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At least 217 records · Page 12

Amine functionalized supported ionic liquid membranes (SILMs) for CO 2 /N 2 separation

Supported ionic liquid membranes (SILMs), containing aprotic N-heterocyclic anion ionic liquids (AHA ILs) in an inorganic inert support, exhibit CO 2 /N 2 permselectivity values as high as 640 at 35.0 °C and 0.03 bar CO 2 , which represents conditions similar to post-combustion carbon capture (PCCC) from a natural gas power plant. A Fickian model fit to the experimental data estimates CO 2 permeability at direct air capture (DAC) conditions of 10,400 barrer and a CO 2 /N 2 permselectivity of 4000 for the best performing IL, triethyl(octyl)phosphonium 4-bromopyrazolide ([P 2228 ][4-BrPyra]). The most important criterion for high selectivity is a large equilibrium constant for binding between the IL and CO 2 , which results in high CO 2 solubility. ILs with smaller molar volumes and with no fluoroalkyl chains enhance N 2 rejection. As a result, low viscosity and high IL molar density also enhance CO 2 /N 2 permselectivity and CO 2 permeance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modeling gas–shell mixing in ICF with separated reactants

Mixing between fuel and shell materials in ICF implosions can affect implosion dynamics and even prevent ignition. We use data from a series of separated reactant experiments on the National Ignition Facility to calibrate and test the predictive power of gas–shell mix models. Two models are used to estimate fuel–shell mix: a Reynolds-averaged turbulence model and molecular diffusion. Minor uncertainties in capsule manufacture, experimental conditions, and values for mix model parameters produce significant variation in simulation results. Using input/output pairs from 1D simulations, we train Gaussian process surrogate models to predict experimental quantities of interest. The surrogates are used to construct posteriors for mix model parameters by marginalizing over uncertainties in capsule manufacture and experimental conditions. Mix models are calibrated with a subset of experimental data (neutron yields, ion temperature, and bang time) and tested using the remaining data. In general, both the diffusion and turbulence model correctly predict experimental DT and TT neutron yields. Despite having more free parameters, the turbulence model underpredicts ion temperature at high convergence ratio. Furthermore, the simpler diffusion model correctly predicts these temperatures, suggesting nonhydrodynamic gas–shell mix. The computational model consistently overpredicts DD neutron yield, indicating possible shortcomings outside of the mix model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Aemulus $\nu$: precise predictions for matter and biased tracer power spectra in the presence of neutrinos

Here we present the Aemulusν simulations: a suite of 150 (1.05 h -1 Gpc) 3 N-body simulations with a mass resolution of 3.51 × 10 10 Ω cb /0.3 h -1 M ⊙ in a wνCDM cosmological parameter space. The simulations have been explicitly designed to span a broad range in σ8 to facilitate investigations of tension between large scale structure and cosmic microwave background cosmological probes. Neutrinos are treated as a second particle species to ensure accuracy to 0.5 eV, the maximum neutrino mass that we have simulated. By employing Zel'dovich control variates, we increase the effective volume of our simulations by factors of 10-10 5 depending on the statistic in question. As a first application of these simulations, we build new hybrid effective field theory and matter power spectrum surrogate models, demonstrating that they achieve ≤ 1% accuracy for k ≤ 1 hMpc -1 and 0 ≤ z ≤ 3, and ≤ 2% accuracy for k ≤ 4 hMpc -1 for the matter power spectrum. We publicly release the trained surrogate models, and estimates of the surrogate model errors in the hope that they will be broadly applicable to a range of cosmological analyses for many years to come.

