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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Realistic Cost to Execute Practical Quantum Circuits using Direct Clifford+T Lattice Surgery Compilation

We report a resource estimation pipeline that explicitly compiles quantum circuits expressed using the Clifford+T gate set into a surface code lattice surgery instruction set. The cadence of magic state requests from the compiled circuit enables the optimization of magic state distillation and storage requirements in a post-hoc analysis. To compile logical circuits into lattice surgery operations, we build upon the open-source Lattice Surgery Compiler. The revised compiler operates in two stages: the first translates logical gates into an abstract, layout-independent instruction set; the second compiles these into local lattice surgery instructions that are allocated to hardware tiles according to a specified resource layout. The second stage retains logical parallelism while avoiding resource contention in the fault-tolerant layer, aiding realism. Additionally, users can specify dedicated tiles at which magic states are replenished, enabling resource costs from the logical computation to be considered independently from magic state distillation and storage. We demonstrate the applicability of our pipeline to large practical quantum circuits by providing resource estimates for the ground state estimation of molecules. Finally, we find that variable magic state consumption rates in real circuits can cause the resource costs of magic state storage to dominate unless production is varied to suit.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2005

Establishing the Global Fresh Water Sensor Web

This paper presents an approach to measuring the major components of the water cycle from space using the concept of a sensor-web of satellites that are linked to a data assimilation system. This topic is of increasing importance, due to the need for fresh water to support the growing human population, coupled with climate variability and change. The net effect is that water is an increasingly valuable commodity. The distribution of fresh water is highly uneven over the Earth, with both strong latitudinal distributions due to the atmospheric general circulation, and even larger variability due to landforms and the interaction of land with global weather systems. The annual global fresh water budget is largely a balance between evaporation, atmospheric transport, precipitation and runoff. Although the available volume of fresh water on land is small, the short residence time of water in these fresh water reservoirs causes the flux of fresh water - through evaporation, atmospheric transport, precipitation and runoff - to be large. With a total atmospheric water store of approx. 13 x 10(exp 12)cu m, and an annual flux of approx. 460 x 10(exp 12)cu m/y, the mean atmospheric residence time of water is approx. 10 days. River residence times are similar, biological are approx. 1 week, soil moisture is approx. 2 months, and lakes and aquifers are highly variable, extending from weeks to years. The hypothesized potential for redistribution and acceleration of the global hydrological cycle is therefore of concern. This hypothesized speed-up - thought to be associated with global warming - adds to the pressure placed upon water resources by the burgeoning human population, the variability of weather and climate, and concerns about anthropogenic impacts on global fresh water availability.

Hildebrand, Peter H.↗
DOE OSTI2018

Inter-Annual Precipitation Variability Decreases Switchgrass Productivity from Arid to Mesic Environments

Cellulosic biofuels are an important source of renewable biomass within the alternative energy portfolio. Switchgrass (Panicum virgatum L.), a perennial C 4 grass native to North America, is widely studied as a biofuel feedstock for its consistently high yields and minimal input requirements. The influences of precipitation amount and temporal variability on the fertilizer response of switchgrass productivity are not fully understood. Moreover, global climate models predict changes in rainfall patterns towards lower and increasingly variable soil water availability in several productive areas worldwide, which may impact net primary production of biofuel crops. We conducted a meta-analysis of aboveground net primary production of switchgrass from 48 publications encompassing 82 different locations, 11 soil types, 52 switchgrass cultivars, fertilizer inputs between 0 to 896 kg N ha –1 year –1 , and 1 to 6 years of annual productivity measures repeated on the same stand. Productivity of the lowland ecotype doubled with N rates > 131 kg N ha –1 year –1 , but upland ecotype productivity increased only by 50%. Results showed an optimum N rate of 30 to 60 kg N ha –1 year –1 for both ecotypes, after which biomass gain per unit of N added decreased. Growing season precipitation (GSPPT) and inter-annual precipitation variability (inter-PPTvar) affected both ecotypes similarly. Long-term mean annual precipitation (MAP) differentially affected lowland and upland productivity, depending on the N level. Productivity responses to MAP and GSPPT were similar for both upland and lowland ecotypes at none or low N rates. When N increased beyond 60 kg N ha –1 year –1 , lowland cultivars had a greater growth response to MAP than uplands. Productivity increased with increasing GSPPT and MAP and had a positive linear response to MAP ranging from 600 to 1200 mm year –1 . One third of the variability in switchgrass production was accounted for by inter-PPTvar. After accounting for MAP, sites with higher inter-PPTvar had lower switchgrass productivity than sites with lower inter-PPTvar. Increased inter-annual variation in precipitation reduced production of both ecotypes. As a result, predicted changes in the amount and timing of precipitation thus likely will exert greater influence on production of upland than lowland ecotypes of switchgrass.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Using energy storage systems to extend the life of hydropower plants

