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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 OSTI2023

Efficient Network Partitioning: Application for Decentralized State Estimation in Power Distribution Grids: Preprint

Increase in the proliferation of DERs requires real-time situational awareness for efficient grid operations. State estimation plays an important role for real time control and management of the power grid. As the sensing infrastructure grows, aggregating and handling high volumes of data at a centralized location is extremely difficult. To address this challenge, this paper first proposes a novel and efficient hierarchical spectral clustering-based network partition algorithm followed by a decentralized compressive sensing (DCS) based state estimation. The applicability of the proposed network partitioning algorithm is tested on IEEE-123 bus, IEEE-8500 node, and a 6204-node distribution network. The results shows that the proposed approach efficiently divides the network into multiple sub-networks with the minimum edge connections among the neighbors. Then, we perform DCS-based state estimation on the 6204-node distribution network after dividing the network into 18 optimal partitions. Simulation results show that DCS-based state estimation recovers the system states with high accuracy and low complexity.

ADMM↗
DOE OSTI2013

RECOVERY ACT - Robust Optimization for Connectivity and Flows in Dynamic Complex Networks

The goal of this project was to study robust connectivity and flow patterns of complex multi-scale systems modeled as networks. Networks provide effective ways to study global, system level properties, as well as local, multi-scale interactions at a component level. Numerous applications from power systems, telecommunication, transportation, biology, social science, and other areas have benefited from novel network-based models and their analysis. Modeling and optimization techniques that employ appropriate measures of risk for identifying robust clusters and resilient network designs in networks subject to uncertain failures were investigated in this collaborative multi-university project. In many practical situations one has to deal with uncertainties associated with possible failures of network components, thereby affecting the overall efficiency and performance of the system (e.g., every node/connection has a probability of partial or complete failure). Some extreme examples include power grid component failures, airline hub failures due to weather, or freeway closures due to emergencies. These are also situations in which people, materials, or other resources need to be managed efficiently. Important practical examples include rerouting flow through power grids, adjusting flight plans, and identifying routes for emergency services and supplies, in the event network elements fail unexpectedly. Solutions that are robust under uncertainty, in addition to being economically efficient, are needed. This project has led to the development of novel models and methodologies that can tackle the optimization problems arising in such situations. A number of new concepts, which have not been previously applied in this setting, were investigated in the framework of the project. The results can potentially help decision-makers to better control and identify robust or risk-averse decisions in such situations. Formulations and optimal solutions of the considered problems need to capture uncertainty and risk using appropriate probabilistic, statistical and optimization concepts. The main difficulty arising in addressing these issues is the dramatic increase in the computational complexity of the resulting optimization problems. This project studied novel models and methodologies for risk-averse network optimization- specifically, network design, network flows and cluster detection problems under uncertainty. The approach taken was to incorporate a quantitative risk measure known as conditional value-at-risk that is widely used in financial applications. This approach presents a viable alternate modeling and optimization framework to chance-constrained optimization and mean-variance optimization, one that also facilitates the detection of risk-averse solutions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Watching the dynamics of electrons and atoms at work in solar energy conversion

The photochemical reactions performed by transition metal complexes have been proposed as viable routes towards solar energy conversion and storage into other forms that can be conveniently used in our everyday applications. In order to develop efficient materials, it is necessary to identify, characterize and optimize the elementary steps of the entire process on the atomic scale. To this end, we have studied the photoinduced electronic and structural dynamics in two heterobimetallic ruthenium–cobalt dyads, which belong to the large family of donor–bridge–acceptor systems. Using a combination of ultrafast optical and X-ray absorption spectroscopies, we can clock the light-driven electron transfer processes with element and spin sensitivity. In addition, the changes in local structure around the two metal centers are monitored. These experiments show that the nature of the connecting bridge is decisive for controlling the forward and the backward electron transfer rates, a result supported by quantum chemistry calculations. More generally, this work illustrates how ultrafast optical and X-ray techniques can disentangle the influence of spin, electronic and nuclear factors on the intramolecular electron transfer process. Finally, some implications for further improving the design of bridged sensitizer-catalysts utilizing the presented methodology are outlined.

