representation of leaf trait dynamics in canopy-level photosynthesis models, potentially enhancing our ability to predict crop productivity and understand agroecosystem carbon dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Impact of residential PV adoption on Retail Electricity Rates

The price of electricity supplied from home rooftop photo voltaic (PV) solar cells has fallen below the retail price of grid electricity in some areas. A number of residential households have an economic incentive to install rooftop PV systems and reduce their purchases of electricity from the grid. A significant portion of the costs incurred by utility companies are fixed costs which must be recovered even as consumption falls. Electricity rates must increase in order for utility companies to recover fixed costs from shrinking sales bases. Increasing rates will, in turn, result in even more economic incentives for customers to adopt rooftop PV. In this paper, we model this feedback between PV adoption and electricity rates and study its impact on future PV penetration and net-metering costs. We find that the most important parameter that determines whether this feedback has an effect is the fraction of customers who adopt PV in any year based solely on the money saved by doing so in that year, independent of the uncertainties of future years. These uncertainties include possible changes in rate structures such as the introduction of connection charges, the possibility of PV prices dropping significantly in the future, possible changes in tax incentives, and confidence in the reliability and maintainability of PV. (C) 2013 Elsevier Ltd. All rights reserved.

Cai, DWH↗
DOE OSTI2023

ECCE sensitivity studies for single hadron transverse single spin asymmetry measurements

Here, we performed feasibility studies for various single transverse spin measurements that are related to the Sivers effect, transversity and the tensor charge, and the Collins fragmentation function. The processes studied include semi-inclusive deep inelastic scattering (SIDIS) where single hadrons (pions and kaons) were detected in addition to the scattered DIS lepton. The data were obtained in pythia6 and geant4 simulated e+p collisions at 18 GeV on 275 GeV, 18 on 100, 10 on 100, and 5 on 41 that use the ECCE detector configuration. Typical DIS kinematics were selected, most notably Q 2 >1 GeV 2 , and cover the x range from 10 -4 to 1. The single spin asymmetries were extracted as a function of x and Q 2 , as well as the semi-inclusive variables z, which corresponds to the momentum fraction the detected hadron carries relative to the struck parton, and P T , which corresponds to the transverse momentum of the detected hadron relative to the virtual photon. They are obtained in azimuthal moments in combinations of the azimuthal angles of the hadron transverse momentum and transverse spin of the nucleon relative to the lepton scattering plane. In order to extract asymmetries, the initially unpolarized MonteCarlo was re-weighted in the true kinematic variables, hadron types and parton flavors based on global fits of fixed target SIDIS experiments and e + e – annihilation data. The expected statistical precision of such measurements is extrapolated to 10 fb –1 and potential systematic uncertainties are approximated given the deviations between true and reconstructed yields. Similar neutron information is obtained by comparing the ECCE e+p pseudo-data with the same from the EIC Yellow Report and scaling the corresponding Yellow Report e+ 3 He pseudo-data uncertainties accordingly. The impact on the knowledge of the Sivers functions, transversity and tensor charges, and the Collins function has then been evaluated in the same phenomenological extractions as in the Yellow Report. Finally, the impact is found to be comparable to that obtained with the parametrized Yellow Report detector and shows that the ECCE detector configuration can fulfill the physics goals on these quantities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Predicting Energetics Materials’ Crystalline Density from Chemical Structure by Machine Learning

To expedite new molecular compound development, a long-sought goal within the chemistry community has been to predict molecules’ bulk properties of interest a priori to synthesis from a chemical structure alone. In this work, we demonstrate that machine learning methods can indeed be used to directly learn the relationship between chemical structures and bulk crystalline properties of molecules, even in the absence of any crystal structure information or quantum mechanical calculations. We focus specifically on a class of organic compounds categorized as energetic materials called high explosives (HE) and predicting their crystalline density. An ongoing challenge within the chemistry machine learning community is deciding how best to featurize molecules as inputs into machine learning models—whether expert handcrafted features or learned molecular representations via graph-based neural network models—yield better results and why. We evaluate both types of representations in combination with a number of machine learning models to predict the crystalline densities of HE-like molecules curated from the Cambridge Structural Database, and we report the performance and pros and cons of our methods. Our message passing neural network (MPNN) based models with learned molecular representations generally perform best, outperforming current state-of-the-art methods at predicting crystalline density and performing well even when testing on a data set not representative of the training data. However, these models are traditionally considered black boxes and less easily interpretable. Here, to address this common challenge, we also provide a comparison analysis between our MPNN-based model and models with fixed feature representations that provides insights as to what features are learned by the MPNN to accurately predict density.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Prediction of interest rate using CKLS model with stochastic parameters

