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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Scenarios of Global Municipal Water-Use Demand Projections over the 21st Century

This paper establishes three future projections of global municipal water use to the end of the 21st century: A reference business-as usual (BAU) scenario, a High Technological Improvement (High Tech) scenario and a Low Technological Improvement (Low Tech) scenario. A global municipal water demand model is constructed using global water use statistics at the country-scale, calibrated to the base year of 2005, and simulated to the end of the 21st century. Since the constructed water demand model hinges on socioeconomic variables (population, income), water price, and end-use technology and efficiency improvement rates, projections of those input variables are adopted to characterize the uncertainty in future water demand estimates. The water demand model is linked to the Global Change Assessment Model (GCAM), a global change integrated assessment model. Under the reference scenario, the global total water withdrawal increases from 466 km3/year in 2005 to 941 km3/year in 2100,while withdrawals in the high and low tech scenarios are 321 km3/ year and 2000 km3/ year, respectively. This wide range (321-2000 km3/ year) indicates the level of uncertainty associated with such projections. The simulated global municipal demand projections are most sensitive to population and income projections, then to end-use technology and efficiency projections, and finally to water price. Thus, using water price alone as a policy measure to reduce municipal water use may substantiate the share of municipal water price of people’s annual incomes.

climate policy↗
DOE OSTI2020

Projected changes in seasonal precipitation extremes over the United States in CMIP6 simulations

Quantifying how climate change may impact precipitation extremes is a priority for informing adaptation and policy planning. In this study, Coupled Model Intercomparison Project phase 6 global climate models are analyzed to identify robust signals of projected changes in summer and winter precipitation extremes over the United States (US). Under a projected fossil-fuel based economic (i.e. high greenhouse gas emissions) scenario, our results show consistent changes in the seasonal patterns for many precipitation extremes by the end of the 21st century. We find a robust projected increase in the intensity of winter precipitation across models, with less agreement during the summer. Similarly, a robust projected amplification of heavy precipitation over the northern US is evident in winter, while intermodel spread is prevalent in summer projections. Specifically, the heavy and very heavy winter precipitation days (R10mm and R20mm) exhibit larger increases compared to other aspects of precipitation. Additionally, changes in dry extremes (e.g. consecutive dry days) are found to differ significantly across various subregions and seasons. Overall, our results suggest that the US may suffer more natural disasters such as floods and droughts in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Partitioning uncertainty in projections of Arctic sea ice

Abstract Improved knowledge of the contributing sources of uncertainty in projections of Arctic sea ice over the 21st century is essential for evaluating impacts of a changing Arctic environment. Here, we consider the role of internal variability, model structure and emissions scenario in projections of Arctic sea-ice area (SIA) by using six single model initial-condition large ensembles and a suite of models participating in Phase 5 of the Coupled Model Intercomparison Project. For projections of September Arctic SIA change, internal variability accounts for as much as 40%–60% of the total uncertainty in the next decade, while emissions scenario dominates uncertainty toward the end of the century. Model structure accounts for 60%–70% of the total uncertainty by mid-century and declines to 30% at the end of the 21st century in the summer months. For projections of wintertime Arctic SIA change, internal variability contributes as much as 50%–60% of the total uncertainty in the next decade and impacts total uncertainty at longer lead times when compared to the summertime. In winter, there exists a considerable scenario dependence of model uncertainty with relatively larger model uncertainty under strong forcing compared to weak forcing. At regional scales, the contribution of internal variability can vary widely and strongly depends on the calendar month and region. For wintertime SIA change in the Greenland-Iceland-Norwegian and Barents Seas, internal variability contributes 60%–70% to the total uncertainty over the coming decades and remains important much longer than in other regions. We further find that the relative contribution of internal variability to total uncertainty is state-dependent and increases as sea ice volume declines. These results demonstrate that internal variability is a significant source of uncertainty in projections of Arctic sea ice.