14 SOLAR ENERGY↗
DOE OSTI2026

Correlated Noise Estimation with Quantum Sensor Networks

We address the metrological problem of estimating collective stochastic properties imprinted on a network of quantum sensors. Canonical examples include center-of-mass quadrature fluctuations in a system of bosonic modes and correlated dephasing in an ensemble of qubits (e.g., spins), bosons, or fermions. We develop a theoretical framework to determine the limits of correlated (weak) noise estimation with quantum sensor networks and reveal the requirements for entanglement advantage. Notably, an advantage emerges from the synergistic interplay between quantum correlations of the sensors and “classical” correlations of the noises. Here, we determine optimal entangled probe states and identify a sensing protocol—reminiscent of a many-body echo—that achieves the fundamental limits of measurement sensitivity for a broad class of problems, unveiling a route toward entanglement-enhanced metrology of correlated many-body phenomena.

Quantum metrology↗
NASA NTRS2013

Flight-Deck Strategies and Outcomes When Flying Schedule-Matching Descents

Recent studies at NASA Ames Research Center have investigated the development and use of ground-based (air traffic controller) tools to manage and schedule air traffic in future terminal airspace. An exploratory study was undertaken to investigate the impacts that such tools (and concepts) could have on the flight-deck. Ten Boeing 747-400 crews flew eight optimized profile descents in the Los Angeles terminal airspace, while receiving scripted current day and futuristic speed clearances, to ascertain their ability to fly schedulematching descents without prior training. Although the study was exploratory in nature, four variables were manipulated: route constraints, winds, speed changes, and clearance phraseology. Despite flying the same scenarios with the same events and timing, there were significant differences in the time it took crews to fly the approaches. This variation is the product of a number of factors but highlights potential difficulties for scheduling tools that would have to accommodate this amount of natural variation in descent times. The focus of this paper is the examination of the crews' aircraft management strategies and outcomes. This includes potentially problematic human-automation interaction issues that may negatively impact arrival times, speed and altitude constraint compliance, and energy management efficiency.

Flight Management System↗
DOE OSTI2024

Identifying and Amplifying the Spontaneously Formed Photo‐Charge Contribution in Opaque and Semitransparent Organic Photovoltaics

Abstract Spontaneous photo‐charge (SP) generation within the non‐fullerene (NFA) bulk helps avoid exciton (EX) related loss as compared to the traditional heterojunction route in organic solar cells (OSCs). Unfortunately, the promising SP utilization attracts little attention at this time due to the lack of knowledge on its specific contribution to the photovoltaic performance and rational optimization in high‐efficiency devices. To fill the gap, the NFAs’ SP characteristics are related with their photocurrent loss and power conversion efficiency (PCE) in state‐of‐the‐art materials. Though higher SP population is good for efficient EX utilization, it simultaneously acts as an additional photo‐charge recombination channel. The former can be further enhanced by increasing the NFAs’ crystallinity with preferred lamellar growth, and the latter can be suppressed via electric doping. With the aid of the two‐step optimization strategy, the total photocurrent loss is reduced from 14.4% to 4.8%, accompanying with PCE increment from 16.9% to 18.5%. The SP utilization strategy is finally applied in the semitransparent OSCs (ST‐OSCs), due to its less heterojunction area sensitive photo‐charge generation characteristic. A light utilization efficiency (LUE) is then increased from 3.21% to 3.77%. The findings highlight the pursue of efficient SP utilization as a new design philosophy in future OSCs’ progresses.

Chemistry↗
DOE OSTI2019

Synthesis of Biomass-Derived Ethers for Use as Fuels and Lubricants

Ethers synthesized from biomass-derived compounds have exceptional properties as fuels, lubricants, and specialty chemicals and can serve as replacements for petroleum-derived products. Recent efforts have identified heterogeneous catalysts for the selective synthesis of ethers from alcohols, aldehydes, ketones, furans, esters, olefins, carboxylic acids, and other molecules derived from biomass. This Review highlights the scope of etherification reactions and provides insights into the choice of catalysts and reaction conditions best suited for producing targeted ethers from the available starting materials. First, the properties of ethers for specific applications and the methods by which synthons for ether synthesis can be obtained from biomass are discussed. Then the progress that has been made on the synthesis of ethers via the following methods is summarized: direct etherification of alcohols; reductive etherification of alcohols with aldehydes or ketones; etherification of furanic compounds, esters, and carboxylic acids; and the addition of alcohols to olefins. Next, the mechanisms of these reactions and catalyst properties required to promote them are discussed, with the goal of understanding how reaction conditions can be tuned to optimize catalyst activity and selectivity towards desired ethers. Finally, the Review closes by examining the tradeoffs between catalyst selectivity, activity, stability, and reaction conditions required to achieve the most economically and environmentally favorable routes to biomass-derived ethers.

