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At least 1,063 records · Page 59

Ion distributions at the dayside magnetopause

Ion phase space distribution, from the AMPTE UKS ion instrument, for a crossing of the dayside magnetopause on October 2, 1984, during typical southward IMF conditions are presented. D-shaped field-aligned phase space distributions of magnetosheath plasma earthward of and hot magnetospheric ions sunward of the magnetopause current layer are observed. The existence of such D-shaped magnetosheath plasma distributions has been predicted as a signature of reconnection. In addition, the observed ion distributions are in stress balance across the magnetopause, and the de Hoffman-Teller frame velocity obtained from the stress balance calculation is in agreement with the observed distribution function cutoff speed. These new observations thus provide further evidence that, at least for southward IMF conditions, reconnection is an important mechanism by which solar wind plasma penetrates into the magnetosphere.

Smith, M. F.↗

Solar UV Radiation and the Origin of Life on Earth

We have started a comprehensive, interdisciplinary study of the influence of solar ultraviolet radiation on the atmosphere of of the early Earth. We plan to model the chemistry of the Earth atmosphere during its evolution, using observed UV flux distributions of early solar analogs as boundary conditions in photochemical models of the Earth's atmosphere. The study has four distinct but interlinked parts: (1) Establishing the radiation of the early Sun; (2) Determining the photochemistry of the early Earth's atmosphere; (3) Estimating the rates of H2 loss from the atmosphere; and (4) Ascertaining how sensitive is the photochemistry to the metallicity of the Sun. We are currently using STIS and EUVE to obtain high-quality far-UV and extreme-UV observations of three early-solar analogs. We will perform a detailed non-LTE study of each stars, and construct theoretical model photosphere, and an empirical model chromospheres, which can be used to extrapolate the continuum to the Lyman continuum region. Given a realistic flux distribution of the early Sun, we will perform photochemical modeling of weakly reducing primitive atmospheres to determine the lifetime and photochemistry of CH4. In particular, we will make estimates of the amount of CH4 present in the prebiotic atmosphere, and estimate the atmospheric CH4 concentration during the Late Archean (2.5-3.0 b.y. ago) and determine whether it would have been sufficiently abundant to help offset reduced solar luminosity at that time. Having obtained a photochemical model, we will solve for the concentrations of greenhouse gasses and important pre-biotic molecules, and perform a detailed radiative transfer calculations to compute the UV flux reaching the surface.

Heap, Sara R.↗

Microstructure Quantification and Random Forest Regression Models for Li4Ti5O12–Ni Property Prediction

All-solid-state structural lithium-ion batteries are sought to enable all-electric propulsion in next generation aerospace concepts through improved safety and systems level weight savings. In this work, the influence of processing conditions on microstructural evolution was evaluated for anode composites of strain-free Li4Ti5O12 and metallic nickel current collector. Beyond size distributions, this study explored methods of quantifying microstructural features that describe changes in the spatial distribution and coalescence of nickel particles as a function of sample composition and sintering conditions. Processing-microstructure-property relationships were described by microstructure quantifiers including nickel particle count per area, nearest neighbor distance distribution, and edge-to-edge distance distribution. Machine learning methods were applied to compare the relative influence of processing conditions and microstructural features on electrical conductivity and mechanical strength to optimize for simultaneous energy storage and load bearing performance. Insights gained from this work inform future evaluation of alternative energy storage materials and microstructures for multifunctional performance, and generation of microstructural descriptors strengthens modeling across length scales.