Bonan, David B. (ORCID:0000000338676009)↗
DOE OSTI2023

Non-parametric projections of national income distribution consistent with the Shared Socioeconomic Pathways

Understanding and projecting income distributions within countries and regions is important to understanding consumption trends and the distributional consequences of climate impacts and responses. Several global, country-level projections of income distribution are available but most project only the Gini coefficient (a summary statistic of the distribution) or utilize the Gini along with the assumption of a lognormal distribution. We test the lognormal assumption and find that it typically underestimates income in the highest deciles and over-estimates it in others. We find that a new model based on two principal components of national time series data for income distribution provides a better fit to the data for all deciles, especially for the highest and lowest. We also construct a projection model in which the first principal component is driven by the Gini coefficient and the second captures deviations from this relationship. We use the model to project income distribution by decile for all countries for the five shared socioeconomic pathways. We find that inequality is consistently higher than projections based on the Gini and the lognormal functional form, with some countries reaching ratios of the highest to lowest income deciles that are almost three times their value using the lognormal assumption.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Simplified projection on total spin zero for state preparation on quantum computers

Here, we introduce a simple algorithm for projecting on J = 0 states of a many-body system by performing a series of rotations to remove states with angular momentum projections greater than zero. Existing methods rely on unitary evolution with the two-body operator J 2 , which when expressed in the computational basis contains many complicated Pauli strings requiring Trotterization and leading to very deep quantum circuits. Our approach performs the necessary projections using the one-body operators J x and J z . By leveraging the method of Cartan decomposition, the unitary transformations that perform the projection can be parametrized as a product of a small number of two-qubit rotations, with angles determined by an efficient classical optimization. Given the reduced complexity in terms of gates, this approach can be used to prepare approximate ground states of even-even nuclei by projecting onto the J = 0 component of deformed Hartree-Fock states. We estimate the resource requirements in terms of the universal gate set {H,S, CNOT ,T} and briefly discuss a variant of the algorithm that projects onto J = 1/2 states of a system with an odd number of fermions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Optical galaxy cluster mock catalogs with realistic projection effects: Validations with the SDSS clusters

Galaxy clusters identified in optical imaging surveys suffer from projection effects: Physically unassociated galaxies along a cluster’s line of sight can be counted as its members and boost the observed richness (the number of cluster members). To model the impact of projection on cluster cosmology analyses, we apply a halo occupation distribution model to 𝑁-body simulations to simulate the red galaxies contributing to cluster members, and we use the number of galaxies in a cylinder along the line of sight (counts in cylinders) to model the impact of projection on cluster richness. We compare three projection models: uniform, quadratic, and Gaussian, and we convert between them by matching their effective cylinder volumes. We validate our mock catalogs using SDSS redMaPPer clusters’ data vectors, including counts vs richness, stacked lensing signal, spectroscopic redshift distribution of member galaxies, and richness remeasured on a redshift grid. We find the former two are insensitive to the projection model, while the latter two favor a quadratic projection model with a width of ≈180 ℎ −1 Mpc (equivalent to the volume of a uniform model with a width of 100 ℎ −1 Mpc and a Gaussian model with a width of 110 ℎ −1 Mpc, or a Gaussian redshift error of 0.04). Furthermore, our framework provides an efficient and flexible way to model optical cluster data vectors, paving the way for a simulation-based joint analysis for clusters, galaxies, and shear.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Random projection using random quantum circuits

The random sampling task performed by Google's Sycamore processor gave us a glimpse of the “quantum supremacy era.” This has definitely shed some light on the power of random quantum circuits in this abstract task of sampling outputs from the (pseudo)random circuits. In this paper, we explore a practical near-term use of local random quantum circuits in dimensional reduction of large low-rank data sets. We make use of the well-studied dimensionality reduction technique called the random projection method. This method has been extensively used in various applications such as image processing, logistic regression, entropy computation of low-rank matrices, etc. We prove that the matrix representations of local random quantum circuits with sufficiently shorter depths [ ∼ O ( n ) ] serve as good candidates for random projection. We demonstrate numerically that their projection abilities are not far off from the computationally expensive classical principal components analysis on MNIST and CIFAR-100 image datasets. We also benchmark the performance of quantum random projection against the commonly used classical random projection in the tasks of dimensionality reduction of image data sets and computing von Neumann entropies of large low-rank density matrices. And finally, using variational quantum singular value decomposition, we demonstrate a near-term implementation of extracting the singular vectors with dominant singular values after quantum random projecting a large low-rank matrix to lower dimensions. All such numerical experiments unequivocally demonstrate the ability of local random circuits to randomize a large Hilbert space at sufficiently shorter depths with robust retention of properties of large data sets in reduced dimensions. Published by the American Physical Society 2024