Despite their advantages, distributed energy resources (DERs) bring inherent uncertainty and variability into the landscape of modern power systems. As DER penetration grows, conventional generators like hydropower plants have to respond more often to arrest the imbalance in the net load. Hydropower turbines provide their best operational performance with minimal wear and tear when operating at regions of maximum efficiency. However, the current needs for hydropower plants require them to operate under varying load conditions and thus sub-optimal operating points leading to additional stress. To relieve the hydropower plants, this paper proposes a hybridization strategy where a hydropower unit is paired with an energy storage system (ESS) to increase operational flexibility and mitigate damage to the hydro plant. Models are developed to represent the operation of the hybrid system, quantify degradation, and assess economic benefits. Moreover, an innovative controller disaggregates the market dispatch signal into separate control setpoints for the ESS and hydropower unit. In case studies performed on a real-world hydropower facility, it was found that the ESS-based hybridization can extend the life of the hydropower plant by 5% on average. Notably, the economic benefits from reduced maintenance and deferred investment are estimated to be around $3.6 million.

13 HYDRO ENERGY↗
DOE OSTI2025

Exploring Afro-Asian water fluxes in CMIP5 and CMIP6 models: Present-day evaluation and future projections

Accurate representation and projection of water fluxes are vital, particularly in monsoon regions where seasonal variability and changes significantly impact water resources, agriculture, hydroelectric power generation, and the economy. This study uses both CMIP5 and CMIP6 models to investigate the present-day representation of key water flux components (including precipitation, evaporation, water vapor, and moisture advection) over the Afro-Asian region during the summer monsoon (JJAS). We also examine future changes under two emission scenarios and assess the underlying physical mechanisms driving these changes while identifying sources of projection uncertainty. Our results show that both models reasonably capture the present-day characteristics of water flux components, although with noticeable biases. Across most regions, we find that CMIP6 models demonstrate slight improvements over CMIP5 in the representation of these components. In a warmer future, a robust intensification of JJAS precipitation (exceeding 0.25 mm/day) is projected across the Afro-Asian region. This increase is largely driven by the vertical thermodynamic term associated with increasing temperature. We find that model uncertainty is the primary source of uncertainty in water flux projections, accounting for over 50 % of the total variance.

Climate change↗
DOE OSTI2010

Non-Gaussianity of quantum states: An experimental test on single-photon-added coherent states

Non-Gaussian states and processes are useful resources in quantum information with continuous variables. An experimentally accessible criterion has been proposed to measure the degree of non-Gaussianity of quantum states based on the conditional entropy of the state with a Gaussian reference. Here we adopt such a criterion to characterize an important class of nonclassical states: single-photon-added coherent states. Our studies demonstrate the reliability and sensitivity of this measure and use it to quantify how detrimental is the role of experimental imperfections in our implementation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