anode↗

X-Ray Characterization of Real Fuel Sprays for Gasoline Direct Injection

Here, the effects of fuel blend properties on spray and injector performance has been investigated in a side-mount injector for gasoline direct injection (GDI) using two certification fuel blends: Euro 5 and Euro 6. Several X-ray diagnostic techniques were conducted to characterize the injector and spray morphology. Detailed internal geometry of the GDI injector was resolved to 1.8 μm, through the use of hard X-ray tomography. The geometry characterization of this six-hole GDI, side mount injector, quantifies relevant hole and counterbore dimensions and reveals the intricate details within the flow passages, including surface roughness and micron-sized features. Internal valve motion was measured with a temporal resolution of 20 μs and a spatial resolution of 2.0 μs, for three injection pressures and several injector energizing strategies. The needle motion for both fuels exhibits similar lift profiles for common energizing commands. A combination of X-ray radiography and ultra-small-angle X-ray scattering (USAXS) was used to characterize the fuel mass distribution and the droplet sizing, respectively. Tomographic spray radiography revealed the near-nozzle distribution of fuel mass for each of the fuels and the asymmetry produced by the angled nozzles. Under evaporative conditions, the two fuels show minor differences in peak fuel mass distribution during steady injection, though both exhibit fluctuations in injection during the early, transient phase. USAXS measurements of the path-specific surface area of the spray indicated lower peak values for the more evaporative conditions in the near nozzle region.

09 BIOMASS FUELS↗

Vertical distribution of boundary layer new particle formation and implications for nanoparticle growth mechanisms (Final Report)

New particles can form high above ground in the atmosphere before such formation events are observed by ground-based instruments. Once formed, these particles can take up significant amounts of water vapor, which has implications on the mechanisms by which nanoparticles grow and, ultimately, impact cloud formation processes. These observations motivated the research performed in this project using a combination of modeling, laboratory experiments, and the analysis of field observations. We hypothesized is that ground-based measurements do not always accurately represent the location and timing of new particle formation events, nor do they adequately characterize the dominant physical and chemical processes that are responsible for the subsequent growth of newly formed particles. Essentially, we wanted to study the new particle formation process under conditions that we expect may be more relevant to the actual location in the atmosphere where such events take place, which are often characterized by higher relative humidities, lower temperatures, and a broader range of precursors and oxidants compared to those observed at ground level. This project had two main objectives, each of which directly addressed our hypothesis. Our first is to investigate the timing, distribution, meteorological conditions, and nanoparticle properties associated with boundary layer new particle formation through the analysis of ARM field campaigns such as HI-SCALE and long-term observations and observations performed in other locales such as in China and India where atmospheric conditions could play a crucial role in determining the mechanisms of new particle formation. This activity provided a comprehensive description, both in time and in space, of the gases and nanoparticle properties that are responsible for these events. We also performed modeling studies to explore the vertical profile and timing of new particle formation events from these campaigns. Our second objective was to perform laboratory and process-level modeling studies to investigate the role that conditions such as low ambient temperature, high relative humidity, and different oxidants such as nitrate radical play in determining unique chemical pathways for nanoparticle growth. In doing so, we revisited the representation of nanoparticle growth in global models and updated assumptions of formation and growth based on the findings of the field, laboratory, and process-level-model work. Our research provides crucial insights into the most important regions of the atmospheric boundary layer for future observational and modeling studies. It also identifies the most relevant environmental conditions, precursors, and oxidants that are responsible for nanoparticle growth, which will aid in the design of laboratory studies and process-level model experiments. The unique pathways that we discovered can be incorporated into regional and global models, thereby improving predictions and attribution of the role of new particle formation in, e.g., air pollution formation and cloud properties.

54 ENVIRONMENTAL SCIENCES↗

Electrochemical Manipulation and Radiolytic Evaluation of Organic Phase Neptunium

Presentation for Seed LDRD proposal presentation: This Seed LDRD research proposes to test an innovative approach to precisely control the oxidation state distribution of neptunium (Np) under used nuclear fuel (UNF) reprocessing conditions using novel electrochemical methods. Current UNF reprocessing technologies are not financially viable in the US, requiring significant scientific and technological innovation to improve cost efficiency. Reducing the number of process cycles is one avenue for increasing cost efficiency, of which resolving the challenge associated with isolating Np is critical. Under envisioned process conditions, Np is present in a mixture of extractable (Np(IV) and Np(VI)) and inextractable (Np(V)) oxidation states, the distribution of which is dependent on several factors, including ionizing radiation dose, that change throughout a reprocessing scheme. Consequently, Np unintentionally partitions into various UNF reprocessing phases and product streams, ultimately increasing the number of process cycles to isolate UNF components. Here, we propose to employ novel, high surface area, optically transparent, Ligand Modified tin-doped indium oxide Electrodes (LMES). These LMEs bind Np, and therefore enable concurrent generation and spectroscopic characterization of Np oxidation states in organic solutions. These proof-of-concept experiments will: (i) facilitate optimization of the proposed electrochemical system conditions for Np oxidation state manipulation; (ii) identify the accessible electrochemical window for Np complexes in the organic phase; (iii) report characteristic optical spectra for each accessible complexed Np oxidation state; and (iv) determine the lifetime and partitioning of a given atypical Np oxidation state in the organic phase in the presence and absence of ionizing radiation fields. The data gathered by this Seed LDRD will provide support for the design of an electrochemical process concept for the precise manipulation of Np oxidation states in UNF reprocessing solvent systems, with the intention of providing advanced control over Np mass transfer, and thus greater process efficiency and economy.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Robust Distribution System Load Restoration With Time-Dependent Cold Load Pickup