Kumaran, Keerthi (ORCID:0009000949125721)↗
DOE OSTI2016

Assessing uncertainties in land cover projections

Understanding uncertainties in land cover projections is critical to investigating land-based climate mitigation policies, assessing the potential of climate adaptation strategies and quantifying the impacts of land cover change on the climate system. In this work, we identify and quantify uncertainties in global and European land cover projections over a diverse range of model types and scenarios, extending the analysis beyond the agro-economic models included in previous comparisons. The results from 75 simulations over 18 models are analysed and show a large range in land cover area projections, with the highest variability occurring in future cropland areas. We demonstrate systematic differences in land cover areas associated with the characteristics of the modelling approach, which is at least as great as the differences attributed to the scenario variations. The results lead us to conclude that a higher degree of uncertainty exists in land use projections than currently included in climate or earth system projections. To account for land use uncertainty, it is recommended to use a diverse set of models and approaches when assessing the potential impacts of land cover change on future climate. Additionally, further work is needed to better understand the assumptions driving land use model results and reveal the causes of uncertainty in more depth, to help reduce model uncertainty and improve the projections of land cover.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

TU-F-18A-06: Dual Energy CT Using One Full Scan and a Second Scan with Very Few Projections

Purpose: The conventional dual energy CT (DECT) requires two full CT scans at different energy levels, resulting in dose increase as well as imaging errors from patient motion between the two scans. To shorten the scan time of DECT and thus overcome these drawbacks, we propose a new DECT algorithm using one full scan and a second scan with very few projections by preserving structural information. Methods: We first reconstruct a CT image on the full scan using a standard filtered-backprojection (FBP) algorithm. We then use a compressed sensing (CS) based iterative algorithm on the second scan for reconstruction from very few projections. The edges extracted from the first scan are used as weights in the Objectives: function of the CS-based reconstruction to substantially improve the image quality of CT reconstruction. The basis material images are then obtained by an iterative image-domain decomposition method and an electron density map is finally calculated. The proposed method is evaluated on phantoms. Results: On the Catphan 600 phantom, the CT reconstruction mean error using the proposed method on 20 and 5 projections are 4.76% and 5.02%, respectively. Compared with conventional iterative reconstruction, the proposed edge weighting preserves object structures and achieves a better spatial resolution. With basis materials of Iodine and Teflon, our method on 20 projections obtains similar quality of decomposed material images compared with FBP on a full scan and the mean error of electron density in the selected regions of interest is 0.29%. Conclusion: We propose an effective method for reducing projections and therefore scan time in DECT. We show that a full scan plus a 20-projection scan are sufficient to provide DECT images and electron density with similar quality compared with two full scans. Our future work includes more phantom studies to validate the performance of our method.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

WE-G-207-02: Full Sequential Projection Onto Convex Sets (FS-POCS) for X-Ray CT Reconstruction