79 ASTRONOMY AND ASTROPHYSICS↗

Multiscale Data-Driven Seismic Full-Waveform Inversion With Field Data Study

Seismic full-waveform inversion (FWI), which uses iterative methods to estimate high-resolution subsurface models from seismograms, is a powerful imaging technique in exploration geophysics. In recent years, the computational cost of FWI has grown exponentially due to the increasing size and resolution of seismic data. Moreover, it is a nonconvex problem and can encounter local minima due to the limited accuracy of the initial velocity models or the absence of low frequencies in the measurements. To overcome these computational issues, we develop a multiscale data-driven FWI method based on fully convolutional networks (FCNs). In preparing the training data, we first develop a real-time style transform method to create a large set of synthetic subsurface velocity models from natural images. We then develop two convolutional neural networks with encoder-decoder structures to reconstruct the low- and high-frequency components of the subsurface velocity models, separately. To validate the performance of our data-driven inversion method and the effectiveness of the synthesized training set, we compare it with conventional physics-based waveform inversion approaches using both synthetic and field data. Finally, these numerical results demonstrate that, once our model is fully trained, it can significantly reduce the computation time and yield more accurate subsurface velocity models in comparison with conventional FWI.

58 GEOSCIENCES↗

Control Oriented Model of Cabin-HVAC System in a Long-Haul Trucks for Energy Management Applications

Super Truck II is a 48V mild hybrid class 8 truck with an all auxiliary loads powered purely by the battery pack. Electric Heating Ventilation and Air Conditioning (HVAC) load is the most prominent battery load during the hotel period, when the truck driver is resting inside the sleeper. For the PACCAR Super Truck II (ST-II) project a 48 V battery system provides the required power during the hotel period. A cabin-HVAC model estimates the electric load on the 48V battery system, allowing the control system to implement an efficient energy management strategy that avoids engine idling during the hotel period. The thermal model accounts for the sun load due to the time of day and the geographic location of the truck during the hotel period. The cabin-HVAC model has two parts. First, a grey box model with two heat exchangers (Condenser and Evaporator) working in unison with refrigerant mass flow rate as an input and HVAC load as an output. Second, a two-node cabin model formulated to estimate the cabin temperature as a function of the Global Horizontal Irradiance (GHI), HVAC load and ambient temperature. The models are calibrated using experimental cabin-HVAC system data as for long-haul class 8 truck (e.g. ST-II). Here, the model simulations show that the overall Root Mean Square Error (RMSE) value of 0.4°C between the experimental and simulated cabin temperature.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

An assessment of potential weather effects due to operation of the Space Orbiting Light Augmentation Reflector Energy System (SOLARES)

Implementation of SOLARES will input large quantities of heat continuously into a stationary location on the Earth's surface. The quantity of heat released by each of the SOlARES ground receivers, having a reflector orbit height of 6378 km, exceeds by 30 times that released by large power parks which were studied in detail. Using atmospheric models, estimates are presented for the local weather effects, the synoptic scale effects, and the global scale effects from such intense thermal radiation.

Allen, N. C.↗

Estimations of model parameters for gravity wave spectra observed by MST radar

The general theory of MST radar observations of gravity wave spectra is developed. This effort extends the previous results to include anisotropy and Doppler effects for the spectra, as well as the consequences for the multibeam configuration. The relationships between the observed one- or two-dimensional spectra for the line-of-sight velocity in the gravity wave spectra are derived. Expressions for cross spectra, as well as covariances between velocities observed on different beams, are computed. Using these results, studies are carried out to show how model parameters for gravity wave spectra can be estimated from the observed quantities. Model parameters include the variance, power law indices, anisotropy parameters, Doppler parameters, mean scale sizes, etc. Cases with different numbers of beams are investigated.

Scheffler, A. O.↗

Spectral Energy Distribution Models for Low-Luminosity Active Galactic Nuclei in LINERs

Low-luminosity active galactic nuclei (LLAGNs) represent the bulk of the AGN population in the present-day universe and they trace the low-level accreting supermassive black holes. In order to probe the accretion and jet physical properties in LLAGNs as a class, we model the broadband radio to X-rays spectral energy distributions (SEDs) of 21 LLAGNs in low-ionization nuclear emission-line regions (LINERs) with a coupled accretion-jet model. The accretion flow is modeled as an inner ADAF outside of which there is a truncated standard thin disk. We find that the radio emission is severely underpredicted by ADAF models and is explained by the relativistic jet. The origin of the X-ray radiation in most sources can be explained by three distinct scenarios: the X-rays can be dominated by emission from the ADAF, or the jet, or the X-rays can arise from a jet-ADAF combination in which both components contribute to the emission with similar importance. For 3 objects both the jet and ADAF fit equally well the X-ray spectrum and can be the dominant source of X-rays whereas for 11 LLAGNs a jet-dominated model accounts better than the ADAF-dominated model for the data. The individual and average SED models that we computed can be useful for different studies of the nuclear emission of LLAGNs. From the model fits, we estimate important parameters of the central engine powering LLAGNs in LINERs, such as the mass accretion rate and the mass-loss rate in the jet and the jet power - relevant for studies of the kinetic feedback from jets.

