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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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This software is to implement real-time energy dispatch for distributed energy resources such as distributed PV, using distributed control algorithm that NREL has developed. The software is developed using Python and is available as open-source.
The degradation of the zirconium cladding may limit nuclear fuel performance. In the high temperature environment of a reactor, the zirconium in the cladding corrodes, releasing hydrogen in the process. Some of this hydrogen is absorbed by the cladding in a highly inhomogeneous manner. The distribution of the absorbed hydrogen is extremely sensitive to temperature and stress concentration gradients. The absorbed hydrogen tends to concentrate near lower temperatures. This hydrogen absorption and hydride formation can cause cladding failure. This project set out to improve the hydrogen distribution prediction capabilities of the BISON fuel performance code. The project was split into two primary sections, first was the use of a high fidelity multi-physics coupling to accurately predict temperature gradients as a function of r, θ , and z, and the second was to use experimental data to create an analytical hydrogen precipitation model. The Penn State version of thermal hydraulics code COBRA-TF (CTF) was successfully coupled to the DeCART neutronics code. This coupled system was verified by testing and validated by comparison to FRAPCON data. The hydrogen diffusion and precipitation experiments successfully calculated the heat of transport and precipitation rate constant values to be used within the hydrogen model in BISON. These values can only be determined experimentally. These values were successfully implemented in precipitation, diffusion and dissolution kernels that were implemented in the BISON code. The coupled output was fed into BISON models and the hydrogen and hydride distributions behaved as expected. Simulations were conducted in the radial, axial and azimuthal directions to showcase the full capabilities of the hydrogen model.
In order to improve quantification of the spatial distribution of carbon sinks and sources in the conterminous US, we conduct a nested global atmospheric inversion with detailed spatial information on crop production and consumption. County-level cropland net primary productivity, harvested biomass, soil carbon change, and human and livestock consumption data over the conterminous US are used for this purpose. Time-dependent Bayesian synthesis inversions are conducted based on CO₂ observations at 210 stations to infer CO₂ fluxes globally at monthly time steps with a nested focus on 30 regions in North America. Prior land surface carbon fluxes are first generated using a biospheric model, and the inversions are constrained using prior fluxes with and without adjustments for crop production and consumption over the 2002–2007 period. After these adjustments, the inverted regional carbon sink in the US Midwest increases from 0.25 ± 0.03 to 0.42 ± 0.13 Pg C yr⁻¹, whereas the large sink in the US southeast forest region is weakened from 0.41 ± 0.12 to 0.29 ± 0.12 Pg C yr⁻¹. These adjustments also reduce the inverted sink in the west region from 0.066 ± 0.04 to 0.040 ± 0.02 Pg C yr⁻¹ because of high crop consumption and respiration by humans and livestock. The general pattern of sink increases in crop production areas and sink decreases (or source increases) in crop consumption areas highlights the importance of considering the lateral carbon transfer in crop products in atmospheric inverse modeling, which provides a reliable atmospheric perspective of the overall carbon balance at the continental scale but is unreliable for separating fluxes from different ecosystems.
This paper presents an optimal control theory that accounts for variable time intervals in the information distribution to control effectors in a distributed microprocessor based flight control system. The theory is developed using a linear process model for the aircraft dynamics and the information distribution process is modeled as a variable time increment process where, at the time that information is supplied to the control effectors, the control effectors know the time of the next information update only in a stochastic sense. An optimal control problem is formulated and solved that provides the control law that minimizes the expected value of a quadratic cost function. An example is presented where the theory is applied to the control of the longitudinal motions of the F8-DFBW aircraft. Theoretical and simulation results indicate that, for the example problem, the optimal cost obtained using a variable time increment Markov information update process where the control effectors know only the past information update intervals and the Markov transition mechanism is almost identical to that obtained using a known uniform information update interval.
The age distribution of galactic cosmic rays in the diffusion approximation is calculated. The influence of the scale height of the spatial source distribution on the mean age of particles arriving at the solar system is discussed. The broader the source distribution with respect to the galactic plane, the longer the mean age. This result provides a natural explanation for the shorter mean age of secondary cosmic rays compared to primary cosmic rays necessary for the understanding of the observed secondary/primary ratio.