Graphical calculus for Gaussian pure states

We provide a unified graphical calculus for all Gaussian pure states, including graph transformation rules for all local and semilocal Gaussian unitary operations, as well as local quadrature measurements. We then use this graphical calculus to analyze continuous-variable (CV) cluster states, the essential resource for one-way quantum computing with CV systems. Current graphical approaches to CV cluster states are only valid in the unphysical limit of infinite squeezing, and the associated graph transformation rules only apply when the initial and final states are of this form. Our formalism applies to all Gaussian pure states and subsumes these rules in a natural way. In addition, the term 'CV graph state' currently has several inequivalent definitions in use. Using this formalism we provide a single unifying definition that encompasses all of them. We provide many examples of how the formalism may be used in the context of CV cluster states: defining the 'closest' CV cluster state to a given Gaussian pure state and quantifying the error in the approximation due to finite squeezing; analyzing the optimality of certain methods of generating CV cluster states; drawing connections between this graphical formalism and bosonic Hamiltonians with Gaussian ground states, including those useful for CV one-way quantum computing; and deriving a graphical measure of bipartite entanglement for certain classes of CV cluster states. We mention other possible applications of this formalism and conclude with a brief note on fault tolerance in CV one-way quantum computing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

Strong Einstein-Podolsky-Rosen entanglement from a single squeezed light source

Einstein-Podolsky-Rosen (EPR) entanglement is a criterion that is more demanding than just certifying entanglement. We theoretically and experimentally analyze the low-resource generation of bipartite continuous-variable entanglement, as realized by mixing a squeezed mode with a vacuum mode at a balanced beam splitter, i.e., the generation of so-called vacuum-class entanglement. We find that in order to observe EPR entanglement the total optical loss must be smaller than 33.3 %. However, arbitrarily strong EPR entanglement is generally possible with this scheme. We realize continuous-wave squeezed light at 1550 nm with up to 9.9 dB of nonclassical noise reduction, which is the highest value at a telecom wavelength so far. Using two phase-controlled balanced homodyne detectors we observe an EPR covariance product of 0.502{+-}0.006<1, where 1 is the critical value. We discuss the feasibility of strong Gaussian entanglement and its application for quantum key distribution in a short-distance fiber network.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Grid Edge Waveform Analytics Framework for Event Detection and Classification

This paper provides a grid edge waveform analytics framework for power system event detection and classification in the local as well as in the wide area. This framework overviews data excellence for event detection and classification. The data excellence describes the data acquisition process and requirements, data processing, data quality, and data integrity. Power system event detection in the local area based on different features such as energy-based, cyclostationary approach, template matching, and wavelet transform are also discussed. Furthermore, local area event detection and classification using approaches such as statistical, signal processing, artificial intelligence, and hybrid are also discussed. Moreover, an overview of wide-area event detection and classification along with several other aspects such as wide-area events, wide-area event detection approaches, event location and system performance, event pattern recognition, inter-area oscillation, and wide-area frequency response under variable deployment of inverter-based resources are also provided. The proposed framework is the first step toward the goal of developing appropriate tools and methodologies to detect and classify local as well as wide-area events using waveform analytics. The appropriate event detection and classification framework development is especially important now as more and more grid edge devices with communication capabilities are being deployed in the modern power grid than ever before.

Bhusal, Narayan↗
DOE OSTI2011

Balancing Act

Explore the source record for details and available documents.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Optimization of a High Pressure Turbine Blade and Sector-Based Annular Rig Design for Supercritical CO2 Power Cycle Representative Testing

Abstract As part of the ongoing research into the design of hardware for zero emission cycles, a first-stage high-pressure turbine (HPT) blade is optimized for a 300 MWe supercritical CO2 (sCO2) power cycle using the surrogate-assisted genetic algorithm optimizer in Numeca FINE/Design three-dimensional with objectives of increasing efficiency and decreasing heat load to the blade. Supercritical CO2 property tables are constructed from NIST REFPROP data for the condensable gas simulation in FINE/Turbo. A detailed mesh sensitivity study is performed for a baseline design to identify the proper-grid refinement and efficiently allocate resources for the optimization. Seventy design variables are selected for the initial population generation. Self-organizing maps are then used to focus the design variables on the most important ones affecting the objective functions. The optimization results in approximately 3000 three-dimensional Reynolds Averaged Navier Stokes simulations of different blade shapes with increases in efficiency of up to 0.85% and decreases in heat load of 14%. Families of blade shapes are identified for experimental testing in an annular rig at the Purdue Experimental Turbine Aerothermal Laboratory. A design to adapt the annular cascade for testing optimized geometries is introduced, which features eccentric radius sectors allowing for scaled-up geometries of sCO2 optimized blade profiles to be tested at design cycle representative conditions at high Reynolds numbers in dry air. Analysis into the effects of Reynolds number, working fluid, and geometric relations are presented to prove the efficacy of the test method.