Nemmen, Rodrigo S.↗

An ISRU Propellant Production System to Fully Fuel a Mars Ascent Vehicle

In-Situ Resource Utilization (ISRU) will enable the long term presence of humans beyond low earth orbit. Since 2009, oxygen production from the Mars atmosphere has been baselined as an enabling technology for Mars human exploration by NASA. However, using water from the Martian regolith in addition to the atmospheric CO2 would enable the production of both liquid Methane and liquid Oxygen, thus fully fueling a Mars return vehicle. A case study was performed to show how ISRU can support NASA's Evolvable Mars Campaign (EMC) using methane and oxygen production from Mars resources. A model was built and used to generate mass and power estimates of an end-to-end ISRU system including excavation and extraction water from Mars regolith, processing the Mars atmosphere, and liquefying the propellants. Even using the lowest yield regolith, a full ISRU system would weigh 1.7 mT while eliminating the need to transport 30 mT of ascent propellants from earth.

Mars Surface↗

Improved Cost Estimates to Boost Pumped Storage Hydropower Construction

Pumped storage hydropower is often overlooked in future grid planning efforts, in part because the cost to build a new facility is not always clear. That's why the National Renewable Energy Laboratory (NREL), along with the U.S. Department of Energy's Water Power Technologies Office, is developing improved cost estimates and cost models to reduce that uncertainty and give developers the data they need to decide where and when to construct new PSH facilities to support the country's evolving energy grid.

ENERGY PLANNING, POLICY, AND ECONOMY,HYDRO ENERGY↗

Phase change energy storage for solar dynamic power systems

This paper presents the results of a transient computer simulation that was developed to study phase change energy storage techniques for Space Station Freedom (SSF) solar dynamic (SD) power systems. Such SD systems may be used in future growth SSF configurations. Two solar dynamic options are considered in this paper: Brayton and Rankine. Model elements consist of a single node receiver and concentrator, and takes into account overall heat engine efficiency and power distribution characteristics. The simulation not only computes the energy stored in the receiver phase change material (PCM), but also the amount of the PCM required for various combinations of load demands and power system mission constraints. For a solar dynamic power system in low earth orbit, the amount of stored PCM energy is calculated by balancing the solar energy input and the energy consumed by the loads corrected by an overall system efficiency. The model assumes an average 75 kW SD power system load profile which is connected to user loads via dedicated power distribution channels. The model then calculates the stored energy in the receiver and subsequently estimates the quantity of PCM necessary to meet peaking and contingency requirements. The model can also be used to conduct trade studies on the performance of SD power systems using different storage materials.

Chiaramonte, F. P.↗

Sensitivity-Based Reactive Power Dispatch of DERs to Support Transmission Grid During Emergency

This paper proposes a TSO-DSO framework including DER set-point dispatch using sensitivity analysis. We address all three steps of TSO-DSO integration stating by estimating the capability curve of an unbalanced distribution system and then modeling of capability curve on the transmission side grid and estimating the reactive power needed from DSO during emergencies, and ending by dispatching the requested reactive power from TSO. The proposed interaction framework is tested on an IEEE 37-node distribution network connected to IEEE 9 bus transmission system. The simulation shows that using sensitivity-based dispatch would reduce the number of communication signals between DERs and DSO and that can decrease the risk of communication contingency.