Service restoration is one of the critical functions to enable the future self-healing distribution system. To restore the distribution system in a timely and reliable manner, the realistic system operating conditions need to be accurately characterized. Here, two main factors that have great impacts on distribution system restoration (DSR) in practice are investigated. First, cold load pickup (CLPU), generally caused by thermostatically controlled loads (TCLs), is a common phenomenon after an outage and shaped by the outage duration. However, the time-dependent behaviors of CLPU are rarely considered in literature. In this paper, the operating state evolution of TCLs after an outage is analyzed to characterize time-dependent CLPU. And the time-dependent CLPU is analytically embedded in DSR to accurately represent the actual behaviors of the restored loads. Second, it is difficult to predict loads that fluctuate during DSR due to the lack of real-time measurement data. Accordingly, a robust DSR based on the information gap decision theory (IGDT) is proposed to address this challenge, fully considering the uncertainty of CLPU. The proposed models are tested in IEEE 13-node and 123-node test feeders. Simulation results demonstrate that the time-dependent CLPU model and the uncertainty modeling of CLPU can accurately capture the actual behaviors of loads with TCLs after an outage, which greatly improves DSR decisions in practice.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Flow establishment in a generic scramjet combustor

The establishment of a quasi-steady flow in a generic scramjet combustor was studied for the case of a time varying inflow to the combustor. Such transient flow is characteristic of the reflected shock tunnel and expansion tube test facilities. Several numerical simulations of hypervelocity flow through a straight duct combustor with either a side wall step fuel injector or a centrally located strut injector are presented. Comparisons were made between impulsively started but otherwise constant flow conditions (typical of the expansion tube or tailored operations of the reflected shock tunnel) and the relaxing flow produced by the 'undertailored' operations of the reflected shock tunnel. Generally the inviscid flow features, such as the shock pattern and pressure distribution, were unaffected by the time varying inlet conditions and approached steady state in approx. the times indicated by experimental correlations. However, viscous features, such as heat transfer and skin friction, were altered by the relaxing inlet flow conditions.

Jacobs, P. A.↗

A probabilistic fatigue analysis of multiple site damage

The variability in initial crack size and fatigue crack growth is incorporated in a probabilistic model that is used to predict the fatigue lives for unstiffened aluminum alloy panels containing multiple site damage (MSD). The uncertainty of the damage in the MSD panel is represented by a distribution of fatigue crack lengths that are analytically derived from equivalent initial flaw sizes. The variability in fatigue crack growth rate is characterized by stochastic descriptions of crack growth parameters for a modified Paris crack growth law. A Monte-Carlo simulation explicitly describes the MSD panel by randomly selecting values from the stochastic variables and then grows the MSD cracks with a deterministic fatigue model until the panel fails. Different simulations investigate the influences of the fatigue variability on the distributions of remaining fatigue lives. Six cases that consider fixed and variable conditions of initial crack size and fatigue crack growth rate are examined. The crack size distribution exhibited a dominant effect on the remaining fatigue life distribution, and the variable crack growth rate exhibited a lesser effect on the distribution. In addition, the probabilistic model predicted that only a small percentage of the life remains after a lead crack develops in the MSD panel.