The Chan, Karolyi, Longstaff and Sanders (CKLS) model is a popular one-factor model for describing the spot interest rates. In this paper, the four parameters in the CKLS model are regarded as stochastic. The parameter vector φ{sup (j)} of four parameters at the (J+n)-th time point is estimated by the j-th window which is defined as the set consisting of the observed interest rates at the j′-th time point where j≤j′≤j+n. To model the variation of φ{sup (j)}, we assume that φ{sup (j)} depends on φ{sup (j−m)}, φ{sup (j−m+1)},…, φ{sup (j−1)} and the interest rate r{sub j+n} at the (j+n)-th time point via a four-dimensional conditional distribution which is derived from a [4(m+1)+1]-dimensional power-normal distribution. Treating the (j+n)-th time point as the present time point, we find a prediction interval for the future value r{sub j+n+1} of the interest rate at the next time point when the value r{sub j+n} of the interest rate is given. From the above four-dimensional conditional distribution, we also find a prediction interval for the future interest rate r{sub j+n+d} at the next d-th (d≥2) time point. The prediction intervals based on the CKLS model with stochastic parameters are found to have better ability of covering the observed future interest rates when compared with those based on the model with fixed parameters.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Toward more accurate adiabatic connection approach for multireference wavefunctions

A multiconfigurational adiabatic connection (AC) formalism is an attractive approach to compute the dynamic correlation within the complete active space self-consistent field and density matrix renormalization group (DMRG) models. Practical realizations of AC have been based on two approximations: (i) fixing one- and two-electron reduced density matrices (1- and 2-RDMs) at the zero-coupling constant limit and (ii) extended random phase approximation (ERPA). This work investigates the effect of removing the “fixed-RDM” approximation in AC. The analysis is carried out for two electronic Hamiltonian partitionings: the group product function- and the Dyall Hamiltonians. Exact reference AC integrands are generated from the DMRG full configuration interaction solver. Two AC models are investigated, employing either exact 1- and 2-RDMs or their second-order expansions in the coupling constant in the ERPA equations. Calculations for model molecules indicate that lifting the fixed-RDM approximation is a viable way toward improving the accuracy of existing AC approximations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2011

Asymptotically Safe Lorentzian Gravity

The gravitational asymptotic safety program strives for a consistent and predictive quantum theory of gravity based on a nontrivial ultraviolet fixed point of the renormalization group (RG) flow. We investigate this scenario by employing a novel functional renormalization group equation which takes the causal structure of space-time into account and connects the RG flows for Euclidean and Lorentzian signature by a Wick rotation. Within the Einstein-Hilbert approximation, the {beta} functions of both signatures exhibit ultraviolet fixed points in agreement with asymptotic safety. Surprisingly, the two fixed points have strikingly similar characteristics, suggesting that Euclidean and Lorentzian quantum gravity belong to the same universality class at high energies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

SU-E-J-25: End-To-End (E2E) Testing On TomoHDA System Using a Real Pig Head for Intracranial Radiosurgery