The Goddard Space Flight Center (GSFC) Distributed Active Archive Center (DAAC) has been operational since October 1, 1993. Its mission is to support the Earth Observing System (EOS) by providing rapid access to EOS data and analysis products, and to test Earth Observing System Data and Information System (EOSDIS) design concepts. One of the challenges is to ensure quick and easy retrieval of any data archived within the DAAC's Data Archive and Distributed System (DADS). Over the 15-year life of EOS project, an estimated several Petabytes (10(exp 15)) of data will be permanently stored. Accessing that amount of information is a formidable task that will require innovative approaches. As a precursor of the full EOS system, the GSFC DAAC with a few Terabits of storage, has implemented a prototype of a constraint-based task and resource scheduler to improve the performance of the DADS. This Honeywell Task and Resource Scheduler (HTRS), developed by Honeywell Technology Center in cooperation the Information Science and Technology Branch/935, the Code X Operations Technology Program, and the GSFC DAAC, makes better use of limited resources, prevents backlog of data, provides information about resources bottlenecks and performance characteristics. The prototype which is developed concurrently with the GSFC Version 0 (V0) DADS, models DADS activities such as ingestion and distribution with priority, precedence, resource requirements (disk and network bandwidth) and temporal constraints. HTRS supports schedule updates, insertions, and retrieval of task information via an Application Program Interface (API). The prototype has demonstrated with a few examples, the substantial advantages of using HTRS over scheduling algorithms such as a First In First Out (FIFO) queue. The kernel scheduling engine for HTRS, called Kronos, has been successfully applied to several other domains such as space shuttle mission scheduling, demand flow manufacturing, and avionics communications scheduling.
We have developed and deployed a distributed-parallel storage system (DPSS) in several high speed asynchronous transfer mode (ATM) wide area networks (WAN) testbeds to support several different types of data-intensive applications. Architecturally, the DPSS is a network striped disk array, but is fairly unique in that its implementation allows applications complete freedom to determine optimal data layout, replication and/or coding redundancy strategy, security policy, and dynamic reconfiguration. In conjunction with the DPSS, we have developed a 'top-to-bottom, end-to-end' performance monitoring and analysis methodology that has allowed us to characterize all aspects of the DPSS operating in high speed ATM networks. In particular, we have run a variety of performance monitoring experiments involving the DPSS in the MAGIC testbed, which is a large scale, high speed, ATM network and we describe our experience using the monitoring methodology to identify and correct problems that limit the performance of high speed distributed applications. Finally, the DPSS is part of an overall architecture for using high speed, WAN's for enabling the routine, location independent use of large data-objects. Since this is part of the motivation for a distributed storage system, we describe this architecture.
The centerline total enthalpy of arc jet flow is determined using laser induced fluorescence of oxygen and nitrogen atoms. Each component of the energy, kinetic, thermal, and chemical can be determined from LIF measurements. Additionally, enthalpy distributions are inferred from heat flux and pressure probe distribution measurements using an engineering formula. Average enthalpies are determined by integration over the radius of the jet flow, assuming constant mass flux and a mass flux distribution estimated from computational fluid dynamics calculations at similar arc jet conditions. The trends show favorable agreement, but there is an uncertainty that relates to the multiple individual measurements and assumptions inherent in LIF measurements.
Size distributions of nebular solids in chondrites suggest an efficient sorting of these early forming objects within the protoplanetary disk. The effect of this sorting has been documented by investigations of modal abundances of CAIs (e.g., [1-4]) and chondrules (e.g., [5-8]). Evidence for aerodynamic sorting in the disk is largely qualitative, and needs to be carefully assessed. It may be a way of concentrating these materials into planetesimal-mass clumps, perhaps 100 fs of ka after they formed. A key parameter is size/density distributions of particles (i.e., chondrules, CAIs, and metal grains), and in particular, whether the radius-density product (rxp) is a better metric for defining the distribution than r alone [9]. There is no consensus between r versus rxp based models. Here we report our initial tests and preliminary results, which when expanded will be used to test the accuracy of current dynamical disk models.
Crystal imperfections limit the efficiency of multicrystalline silicon solar cells. Recombination through traps is more prominent in areas with high density of crystal imperfections. A method to visualize the distribution of radiative emission from Shockley Read Hall recombination in silicon is demonstrated. We use hyperspectral photoluminescence, a fast non-destructive method, to image radiatively active recombination processes on a set of 50 wafers through a silicon block. The defect related emission lines D1 and D2 may be detected together or alone. The D3 and D4 seem to be correlated if we assume that an emission at the similar energy as D3 (VID3) is caused by a separate mechanism. The content of interstitial iron (Fe{sub i}) correlates with D4. This method yields a spectral map of the inter band gap transitions, which opens up for a new way to characterize mechanisms related to loss of efficiency for solar cells processed from the block.