09 BIOMASS FUELS↗
DOE OSTI2016

Joint optimization of logistics infrastructure investments and subsidies in a regional logistics network with CO 2 emission reduction targets

This study proposes an optimization model that simultaneously incorporates the selection of logistics infrastructure investments and subsidies for green transport modes to achieve specific CO 2 emission targets in a regional logistics network. The proposed model is formulated as a bi-level formulation, in which the upper level determines the optimal selection of logistics infrastructure investments and subsidies for green transport modes such that the benefit-cost ratio of the entire logistics system is maximized. The lower level describes the selected service routes of logistics users. A genetic and Frank-Wolfe hybrid algorithm is introduced to solve the proposed model. The proposed model is applied to the regional logistics network of Changsha City, China. Findings show that using the joint scheme of the selection of logistics infrastructure investments and green subsidies is more effective than using them solely. In conclusion, carbon emission reduction targets can significantly affect logistics infrastructure investments and subsidy levels.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Biosynthesis of monoethylene glycol in Saccharomyces cerevisiae utilizing native glycolytic enzymes

Monoethylene glycol (MEG) is an important commodity chemical with applications in numerous industrial processes, primarily in the manufacture of polyethylene terephthalate (PET) polyester used in packaging applications. In the drive towards a sustainable chemical industry, bio-based production of MEG from renewable biomass has attracted growing interest. Recent attempts for bio-based MEG production have investigated metabolic network modifications in Escherichia coli, specifically rewiring the xylose assimilation pathways for the synthesis of MEG. In the present study, we examined the suitability of Saccharomyces cerevisiae, a preferred organism for industrial applications, as platform for MEG biosynthesis. Here, based on combined genetic, biochemical and fermentation studies, we report evidence for the existence of an endogenous biosynthetic route for MEG production from D-xylose in S. cerevisiae which consists of phosphofructokinase and fructose-bisphosphate aldolase, the two key enzymes in the glycolytic pathway. Further metabolic engineering and process optimization yielded a strain capable of producing up to 4.0 g/L MEG, which is the highest titer reported in yeast to-date.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Oxidative Functionalization of Long-Chain Liquid Alkanes by Pulsed Plasma Discharges at Atmospheric Pressure

In this work, we introduce the oxidation of long aliphatic alkanes using non-thermal, atmospheric plasma processing as an eco-friendly route for organic synthesis. A pulsed dielectric barrier discharge in He/O 2 gas mixtures was employed to functionalize n-octadecane. C 18 secondary alcohols and ketones were the main products, with an optimal molar yield of ~29.2%. Prolonged treatment resulted in the formation of dialcohols, diketones, and higher molecular weight oxygenates. Lighter hydrocarbon products and decarboxylation to CO 2 were also observed at longer treatment times and higher power inputs. A maximum energy yield of 5.48 × 10 –8 mol/J was achieved at short treatment times and high powers, associated with higher selectivity to primary oxygenates. Direct hydroxylation of alkyl radicals, as well as disproportionation reactions, are proposed as the main pathways to alcohols and ketones. The results hold promise for functionalizing long hydrocarbon molecules at ambient conditions using catalyst-free plasma discharges.

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

Genetically engineered oleaginous yeast Lipomyces starkeyi for sesquiterpene a-zingiberene production

In this study we demonstrate that transgenic Lipomyces starkeyi strains expressing a ?-zingiberene synthase gene from Lemon basil or Hall’s panicgrass can produce up to 17 mg/l of ?-zingiberene in yeast extract peptone dextrose (YPD) medium containing 4% glucose. Following these findings, the transgenic strain was examined in 8% glucose media with C/N ratios of 20 or 80, and YPD. YPD medium resulted in 59.2 mg/l??-zingiberene accumulation. We further improved ?-zingiberene production by over-expression of selected genes from mevalonate pathway and achieved 145% improvement in ?-zingiberene synthesis. The growth medium was optimized for ?-zingiberene production, which resulted in 14.9% higher titer than YPD medium. The final transgenic strain produced 700 mg/l ?-zingiberene in fed-batch bioreactor culture. This study opens a new synthetic route to produce ?-zingiberene or other terpenoids in the oleaginous yeast L. starkeyi and establishes this yeast as a platform for jet fuel biosynthesis.