Purpose: To determine the MVCT imaging uncertainty on the TomoHDA system for intracranial radiosurgery treatments. To determine the end-to-end (E2E) overall accuracy of the TomoHDA system for intracranial radiosurgery. Methods: A pig head was obtained from the butcher, cut coronally through the brain, and preserved in formaldehyde. The base of the head was fixed to a positioning plate allowing precise movement, i.e. translation and rotation, in all 6 axes. A repeatability test was performed on the pig head to determine uncertainty in the image bone registration algorithm. Furthermore, the test studied images with MVCT slice thicknesses of 1 and 3 mm in unison with differing scan lengths. A sensitivity test was performed to determine the registration algorithm’s ability to find the absolute position of known translations/rotations of the pig head. The algorithm’s ability to determine absolute position was compared against that of manual operators, i.e. a radiation therapist and radiation oncologist. Finally, E2E tests for intracranial radiosurgery were performed by measuring the delivered dose distributions within the pig head using Gafchromic films. Results: The repeatability test uncertainty was lowest for the MVCTs of 1-mm slice thickness, which measured less than 0.10 mm and 0.12 deg for all axes. For the sensitivity tests, the bone registration algorithm performed better than human eyes and a maximum difference of 0.3 mm and 0.4 deg was observed for the axes. E2E test results in absolute position difference measured 0.03 ± 0.21 mm in x-axis and 0.28 ± 0.18 mm in y-axis. A maximum difference of 0.32 and 0.66 mm was observed in x and y, respectively. The average peak dose difference between measured and calculated dose was 2.7 cGy or 0.4%. Conclusion: Our tests using a pig head phantom estimate the TomoHDA system to have a submillimeter overall accuracy for intracranial radiosurgery.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2011

Investigations on Repository Near-Field Thermal Modeling - Repository Science/Thermal Load Management & Design Concepts (M41UF033302)

The various layers of material from the waste package (such as components of the engineered barrier system and the host rock surface) to a given distance within the rock wall at a given distance can be described as concentric circles with varying thermal properties (see Figure 5.1-1). The selected model approach examines the contributions of the waste package, axial waste package neighbors and lateral neighboring emplacement drifts (see Section 5.2.1 and Appendix H, Section 2). In clay and deep borehole media, the peak temperature is driven by the central waste package whereas, in granite and salt, the contribution to the temperature rise by adjacent (lateral) waste packages in drift or emplacement borehole lines is dominant at the time of the peak temperature. Mathematical models generated using Mathcad software provide insight into the effects of changing waste package spacing for six waste forms, namely UOX, MOX, co-extraction, new extraction, E-Chem ceramic and E-Chem metal in four different geologic media (granite, clay, salt and deep borehole). Each scenario includes thermal conductivity and diffusivity for each layer between the waste package and the host rock, dimensions of representative repository designs (such as waste package spacing, drift or emplacement borehole spacing, waste package dimensions and layer thickness), and decay heat curves generated from knowledge of the contents of a given waste form after 10, 50, 100 and 200 years of surface storage. Key results generated for each scenario include rock temperature at a given time calculated at a given radius from the central waste package (Section 5.2.1 and Appendix H, Section 3), the corresponding temperature at the interface of the waste package and EBS material, and at each EBS layer in between (Section 5.2.2 and Appendix H, Section 4). This information is vital to understand the implications of repository design (waste package capacity, surface storage time, waste package spacing, and emplacement drift or borehole spacing) by comparing the peak temperature to the thermal limits of the concentric layers surrounding the waste package; specifically 100 C for the bentonite buffer in granite and clay repositories, 100 C for rock wall in a clay repository and 200 C at the rock wall for a salt repository. These thermal limits are both preliminary and approximate, and serve as a means to evaluate design options rather than determining compliance for licensing situations. The thermal behavior of a salt repository is more difficult to model because it is not a concentric geometry and because the crushed salt backfill initially has a much higher thermal resistance than intact salt. Three models were investigated, namely a waste package in complete contact with crushed salt, secondly a waste package in contact with intact salt, and thirdly a waste package in contact with 75% intact and 25% crushed salt. The latter model best depicts emplacement of a waste package in the corner of an intact salt alcove and subsequently covered with crushed salt backfill to the angle of repose. The most conservative model (crushed salt) had temperatures much higher than the other models and although bounding, is too conservative to use. The most realistic model (75/25) had only a small temperature difference from the simplest (non-conservative, intact salt) model, and is the one chosen in this report (see Section 5.2.3). A trade-study investigating three key variables (surface storage time, waste package capacity and waste package spacing) is important to understand and design a repository. Waste package heat can be reduced by storing for longer periods prior to emplacement, or by reducing the number of assemblies or canisters within that waste package. Waste package spacing can be altered to optimize the thermal load without exceeding the thermal limits of the host rock or EBS components. By examining each of these variables, repository footprint (and therefore cost) can be optimized. For this report, the layout was fixed for each geologic medium based on prior published designs in the international community, but it will be varied in future work. Section 5.2.4 summarizes the conclusions based on varying two of the three parameters (storage time and waste package capacity), and the results are shown in Appendix H, Sections 5 and 6.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