Rohrbaugh, S. M.↗

Temporal Stability of Surface Roughness Effects on Radar Based Soil Moisture Retrieval During the Corn Growth Cycle

A representative soil surface roughness parameterization needed for the retrieval of soil moisture from active microwave satellite observation is difficult to obtain through either in-situ measurements or remote sensing-based inversion techniques. Typically, for the retrieval of soil moisture, temporal variations in surface roughness are assumed to be negligible. Although previous investigations have suggested that this assumption might be reasonable for natural vegetation covers (Moran et al. 2002, Thoma et al. 2006), insitu measurements over plowed agricultural fields (Callens et al. 2006) have shown that the soil surface roughness can change considerably over time. This paper reports on the temporal stability of surface roughness effects on radar observations and soil moisture retrieved from these radar observations collected once a week during a corn growth cycle (May 10th - October 2002). The data set employed was collected during the Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3) field campaign covering this 2002 corn growth cycle and consists of dual-polarized (HH and VV) L-band (1.6 GHz) acquired at view angles of 15, 35, and 55 degrees. Cross-polarized L baud radar data were also collected as part of this experiment, but are not used in the analysis reported on here. After accounting for vegetation effects on radar observations, time-invariant optimum roughness parameters were determined using the Integral Equation Method (IEM) and radar observations acquired over bare soil and cropped conditions (the complete radar data set includes entire corn growth cycle). The optimum roughness parameters, soil moisture retrieval uncertainty, temporal distribution of retrieval errors and its relationship with the weather conditions (e.g. rainfall and wind speed) have been analyzed. It is shown that over the corn growth cycle, temporal roughness variations due to weathering by rain are responsible for almost 50% of soil moisture retrieval uncertainty depending on the sensing configuration. The effects of surface roughness variations are found to be smallest for observations acquired at a view angle of 55 degrees and HH polarization. A possible explanation for this result is that at 55 degrees and HH polarization the effect of vertical surface height changes on the observed radar response are limited because the microwaves travel parallel to the incident plane and as a result will not interact directly with vertically oriented soil structures.

Joseph, A.T.↗

Developing and Testing a Physics Guided Machine Learning NeuralNetwork to Predict Tonal Noise Emitted by a Propeller

Artificial neural networks offer a highly nonlinear and adaptive model for predicting complex interactions between input-output parameters. However, these networks require large datasets which often exceed practical considerations in modeling experimental results. To alleviate the dataset size requirement, a method known as physics guided machine learning has been applied to construct several neural networks for predicting propeller tonal noise in the time domain over a broad range of flight conditions. Three space-filling designs, namely, Latin-Hypercube, Sphere-Packing, and Grid-Space, were used to distribute points throughout the input parameter space encompassing nondimensional flight conditions and observer geometry. Each neural network’s performance was validated by conditions outside of the training set and compared to the Propeller Analysis System tool from the NASA Aircraft Noise Prediction Program. Compared to the Grid-Space input design, the Latin-Hypercube and the Sphere-Packing designs provided a better representation of the domain for training. Regarding the network archetype, a fully connected perceptron was found to outperform the partially connected perceptron in their ability to predict tonal noise for small datasets. The black-box nature of these neural networks was also explored to understand how the networks constructed the waveform and understand why some network designs produce better models.

Propeller noise↗

Analysis of measured airfoil pressure distributions

A method for evaluating the Glauert coefficients from airfoil pressure distributions is investigated. The linear operating range of the airfoils in steady-state and periodic operating conditions are considered. A rational method for quantitatively characterizing airfoil pressure distributions relative to their geometry and aerodynamic operating environment is developed. The characteristics of the airfoil operating environment is determined from its measured pressure distribution.