Engineering↗
DOE OSTI2019

GPCNeT

Network congestion is one of the biggest problems facing HPC systems today, affecting system throughput, performance, user experience, and reproducibility. Congestion manifests as run-to-run variability due to contention for shared resources (e.g., filesystems) or routes between compute endpoints. Despite its significance, current network benchmarks fail to proxy the real-world network utilization seen on congested systems. We propose a new open-source benchmark suite called the Global Performance and Congestion Network Tests (GPCNeT) to advance the state of the practice in this area. The guiding principles used in designing GPCNeT are described and the methodology employed to maximize its utility is presented. The capabilities of GPCNeT are evaluated by analyzing results from several world's largest HPC systems, including an evaluation of congestion management on a next-generation network. The results show that systems of all technologies and scales are susceptible to congestion and this work motivates the need for congestion control in next-generation networks.

Chunduri, Sudheer↗
DOE OSTI2016

Markov chain decomposition of monthly rainfall into daily rainfall: Evaluation of climate change impact

This paper evaluates the effect of climate change on daily rainfall, especially on the mean number of wet days and the mean rainfall intensity. Assuming that the mechanism of daily rainfall occurrences follows the first-order Markov chain model, the possible changes in the transition probabilities are estimated by considering the climate change scenarios. Also, the change of the stationary probabilities of wet and dry day occurrences and finally the change in the number of wet days are derived for the comparison of current (1x CO 2 ) and 2x CO 2 conditions. As a result of this study, the increase or decrease in the mean number of wet days was found to be not enough to explain all of the change in monthly rainfall amounts, so rainfall intensity should also be modified. The application to the Seoul weather station in Korea shows that about 30% of the total change in monthly rainfall amount can be explained by the change in the number of wet days and the remaining 70% by the change in the rainfall intensity. That is, as an effect of climate change, the increase in the rainfall intensity could be more significant than the increase in the wet days and, thus, the risk of flood will be much highly increased.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2011

Regional Energy Deployment System (ReEDS)

The Regional Energy Deployment System (ReEDS) is a deterministic optimization model of the deployment of electric power generation technologies and transmission infrastructure throughout the contiguous United States into the future. The model, developed by the National Renewable Energy Laboratory's Strategic Energy Analysis Center, is designed to analyze the critical energy issues in the electric sector, especially with respect to potential energy policies, such as clean energy and renewable energy standards or carbon restrictions. ReEDS provides a detailed treatment of electricity-generating and electrical storage technologies and specifically addresses a variety of issues related to renewable energy technologies, including accessibility and cost of transmission, regional quality of renewable resources, seasonal and diurnal generation profiles, variability of wind and solar power, and the influence of variability on the reliability of the electrical grid. ReEDS addresses these issues through a highly discretized regional structure, explicit statistical treatment of the variability in wind and solar output over time, and consideration of ancillary services' requirements and costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2013

Market and Policy Barriers to Energy Storage Deployment

Electric energy storage technologies can provide numerous grid services; there are a number of factors that restrict their current deployment. The most significant barrier to deployment is high capital costs, though several recent deployments indicate that capital costs are decreasing and energy storage may be the preferred economic alternative in certain situations. However, a number of other market and regulatory barriers persist, limiting further deployment. These barriers can be categorized into regulatory barriers, market (economic) barriers, utility and developer business model barriers, cross-cutting barriers and technology barriers.