Dai, Ziyu↗
DOE OSTI2023

Efficient Network Partitioning: Application for Decentralized State Estimation in Power Distribution Grids

Increase in the proliferation of distributed energy resources require real-time situational awareness for efficient grid operations. State estimation plays an important role for the real-time control and management of the power grid. As the sensing infrastructure grows, aggregating and handling high volumes of data at a centralized location is extremely difficult. To address this challenge, this paper first proposes a novel and efficient hier-archical spectral clustering-based network partitioning algorithm followed by a decentralized compressive sensing (DCS)-based state estimation. The applicability of the proposed network partitioning algorithm is tested on an IEEE 123-bus network, an IEEE 8,500-node system, and a 6,000+ node distribution network. The results shows that the proposed approach efficiently divides the network into multiple sub-networks with the minimum number of edge connections among the neighbors. Then, we perform DCS-based state estimation on the 6,000+ node distribution network after dividing the network into 18 optimal partitions. Simulation results show that the DCS-based state estimation recovers the system states with high accuracy and low complexity.

alternating direction method of multipliers↗
NASA NTRS1981

Synthesis of perfluoroalkylene dianilines

The objective of this contrast was to optimize and scale-up the synthesis of 2,2-bis(4-aminophenyl)-hexafluoropropane and 1,3-bis(4-aminophenyl)hexafluoropropane, as well as to explore avenues to other perfluoroalkyl-bridged dianilines. Routes other than Friedel-Crafts reaction leading to 2,2-bis(4-aminophenyl)hexafluoropropane were investigated. The processes utilizing bisphenol-AF were all unsuccessful; reactions aimed at the production of 4-(hexafluoro-2-halo-isopropyl)aniline from the hydroxyl intermediate failed to yield the desired products. Tailoring the conditions of the Friedel-Crafts reaction of 4-(hexafluoro-2-hydroxyisopropyl)aniline, aniline, and aluminum chloride by using hydrochloride salts and selecting optimum reagent ratios, reaction times, and temperature resulted in approx. 20% yield of pure crystallized 2,2-bis(4-aminophenyl)hexafluoropropane in 0.2 mole reaction batches. Yields up to approx. 40% were realized in small, approx. 0.01 mole, batches. The synthesis of 1,3-bis(4-aminophenyl)hexafluoropropane starting with perfluoroglutarimidine was reinvestigated. The yield of the 4-step reaction sequence giving 1,3-bis(4-acetamidophenyl)hexafluoropropane was raised to 44%. The yield of the subsequent hydrolysis process was improved by a factor of approx. 2. Approaches to prepare other perfluoroalkyl-bridged dianilines were unsuccessful. Reactions reported to proceed readily with trifluoromethyl substituents failed when longer chain perfluoroalkyl groups were employed.

Paciorek, K. L.↗
NASA NTRS2012

I-FORCAST: Rapid Flight Planning Tool

I-FORCAST (Instrument - Field of Regard Coverage Analysis and Simulation Tool) is a flight planning tool specifically designed for quickly verifying the feasibility and estimating the cost of airborne remote sensing campaigns (see figure). Flights are simulated by being broken into three predefined routing algorithms as necessary: mapping in a snaking pattern, mapping the area around a point target (like a volcano) with a star pattern, and mapping the area between a list of points. The tool has been used to plan missions for radar, lidar, and in-situ atmospheric measuring instruments for a variety of aircraft. It has also been used for global and regional scale campaigns and automatically includes landings when refueling is required. The software has been compared to the flight times of known commercial aircraft route travel times, as well as a UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar) campaign, and was within 15% of the actual flight time. Most of the discrepancy is due to non-optimal flight paths taken by actual aircraft to avoid restricted airspace and used to follow landing and take-off corridors.

Oaida, Bogdan↗
DOE OSTI2019

Optimal placement of data concentrators for expansion of the smart grid communications network

Evolving power systems with increasing renewables penetration, along with the development of the smart grid, calls for improved communication networks to support these distributed generation sources. Automatic and optimal placement of communication resources within the advanced metering infrastructure is critical to provide a high‐performing, reliable, and resilient power system. Three network design formulations based on mixed‐integer linear and non‐linear programming approaches are proposed to minimise network congestion by optimising residual buffer capacity through the placement of data concentrators and network routeing. Results on a case study show that the proposed models improve network connectivity and robustness, and increase average residual buffer capacity. Maximising average residual capacity alone, however, results in both oversaturated and underutilised nodes, while maximising either minimum residual capacity or total reciprocal residual capacity can yield much‐improved network load allocation. Consideration of connection redundancy improves network reliability further by ensuring quality‐of‐service in the event of an outage. Analysis of multi‐period network expansion shows that the models do not deviate significantly from optimal when used progressively (within 5% deviation), and are effective for utility planners to use for smart grid expansion.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