Purpose: To develop an iterative reconstruction method for X-ray CT, in which the reconstruction can quickly converge to the desired solution with much reduced projection views. Methods: The reconstruction is formulated as a convex feasibility problem, i.e. the solution is an intersection of three convex sets: 1) data fidelity (DF) set – the L2 norm of the difference of observed projections and those from the reconstructed image is no greater than an error bound; 2) non-negativity of image voxels (NN) set; and 3) piecewise constant (PC) set - the total variation (TV) of the reconstructed image is no greater than an upper bound. The solution can be found by applying projection onto convex sets (POCS) sequentially for these three convex sets. Specifically, the algebraic reconstruction technique and setting negative voxels as zero are used for projection onto the DF and NN sets, respectively, while the projection onto the PC set is achieved by solving a standard Rudin, Osher, and Fatemi (ROF) model. The proposed method is named as full sequential POCS (FS-POCS), which is tested using the Shepp-Logan phantom and the Catphan600 phantom and compared with two similar algorithms, TV-POCS and CP-TV. Results: Using the Shepp-Logan phantom, the root mean square error (RMSE) of reconstructed images changing along with the number of iterations is used as the convergence measurement. In general, FS- POCS converges faster than TV-POCS and CP-TV, especially with fewer projection views. FS-POCS can also achieve accurate reconstruction of cone-beam CT of the Catphan600 phantom using only 54 views, comparable to that of FDK using 364 views. Conclusion: We developed an efficient iterative reconstruction for sparse-view CT using full sequential POCS. The simulation and physical phantom data demonstrated the computational efficiency and effectiveness of FS-POCS.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-FG-CAMPUS-JeP3-03: Detection of Unpredictable Patient Movement During SBRT Using a Single KV Projection of An On-Board CBCT System: Simulation Study

Purpose: An unpredictable movement of a patient can occur during SBRT even when immobilization devices are applied. In the SBRT treatments using a conventional linear accelerator detection of such movements relies heavily on human interaction and monitoring. This study aims to detect such positional abnormalities in real-time by assessing intra-fractional gantry mounted kV projection images of a patient’s spine. Methods: We propose a self-CBCT image based spine tracking method consisting of the following steps: (1)Acquire a pre-treatment CBCT image; (2)Transform the CBCT volume according to the couch correction; (3)Acquire kV projections during treatment beam delivery; (4)Simultaneously with each acquisition generate a DRR from the CBCT volume based-on the current projection geometry; (5)Perform an intensity gradient-based 2D registration between spine ROI images of the projection and the DRR images; (6)Report an alarm if the detected 2D displacement is beyond a threshold value. To demonstrate the feasibility, retrospective simulations were performed on 1,896 projections from nine CBCT sessions of three patients who received lung SBRT. The unpredictable movements were simulated by applying random rotations and translations to the reference CBCT prior to each DRR generation. As the ground truth, the 3D translations and/or rotations causing >3 mm displacement of the midpoint of the thoracic spine were regarded as abnormal. In the measurements, different threshold values of 2D displacement were tested to investigate sensitivity and specificity of the proposed method. Results: A linear relationship between the ground truth 3D displacement and the detected 2D displacement was observed (R{sup 2} = 0.44). When the 2D displacement threshold was set to 3.6 mm the overall sensitivity and specificity were 77.7±5.7% and 77.9±3.5% respectively. Conclusion: In this simulation study, it was demonstrated that intrafractional kV projections from an on-board CBCT system have a potential to detect unpredictable patient movement during SBRT. This research is funded by Interfractional Imaging Research Grant from Elekta.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Incorporating Snow Albedo Feedback into Downscaled Temperature and Snow Cover Projections for California’s Sierra Nevada

California’s Sierra Nevada is a high-elevation mountain range with significant seasonal snow cover. Under anthropogenic climate change, amplification of the warming is expected to occur at elevations near snow margins due to snow albedo feedback. However, climate change projections for the Sierra Nevada made by global climate models (GCMs) and statistical downscaling methods miss this key process. Dynamical downscaling simulates the additional warming due to snow albedo feedback. Ideally, dynamical downscaling would be applied to a large ensemble of 30 or more GCMs to project ensemble-mean outcomes and intermodel spread, but this is far too computationally expensive. To approximate the results that would occur if the entire GCM ensemble were dynamically downscaled, a hybrid dynamical–statistical downscaling approach is used. First, dynamical downscaling is used to reconstruct the historical climate of the 1981–2000 period and then to project the future climate of the 2081–2100 period based on climate changes from five GCMs. Next, a statistical model is built to emulate the dynamically downscaled warming and snow cover changes for any GCM. This statistical model is used to produce warming and snow cover loss projections for all available CMIP5 GCMs. These projections incorporate snow albedo feedback, so they capture the local warming enhancement (up to 3°C) from snow cover loss that other statistical methods miss. Capturing these details may be important for accurately projecting impacts on surface hydrology, water resources, and ecosystems