The Effect of Ionospheric Models on Electromagnetic Pulse Locations

Locations of electromagnetic pulses (EMPs) determined by time-of-arrival (TOA) often have outliers with significantly larger errors than expected. In the past, these errors were thought to arise from high order terms in the Appleton-Hartree equation. We simulated 1000 events randomly spread around the Earth into a constellation of 22 GPS satellites. We used four different ionospheres: “simple” where the time delay goes as the inverse of the frequency-squared, “full Appleton-Hartree”, the “BobRD integrals” and a full raytracing code. The simple and full Appleton-Hartree ionospheres do not show outliers whereas the BobRD and raytracing do. This strongly suggests that the cause of the outliers is not additional terms in the Appleton-Hartree equation, but rather is due to the additional path length due to refraction. A method to fix the outliers is suggested based on fitting a time to the delays calculated at the 5 GPS frequencies with BobRD and simple ionospheres. The difference in time is used as a correction to the TOAs.

58 GEOSCIENCES↗
DOE OSTI2020

ARM Shortwave Spectral Radiometry Strategy Review Report

A meeting of experts in shortwave (SW) spectral measurements was held in February 2019 to discuss the current state of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility instrumentation and the potential scientific impact of these measurements. Instrument mentors and users reported significant progress in hyperspectral measurement quality, with good-quality data sets now possible at several field campaigns and fixed sites. Ongoing filter-based measurement improvements, including addition of the 1.6-micron channel to the multifilter rotating shadowband radiometer (MFRSR) and lunar tracking mode of the Cimel sun photometers, were also lauded as exciting developments to improve retrievals of aerosol radiative properties and size distributions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

ARM Shortwave Spectral Radiometry Strategy Review Report

A meeting of experts in shortwave (SW) spectral measurements was held in February 2019 to discuss the current state of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility instrumentation and the potential scientific impact of these measurements. Instrument mentors and users reported significant progress in hyperspectral measurement quality, with good-quality data sets now possible at several field campaigns and fixed sites. Ongoing filter-based measurement improvements, including addition of the 1.6-micron channel to the multifilter rotating shadowband radiometer (MFRSR) and lunar tracking mode of the Cimel sun photometers, were also lauded as exciting developments to improve retrievals of aerosol radiative properties and size distributions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Partial program correctness

Discussed the preexisting problem of input dependence, interactions with other kinds of observable behavior and lack of debugger support. Also fixed (preexisting) "first" in wording based SGI review.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Testing of an Optical Fiber--Based Gamma Thermometer in the High Flux Isotope Reactor Gamma Irradiation Facility