The coastal streamflow flux in the Regional Arctic System Model

The coastal streamflow flux from the Arctic drainage basin is an important driver of dynamics in the coupled ice-ocean system. Comprising more than one third of the total freshwater flux into the Arctic Ocean, streamflow is a key component of the regional and global freshwater cycle. To better represent the coupling of the streamflow flux to the ocean, we have developed and applied the RVIC streamflow routing model within the Regional Arctic System Model (RASM). The RASM is a high-resolution regional Earth System Model whose domain includes all of the Arctic drainage basin. Here in this paper, we introduce the RVIC streamflow routing model, detailing its application within RASM and its advancements in terms of representing high-resolution streamflow processes. We evaluate model simulated streamflow relative to in situ observations and demonstrate a method for improving model performance using a simple optimization procedure. We also present a new, spatially and temporally consistent, high-resolution data set of coastal freshwater fluxes for the Arctic drainage basin and surrounding areas that is based on a fully coupled RASM simulation and intended for use in Arctic Ocean modeling applications. This data set is evaluated relative to other coastal streamflow data sets commonly used by the ocean modeling community. We demonstrate that the RASM-simulated streamflow flux better represents the annual cycle than existing data sets, especially in ungauged areas. Finally, we assess the impact that streamflow has on the coupled ice-ocean system, finding that the presence of streamflow leads to reduced sea surface salinity, increased sea surface temperatures, and decreased sea ice thickness.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Rerouting reductant flux via protein tethering enhances biohydrogen production in Thermococcus kodakarensis

Microbes that generate copious amounts of hydrogen (H 2 ) via dark fermentation are a promising means to evolve and improve renewable biofuels. Many anaerobic hyperthermophilic archaea, such as the fast-growing, genetically tractable, heterotroph Thermococcus kodakarensis, produce generous quantities of H2 and provide an idealized platform to further optimize naturally high levels of biohydrogen reduction. Precise genetic manipulations and modifications to growth conditions have already resulted in substantial increases to H2 output but additional improvements are desired. An unexamined and potentially valuable route towards increased H 2 production is to tether select electron donor and acceptor proteins together to reroute and maximize the flow of electrons towards H 2 production. Such strategies have shown promise in Bacteria and Eukarya but have not yet been investigated in thermophilic Archaea. Here, we generate and evaluate twelve novel T. kodakarensis strains wherein a proteinaceous electron carrier (a ferredoxin, Fd) is physically tethered to the membrane-bound-hydrogenase (MBH), the sole H 2 producing enzyme, to direct electron flux towards biohydrogen generation. Growth assessments and H 2 output measurements demonstrate that strains encoding protein-fusions evolve up to ~ 40% more H2 per cell than the host strain. Eliminating H 2 consumption and alternative routes of electron sinks in concert with protein tethering further increased H2 output per cell for a maximum increase of ~ 66% over the host strain. Our results demonstrate that rerouting electron flux via protein tethering coupled with the elimination of reductant sinks is a promising means towards improved biohydrogen production in T. kodakarensis. KEY POINTS: Protein tethering between redox proteins can reroute electron flux in vivo. Enforced protein proximity results in ~ 40% increases in H2 production per cell. Protein-tethering provides a generalizable framework to redirect redox metabolism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Impact of cyber attacks on distributed compressive sensing based state estimation in power distribution grids

Modern power distribution grids suffer from multiple vulnerabilities due to the tight integration between the physical system and the cyber infrastructure. Sophisticated and malicious cyber attacks continue to adversely impact the grid operation leading to performance degradation, service interruption, and grid failure. State estimation plays an essential role in grid monitoring and advancing cyber-attack situational awareness. In this regard, this paper first proposes a distributed compressive sensing (CS) state estimation approach for an unobservable distribution grid. Further, the proposed distributed CS approach divides the distribution grid into sub-areas to perform local state estimation. Then an alternating direction method of multipliers (ADMM) based iterative information exchange among neighboring areas is employed to complete the estimation process. In this estimation process, the impact of loss of measurement data, false data injection (FDI), replay, and neighborhood cyber-attacks is analyzed. Extensive simulations are performed on the IEEE 37-bus and IEEE 123-bus standard networks to demonstrate the algorithm’s robustness to the aforementioned cyber-attacks. A quantitative analysis of computational complexity and simulation time of the distributed CS based approach is also presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