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Future Projection of Tropical Upper-Tropospheric Troughs and Implications for Tropical Cyclone Activity

Summertime tropical upper-tropospheric troughs (TUTTs) provide a unified framework to better understand how extratropical and tropical forcings jointly modulate basin-scale tropical cyclone (TC) activity. In this study, we examine future changes in TUTTs and their implications for TC activity. Multimodel ensemble-mean projections from 45 Coupled Model Intercomparison Project phase 6 (CMIP6) models suggest a contraction of the Pacific TUTT and an expansion of the Atlantic TUTT as the climate warms. Consistently, future changes in environment-based TC indices indicate that the large-scale conditions will become more favorable for TC genesis and intensification over the central North Pacific but less favorable over the tropical North Atlantic and Gulf of Mexico. Utilizing a TC-permitting large-ensemble dataset [i.e., the Database for Policy Decision-Making for Future Climate Change (d4PDF)] that adequately captures the observed interannual TUTT–TC relationships, we further confirm the impacts of projected TUTT changes on the TC activity in a warmer climate. In contrast, the TUTT–TC relationship is poorly represented in most CMIP6 High-Resolution Model Intercomparison Project (HighResMIP) models; such deficiencies call for caution when assessing future TC risk based on explicitly tracked TCs in these models. Additionally, CMIP6 projections show large intermodel spread in TUTT changes, implying uncertainty in projected TC activity, especially over the central-to-eastern Pacific and the North Atlantic. This intermodel spread is associated with interhemispheric sea surface temperature warming asymmetry, which leads to a meridional shift of the intertropical convergence zone (ITCZ) and the simultaneous weakening or strengthening of TUTTs in the North Pacific and North Atlantic. The potential contributions of anthropogenic aerosol forcing and oceanic circulation to this interhemispheric warming asymmetry are briefly examined.

Climate Change↗
DOE OSTI2011

Feasibility Study for a Hopi Utility-Scale Wind Project

The goal of this project was to investigate the feasibility for the generation of energy from wind and to parallel this work with the development of a tribal utility organization capable of undertaking potential joint ventures in utility businesses and projects on the Hopi reservation. The goal of this project was to investigate the feasibility for the generation of energy from wind and to parallel this work with the development of a tribal utility organization capable of undertaking potential joint ventures in utility businesses and projects on the Hopi reservation. Wind resource assessments were conducted at two study sites on Hopi fee simple lands located south of the city of Winslow. Reports from the study were recently completed and have not been compared to any existing historical wind data nor have they been processed under any wind assessment models to determine the output performance and the project economics of turbines at the wind study sites. Ongoing analysis of the wind data and project modeling will determine the feasibility of a tribal utility-scale wind energy generation.

17 WIND ENERGY↗
DOE OSTI2011

Role of Renewable Energy Certificates in Developing New Renewable Energy Projects

For more than a decade, renewable energy certificates (RECs) have grown in use, becoming a common way to track ownership of the renewable and environmental attributes of renewable electricity generation. In recent years, however, questions have risen about the role RECs play in the decision to build new renewable energy projects. Information from a variety of market participants suggests that theimportance of RECs in building new projects varies depending on a number of factors, including electricity market prices, the cost-competitiveness of the project, the presence or absence of public policies supportive of new projects, contract duration, and the perspective of different market participants. While there is no single answer to the role that RECs play, there are situations in whichREC revenues are essential to project economics, as well as some where REC revenues may have little impact. To strengthen the role RECs play in both compliance and voluntary markets, there are a number of options that could be considered. In compliance markets, lawmakers or regulators would have to adopt measures that strengthen the role of RECs in the development of new projects, while involuntary markets, it would be up to program leaders and market participants themselves to implement measures.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2011