Alkhonain, Ahmed↗

Current Observer Based Predictive Decoupled Power Control Grid-Interactive Inverter

This paper presents a sensor-less current model predictive control (MPC) scheme via a full state observer based current estimator. The grid interactive inverters’ control schemes require current and voltage sensors. Elimination of current sensor enhances the inverter reliability. This paper leverages the inherent characteristics of MPC towards robust current sensor-less grid interactive inverter with LC filter. The observer for inductor current is developed based on the existing capacitor voltage measurement. The estimator dynamic state-space matrices are then obtained through reconstruction of the inverter model with the capacitor voltage and inductor current being the state variables. The controller objectives are to regulate active and reactive power in a decoupled manner. The theoretical expectation, controller performance, and accuracy of the current estimation are verified by conducting a real-time simulation via Typhoon HIL.

Zhang, Zhen↗

Generalized Analytical Estimation of Sensitivity Matrices in Unbalanced Distribution Networks

Fast and accurate estimation of sensitivity matrices is significant for the enhancement of distribution system modeling and automation. Analytical estimations have mainly focused on voltage magnitude sensitivity to active/reactive power injections for unbalanced networks with Wye-connected loads and neglecting DERs' smart inverter functionality. Hence, this paper enhances the scope of analytical estimation of sensitivity matrices for unbalanced networks with 1- Φ, 2- Φ, and 3- Φ Delta/Wye-connected loads, DERs with smart inverter functionality, and substation/line step-voltage regulators (SVR). A composite bus model comprising of DER, Delta- and Wye-connected load is proposed to represent a generic distribution bus, which can be simplified to load, PV, or voltage-controlled bus as required. Furthermore, the proposed matrix-based analytical method consolidates voltage magnitude and angle sensitivity to active/reactive power injection and tap-position of all SVRs into a single algorithm. Extensive case studies on IEEE and EPRI networks show the accuracy and wide scope of the proposed algorithm compared to the existing benchmark method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Estimating Cosmic Ray Spectral Parameters From Simulated Detector Responses With Detector Design Implications

A simple power law model consisting of a single spectral index alpha (sub 1), is believed to be an adequate description of the galactic cosmic ray (GCR) proton flux at energies below 10(exp 13) eV, with a transition at knee energy E(sub k) to a steeper spectral index alpha(sub 2) greater than alpha(sub 1) above E(sub k). The maximum likelihood procedure is developed for estimating these three spectral parameters of the broken power law energy spectrum from simulated detector responses. These estimates and their surrounding statistical uncertainty are being used to derive the requirements in energy resolution, calorimeter size, and energy response of a proposed sampling calorimeter for the Advanced Cosmic ray Composition Experiment for the Space Station (ACCESS). This study thereby permits instrument developers to make important trade studies in design parameters as a function of the science objectives, which is particularly important for space-based detectors where physical parameters, such as dimension and weight, impose rigorous practical limits to the design envelope.

Howell, L. W.↗

A multi-variance analysis in the time domain

Recently a new technique for characterizing the noise processes affecting oscillators was introduced. This technique minimizes the difference between the estimates of several different variances and their values as predicted by the standard power law model of noise. The method outlined makes two significant advancements: it uses exclusively time domain variances so that deterministic parameters such as linear frequency drift may be estimated, and it correctly fits the estimates using the chi-square distribution. These changes permit a more accurate fitting at long time intervals where there is the least information. This technique was applied to both simulated and real data with excellent results.

Walter, Todd↗

Dynamic Parameter Estimation with Physics-based Neural Ordinary Differential Equations

Accurate estimation of dynamic parameters of gen-erators is crucial to building a reliable model for dynamical studies and reliable operation of the power system. This paper develops a physics-based neural ordinary differential equations (ODE) approach to learn the parameters of generator dynamic model using phasor measurement units (PMU) data. We design a physics-based neural network to represent the swing equations of the power system dynamics. A loss function is defined as the difference between dynamic simulation results from the physics-based neural networks and pseudo PMU measurements. The parameters of generator dynamic model are iteratively updated using the neural ODEs and the adjoint method. By exploiting the mini-batch scheme in neural ODE training, the parameter estimation performance is significantly improved. Numerical study results on a 3-machine 9-bus system show that the proposed algorithm outperforms state-of-the-art baseline method in both computation time and dynamic parameter estimation accuracy.

24 POWER TRANSMISSION AND DISTRIBUTION↗