This report describes the design, thermal modeling, and gamma irradiation testing of an optical fiber–based gamma thermometer (OFBGT), which was irradiated in the High Flux Isotope Reactor (HFIR) Gamma Irradiation Facility (GIF). OFBGTs are a promising technology for application in nuclear reactors because they can provide a distributed measurement of gamma ray heating rate, unlike thermocouple-based gamma thermometers, which are fixed in-core sensors that can be used in boiling water reactors to calibrate local power range monitors. OFBGTs measure gamma ray heating rate by measuring the temperature difference between a pair of optical fibers; one fiber is in thermal contact with a heat sink (usually the reactor coolant), and the other is in thermal contact with a thermally isolated mass. The device can be calibrated with a heating wire within the thermal mass. The OFBGT that was designed and fabricated at Oak Ridge National Laboratory can measure distributed gamma ray heating rate over an effective measurement length of 61 cm, and the outer diameter of the sensor is 12.7 mm, giving the prototypical sensor design a relatively small footprint. The sensor housing is backfilled with Ar to ensure a well-predicted thermal response that is not affected by humidity or chemical interactions during operation. For calibration, the sensor design uses a Ni–Cr wire, which can be supplied with currents from 0 to 1 A to capture the wide range of potential gamma ray heating rates expected in HFIR’s spent fuel elements. The OFBGT was thermally modeled analytically and numerically; both models account for temperature-dependent thermal conductivities of the materials and show good agreement. The thermal response of the sensor inside spent HFIR fuel elements was simulated for times up to 1 year after discharge of the fuel element. Out-of-pile open-air tests indicated that the steady-state response of the sensor matches modeled results within experimental uncertainty. Calibration tests were performed using electrical heating in the HFIR spent fuel pool, above the fuel elements, to establish a relationship between the difference in spectral shift measured by optical fibers located inside and outside the OFBGT and the applied electrical heating. Subsequently, the OFBGT was placed within the the spent fuel element from HFIR cycle 501 to measure the spatial profile of the gamma heating rates. Results showed good agreement between the theoretical and measured gamma dose rate profiles, with maximum deviations of ~10% or less.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Status of the Jefferson Lab Eta Factory (JEF) experiment

The Jefferson Lab Eta Factory (JEF) experiment is an experiment running in Hall D at Jefferson Lab that focuses on studying the decays of the ¿ meson. These decays provide a rich laboratory for searching for new charge conjugation violating / parity conserving (CVPC) processes, looking for hints of Beyond Standard Model physics, and probing higher order terms in Chiral Perturbation Theory. The flagship channel is the rare decay ¿ ¿ p0¿¿, the measurement of which required an upgrade to the existing equipment in Hall D. The experiment uses the GlueX detector, a fixed-target large acceptance spectrometer based on a solenoid magnet containing drift chambers for tracking charged particles and a lead-scintillator barrel calorimeter in the central region and an array of 4 × 4 × 45 cm3 lead glass blocks in the forward region for detecting neutral particles. During the last two years the inner 80×80 cm2 region of the forward calorimeter has been replaced by an array of 2 × 2 × 20 cm3 lead tungstate crystals, which provide factors of two improvement in energy and position resolution. The first round of data taking with this configuration took place this year. A first look at the data will be presented.

Taylor, Simon [Thomas Jefferson National Accelerat↗
DOE OSTI2016

Numerical simulations of turbulent molecular clouds regulated by radiation feedback forces. I. Star formation rate and efficiency

Radiation feedback from stellar clusters is expected to play a key role in setting the rate and efficiency of star formation in giant molecular clouds. To investigate how radiation forces influence realistic turbulent systems, we have conducted a series of numerical simulations employing the Hyperion radiation hydrodynamics solver, considering the regime that is optically thick to ultraviolet and optically thin to infrared radiation. Our model clouds cover initial surface densities between Σ{sub cl,0}∼10--300 M{sub ⊙} pc{sup −2}, with varying initial turbulence. We follow them through turbulent, self-gravitating collapse, star cluster formation, and cloud dispersal by stellar radiation. All our models display a log-normal distribution of gas surface density Σ; for an initial virial parameter α{sub vir,0}=2, the log-normal standard deviation is σ{sub lnΣ}=1--1.5 and the star formation rate coefficient ε{sub ff, ρ-bar }=0.3--0.5, both of which are sensitive to turbulence but not radiation feedback. The net star formation efficiency (SFE) ε{sub final} increases with Σ{sub cl,0} and decreases with α{sub vir,0}. We interpret these results via a simple conceptual framework, whereby steady star formation increases the radiation force, such that local gas patches at successively higher Σ become unbound. Based on this formalism (with fixed σ{sub lnΣ}), we provide an analytic upper bound on ε{sub final}, which is in good agreement with our numerical results. The final SFE depends on the distribution of Eddington ratios in the cloud and is strongly increased by the turbulent compression of gas.

79 ASTRONOMY AND ASTROPHYSICS↗