Battleground Energy Recovery Project

In October 2009, the project partners began a 36-month effort to develop an innovative, commercial-scale demonstration project incorporating state-of-the-art waste heat recovery technology at Clean Harbors, Inc., a large hazardous waste incinerator site located in Deer Park, Texas. With financial support provided by the U.S. Department of Energy, the Battleground Energy Recovery Project was launched to advance waste heat recovery solutions into the hazardous waste incineration market, an area that has seen little adoption of heat recovery in the United States. The goal of the project was to accelerate the use of energy-efficient, waste heat recovery technology as an alternative means to produce steam for industrial processes. The project had three main engineering and business objectives: Prove Feasibility of Waste Heat Recovery Technology at a Hazardous Waste Incinerator Complex; Provide Low-cost Steam to a Major Polypropylene Plant Using Waste Heat; and Create a Showcase Waste Heat Recovery Demonstration Project.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2012

Summary of Carbon Storage Project Public Information Meeting and Open House

The Kentucky Geological Survey (KGS) completed a second phase of carbon dioxide (CO 2 ) injection and seismic imaging in the Knox Group, a Cambrian Ordovician dolomite and sandstone sequence in September 2010. This work completed 2 years of activity at the KGS No. 1 Marvin Blan well in Hancock County, Kentucky. The well was drilled in 2009 by a consortium of State and industry partners (Kentucky Consortium for Carbon Storage). An initial phase of CO 2 injection occurred immediately after completion of the well in 2009. The second phase of injection and seismic work was completed in September 2010 as part of a U.S. DOE funded project, after which the Blan well was plugged and abandoned. Following completion of research at the Blan well, a final public meeting and open house was held in Hancock County on October 28, 2010. This meeting followed one public meeting held prior to drilling of the well, and two on site visits during drilling (one for news media, and one for school teachers). The goal of the final public meeting was to present the results of the project to the public, answer questions, and address any concerns. Despite diligent efforts to publicize the final meeting, it was poorly attended by the general public. Several local county officials and members of the news media attended, but only one person from the general public showed up. We attribute the lack of interest in the results of the project to several factors. First, the project went as planned, with no problems or incidents that affected the local residents. The fact that KGS fulfilled the promises it made at the beginning of the project satisfied residents, and they felt no need to attend the meeting. Second, Hancock County is largely rural, and the technical details of carbon sequestration were not of interest to many people. The county officials attending were an exception; they clearly realized the importance of the project in future economic development for the county.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2014

TEP Power Partners Project [Tucson Electric Power]

The Arizona Governor’s Office of Energy Policy, in partnership with Tucson Electric Power (TEP), Tendril, and Next Phase Energy (NPE), formed the TEP Power Partners pilot project to demonstrate how residential customers could access their energy usage data and third party applications using data obtained from an Automatic Meter Reading (AMR) network. The project applied for and was awarded a Smart Grid Data Access grant through the U.S. Department of Energy. The project participants’ goal for Phase I is to actively engage 1,700 residential customers to demonstrate sustained participation, reduction in energy usage (kWh) and cost ($), and measure related aspects of customer satisfaction. This Demonstration report presents a summary of the findings, effectiveness, and customer satisfaction with the 15-month TEP Power Partners pilot project. The objective of the program is to provide residential customers with energy consumption data from AMR metering and empower these participants to better manage their electricity use. The pilot recruitment goals included migrating 700 existing customers from the completed Power Partners Demand Response Load Control Project (DRLC), and enrolling 1,000 new participants. Upon conclusion of the project on November 19, 2013; 1,390 Home Area Networks (HANs) were registered; 797 new participants installed a HAN; Survey respondents’ are satisfied with the program and found value with a variety of specific program components; Survey respondents report feeling greater control over their energy usage and report taking energy savings actions in their homes after participating in the program; On average, 43 % of the participants returned to the web portal monthly and 15% returned weekly; and An impact evaluation was completed by Opinion Dynamics and found average participant savings for the treatment period1 to be 2.3% of their household use during this period.2 In total, the program saved 163 MWh in the treatment period of 2013.

24 POWER TRANSMISSION AND DISTRIBUTION↗