Piziali, R. A.↗

Emission Spectral Measurements in the Plenum of an Arc Jet Wind Tunnel

Arc jet wind tunnel facilities are used to evaluate thermal protection system materials for re-entry vehicles. The high speed, high temperature flowfield generated by the arc jet can simulate the extreme aerodynamic heating environment experienced during re-entry so that the survivability of heat shield materials and performance of various designs options can be tested. Although the re-entry heating environment can be approximated in the arc jet facility, the flowfield only partially simulates the actual re-entry flight conditions. Reynolds numbers are not matched so that surface shear stress distributions and mass transfer rates due to ablation or other mechanisms are not modeled correctly. Unlike flight conditions the arc freestream air is in non-equilibrium because of the rapid expansion that occurs in the supersonic nozzle. To properly study the actual re-entry flow environment, computational fluid dynamics, computational chemistry and radiation models must be used. Arc jet tunnel tests serve to validate these models. To perform accurate simulations inlet and boundary-conditions are needed, which come from measurements of the flowfield. The present study is concerned with measurements in the plenum region of an arc heater. In the past, conditions in the arc heater flowfield have been predicted using simulations since conventional measurement techniques could not be used in the harsh extremely high temperature environment. The present study is part of a recent push to utilize optical techniques to help better characterize the arc jet flowfields. Emission measurements have been made in the shock layer and the constrictor section of the arc heater to determine temperatures and species number densities. LIF measurements have been made in the free stream to determine temperature and velocity.

Donohue, Jim↗

Numerical investigation of micro-galvanic corrosion in Mg alloys: Role of the cathodic intermetallic phase size and spatial distributions

Magnesium alloys are of increasing interest in structural applications due to their low-density, moderate specific strength and stiffness, recyclability, and high damping among other properties. However, the wide-scale applicability of magnesium alloys in structural applications has been limited due to many factors including its poor corrosion resistance. In this work, a numerical investigation to simulate the micro-galvanic corrosion behavior was performed to examine the influence of size and distribution of cathodic intermetallic phase (ß-Mg17Al12) in a Mg matrix. The ratio of cathodic to anodic surface area was kept constant in each simulation condition to understand the effect of size and spacing distributions. In general, fragmentation of a larger intermetallic particle into smaller ones was found to enhance the localized current density. However, the uniform distribution of this small intermetallic phase throughout the matrix was found to reduce the overall dissolution current density and hence, pitting corrosion severity.

Beura, Vikrant↗

Transient Numerical Modeling of Catalytic Channels

This paper presents a transient model of catalytic combustion suitable for isolated channels and monolith reactors. The model is a lumped two-phase (gas and solid) model where the gas phase is quasi-steady relative to the transient solid. Axial diffusion is neglected in the gas phase; lateral diffusion, however, is accounted for using transfer coefficients. The solid phase includes axial heat conduction and external heat loss due to convection and radiation. The combustion process utilizes detailed gas and surface reaction models. The gas-phase model becomes a system of stiff ordinary differential equations while the solid phase reduces, after discretization, into a system of stiff ordinary differential-algebraic equations. The time evolution of the system came from alternating integrations of the quasi-steady gas and transient solid. This work outlines the numerical model and presents some sensitivity studies on important parameters including internal transfer coefficients, catalytic surface site density, and external heat-loss (if applicable). The model is compared to two experiments using CO fuel: (1) steady-state conversion through an isothermal platinum (Pt) tube and (2) transient propagation of a catalytic reaction inside a small Pt tube. The model requires internal mass-transfer resistance to match the experiments at lower residence times. Under mass-transport limited conditions, the model reasonably predicted exit conversion using global mass-transfer coefficients. Near light-off, the model results did not match the experiment precisely even after adjustment of mass-transfer coefficients. Agreement improved for the first case after adjusting the surface kinetics such that the net rate of CO adsorption increased compared to O2. The CO / O2 surface mechanism came from a sub-set of reactions in a popular CH4 / O2 mechanism. For the second case, predictions improved for lean conditions with increased external heat loss or adjustment of the kinetics as in the first case. Finally, the results show that different initial surface-species distribution leads to different steady-states under certain conditions. These results demonstrate the utility of a lumped two-phase model of a transient catalytic combustor with detailed chemistry.