25 ENERGY STORAGE↗
DOE OSTI2017

Discovering the desirable alleles contributing to the lignocellulosic biomass traits in Saccharum germplasm collections for energy cane improvement

1) The success in crop improvement programs depends largely on the extent of genetic variability available. Germplasm collections assembles all the available genetic resources and are critical for long-term crop improvement. This world sugarcane germplasm collection contains enormous genetic variability for various morphological traits, biomass yield components, adaptation and many quality traits, prospectively imbeds a large number of valuable alleles for biofuel traits such as high biomass yield, quantity and quality of lignocelluloses, stress tolerance, and nutrient use efficiency. The germplasm collection is of little value unless it is characterized and utilized for crop improvement. In this project, we phenotypically and genotypically characterized the sugarcane world germplasm collection (The results were published in two papers already and another two papers are to be published). This data will be made available for public to refer to for germplasm unitization specifically in the sugarcane and energy cane breeding programs. In addition, we are identifying the alleles contributing to the biomass traits in sugarcane germplasm. This part of project is very challenging due to the large genome and highly polyploid level of this crop. We firstly established a high throughput sugarcane genotyping pipeline in the genome and bioinformatics era (a paper is published in 2016). We identified and modified a software for genome-wide association analysis of polyploid species. The results of the alleles associated to the biomass traits will be published soon, which will help the scientific community understand the genetic makeup of the biomass components of sugarcane. Molecular breeders can develop markers for marker assisted selection of biomass traits improvement. Further, the development and release of new energy cane cultivars through this project not only improved genetic diversity but also improved dry biomass yields and resistance to diseases. These new cultivars were tested on marginal soils in Florida and showed very promising yield potential that is important for the successful use of energy cane as a dedicated feedstock for lignocellulosic ethanol production. 2) Multiple techniques at different project progress stages were utilized. For example, for the whole world germplasm accession genotyping, a cheap widely used SSR marker genotyping platform was utilized due to the large number of samples (over thousand). But the throughput of this technique is low in generating data points. However, the purpose the genotyping is to form a core collection for further high throughput genotyping. Thus the results from the SSR genotyping was quite good enough to generated the core collection. To genotype the few hundred core collection accessions, an target enrichment sequencing technology was used, which is not only high throughput in generating large number of genotyping data, but also has the candidate genes targeted to genotyping. The data generated would be sufficient in identifying the alleles contributing to the traits of interests. All the techniques used in this project are effective though extensive time was invested specifically for establish the pipeline in the experimental design, data analysis, and different approach comparison. 3) the research can benefit to the public in polyploid genotyping and new and cost efficient genotyping platform development

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A 2023 Perspective: What Is the Value of Hybridization?

This report takes a wind developer's perspective and provides a summary of the current and future state of hybrid facilities, and ultimately seeks to answer the question: "Are hybrid power plants a pivotal tool for meeting future energy and decarbonization targets?" The intention is not to provide an in-depth system-level technical analysis of hybrid facilities, but to showcase a high-level overview of the hybrid facility ecosystem and its potential future directions. Lastly, the authors acknowledge and recognize that non-renewable generation technologies can be integrated into a hybrid facility, however these technologies are outside the scope of this report.

17 WIND ENERGY↗
DOE OSTI2024

Evaluating the Nation's Pipeline Infrastructure with NETL's Advanced Infrastructure Integrity Model (AIIM)

This poster is a part of BIL-EDX4CCS Task 36: Advanced Infrastructure Integrity Modeling to Evaluate Existing Energy Infrastructure Reusability and Risk, the goal of which is to produce a smart tool that will assess existing energy infrastructure reusability and risk using the Advanced Infrastructure Integrity Model (AIIM). This model forecasts lifespan and potential risk using a multitude of factors such as incidents reports, structural characteristics, and the surrounding environment. The project aims to provide scientific insights for a better understanding of carbon storage (CS), potential to support CS stakeholder needs, national decarbonization, and mitigating climate change. AIIM will utilize an energy infrastructure database as its input, developed by acquiring publicly available data as well as NETL derived products. These resources include incidents, geohazards, and infrastructure variables. Soil data in the form of rasters and pipeline incident reports were processed and a script was developed to count the number of times features such as roads, railroads, and rivers intersected with pipeline segments which were then converted to points. Distance to oil and natural gas wells, petroleum ports, intermodal freight facilities, and geologic structures were also calculated. After data preparation and quality control was completed, the data was integrated into the pipeline points. Once models are complete, a smart tool will be created in the form of an online dashboard.

Malay, Caleb↗