The Lyman-α forest is a highly non-linear field with considerable information available in the data beyond the power spectrum. The flux probability distribution function (PDF) has been used as a successful probe of small-scale physics. In this paper we argue that measuring coefficients of the Legendre polynomial expansion of the PDF offers several advantages over measuring the binned values as is commonly done. In particular, the n -th Legendre coefficient can be expressed as a linear combination of the first n moments, allowing these coefficients to be measured in the presence of noise and allowing a clear route for marginalisation over mean flux. Moreover, in the presence of noise, our numerical work shows that a finite number of coefficients are well measured with a very sharp transition into noise dominance. This compresses the available information into a small number of well-measured quantities. In conclusion, we find that the amount of recoverable information is a very non-linear function of spectral noise that strongly favors fewer quasars measured at better signal to noise.
We report the results of semiclassical calculations of the asymmetric molecular-frame photoelectron angular distributions for C 1s ionization of CO{sub 2} measured with respect to the CO{sup +} and O{sup +} ions produced by subsequent Auger decay, and show how the decay event can be used to probe ultrafast molecular dynamics of the transient cation. The fixed-nuclei photoionization amplitudes were constructed using variationally obtained electron-molecular-ion scattering wave functions. The amplitudes are then used in a semiclassical manner to investigate their dependence on the nuclear dynamics of the cation. The method introduced here can be used to study other core-level ionization events.
We use the continuum shell model approach to explore the resonance width distribution in unstable many-body systems. The single-particle nature of a decay, the few-body character of the interaction Hamiltonian, and the collectivity that emerges in nonstationary systems due to the coupling to the continuum of reaction states are discussed. Correlations between the structures of the parent and daughter nuclear systems in the common Fock space are found to result in deviations of decay width statistics from the Porter-Thomas distribution.
Blockchain is the next generation of secure data management that creates near-immutable decentralized storage. Secure cryptography created a niche for blockchain to provide alternatives to well-known security compromises. However, design bottlenecks with traditional blockchain data structures scale poorly with increased network usage and are extremely computation-intensive. This made the technology difficult to combine with limited devices, like those in Internet of Things networks. In protocols like IOTA, replacement of blockchain's linked-list queue processing with a lightweight dynamic ledger showed remarkable throughput performance increase. However, current stochastic algorithms for ledger construction suffer distinct trade-offs between efficiency and security. This work proposed a machine-learning approach with a multi-arm bandit that resolved these issues and was designed for auditing on limited devices. This algorithm was tested in a reinforcement-learning environment simulating the IOTA ledger's construction with a decision tree. This study showed through regret analysis and experimentation that this approach was secure against impulse manipulation attacks while remaining energy-efficient. Although the IOTA protocol was a pioneer for lightweight distributed ledgers, it is expected that future blockchain protocols will adopt techniques similar to those presented in this work.
The rapid adoption of photovoltaic (PV) systems combined with falling prices of energy storage is paving the way for a future in which customers could locally supply their energy needs and export surplus power to the grid. However, reverse power flow from multiple sites in a network can cause overvoltage that decreases system reliability and the utilization level of PV system. In this paper, we present a two-stage approach to solve the energy coordination problem in distribution networks. In the first stage, a household with PV and energy storage is optimized to allow customers to adopt different control strategies such as load following and tariff arbitrage. We show that such customer-led control strategies can cause reverse power flows during peak PV generation periods, thus resulting in overvoltage. In such cases, the second stage of the proposed approach is called upon to solve a fairness-based energy coordination problem that can maintain voltages within limits while maximizing the PV generation while fairly distributing the actions among all the PV systems. As a result, each of the resources in the network has equal opportunity to export power and shares the responsibility of voltage regulation. Simulation studies have been carried out on the IEEE 13-bus test feeder to verify the effectiveness of the proposed approach.
Utilities around the world are experiencing change with the increasing digitalization of their systems and those of their customers. Efforts to decarbonize the electric power system have led to growth in renewable energy resources, particularly distributed energy resources (DERs), such as generation, storage, and flexible load, both in front of and behind the meter. As this change occurs in any given utility service area, new tools, such as advanced distribution management systems (ADMSs), are needed to manage utility operations, planning, and business issues, some of which are discussed here.