Struk, Peter M.↗

The Impact of Behind-the-Meter Heterogeneous Distributed Energy Resources on Distribution Grids: Preprint

The increasing integration of distributed energy resources (DERs) on the electric grid brings new challenges and opportunities for utility grid operations. With the rapid deployment of DERs, there is emerging interest in integrating these controllable devices with utility operations at all levels for monitoring and management. Different types of DERs such as Photovoltaics (PV), energy storage, electric vehicles (EVs), etc. have varying effects on the grid based on how and where they are deployed. Again, the DER deployment and its impact are network-dependent, while the traditional electric grids were not designed to host DERs. To understand the challenges with increasing behind-the-meter (BTM) DERs and to identify the needs in deploying advanced controls, a comprehensive grid impact study is indispensable. This paper investigates the impacts of integrating a mix of DERs in the utility distribution network in Colorado, U.S. Firstly, BTM DERs at the residential scale including distributed PV; battery energy storage systems (BESS); heating, ventilation, and air-conditioning (HVAC) load; electric water heater (EWH) load; and EVs are modeled. The impacts of integrating these resources on the distribution network are evaluated by conducting time-series simulations for different scenarios considering different days to capture the worst-case conditions. Monte Carlo simulations are conducted to generate the realistic EV charging profile. The voltage issues, substation transformer loadings, and critical nodes in the network are identified with the incorporation of uncoordinated EV charging loads and other DER in the network. This analysis helps visualize the DER impact on the grid, identify the challenges, and provides an insight into the new distribution management and control needs to enable reliable and resilient distribution grid operations. Additionally, further analysis is performed to estimate the daily residential electricity cost with the inclusion of DERs under time-of-use tariffs. The result shows the daily residential electricity cost reduced by 20:7% on average with DERs compared to the case without DERs.

27 ARPA - Advanced Research Projects Agency-Energy↗

Experimental Analysis of Distribution Network Voltage Regulation Using Smart Inverters

Smart inverters (SIs) have demonstrated their potential to provide grid services for both transmission and distribution systems. One of these grid services, distribution network voltage regulation by SIs, has the potential to improve network voltage regulation through controlling the reactive and active power output of the SIs. Voltage regulation by SIs will be distributed and might be better suited to controlling local conditions to complement traditional voltage-regulating assets, e.g., tap-changing transformers, capacitor banks, and line voltage regulators. There is a gap in the literature on comparing the SI response characteristics when the SIs are controlled by a local controller or external control signals. This paper presents an experimental study to characterize SI reactive power regulation responses to two different control methods: autonomous control and remote dispatch. We found that SI reactive power regulation responses exhibit important differences between these methods in terms of delays and ramp rate. Finally, power-hardware-in-the-loop (PHIL) tests were conducted to evaluate the performance of these two methods. The PHIL test results show that the SI response characteristics for autonomous control and remote dispatch need to be considered when planning for distribution network voltage regulation using SIs.

autonomous control↗

5G integrated edge computing platform for efficient component monitoring in coal-fired power plants

This project developed a cutting-edge 5G-integrated edge computing framework to enhance operational efficiency and reliability in coal-fired power plants through real-time component monitoring and anomaly detection. The initiative focused on leveraging distributed machine learning, federated learning, and 5G-based dynamic network slicing to support scalable, fault-tolerant monitoring environments to meet the operational requirements in industrial control systems. With a Distributed Edge Computing Service (DECS) orchestration, this project enabled federated learning at edge for condition monitoring and introduced adaptive client selection strategies to minimize communication overhead. Scalable distributed training was achieved using the Horovod framework, thus enhancing performance across edge nodes. In the realm of 5G networking, the project designed and deployed reconfigurable, QoS-aware network slicing tailored for operational technology (OT) environments, integrating software-defined networks to bolster cyber-resilience and enabling dynamic slicing for federated learning workloads. A significant milestone was the development of a virtualized ICS environment with 5G core integration—which allowed elastic and fault tolerant distributed training on real-world datasets such as NASA Bearings, Hydraulic Systems, and TEP. To broaden the impact of the project, a TRL-3 virtualized ICS testbed for research and education was designed. This project engaged several graduate and undergraduate students to conduct research on the cutting-edge technology, and it resulted in one PhD dissertation, one MS thesis, and over 14 peer-reviewed publications. With the support of this project students also participated in national cybersecurity competitions to improve their professional development skills.

20 FOSSIL-FUELED POWER PLANTS↗