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NASA NTRS2015

How the Assumed Size Distribution of Dust Minerals Affects the Predicted Ice Forming Nuclei

The formation of ice in clouds depends on the availability of ice forming nuclei (IFN). Dust aerosol particles are considered the most important source of IFN at a global scale. Recent laboratory studies have demonstrated that the mineral feldspar provides the most efficient dust IFN for immersion freezing and together with kaolinite for deposition ice nucleation, and that the phyllosilicates illite and montmorillonite (a member of the smectite group) are of secondary importance.A few studies have applied global models that simulate mineral specific dust to predict the number and geographical distribution of IFN. These studies have been based on the simple assumption that the mineral composition of soil as provided in data sets from the literature translates directly into the mineral composition of the dust aerosols. However, these tables are based on measurements of wet-sieved soil where dust aggregates are destroyed to a large degree. In consequence, the size distribution of dust is shifted to smaller sizes, and phyllosilicates like illite, kaolinite, and smectite are only found in the size range 2 m. In contrast, in measurements of the mineral composition of dust aerosols, the largest mass fraction of these phyllosilicates is found in the size range 2 m as part of dust aggregates. Conversely, the mass fraction of feldspar is smaller in this size range, varying with the geographical location. This may have a significant effect on the predicted IFN number and its geographical distribution.An improved mineral specific dust aerosol module has been recently implemented in the NASA GISS Earth System ModelE2. The dust module takes into consideration the disaggregated state of wet-sieved soil, on which the tables of soil mineral fractions are based. To simulate the atmospheric cycle of the minerals, the mass size distribution of each mineral in aggregates that are emitted from undispersed parent soil is reconstructed. In the current study, we test the null-hypothesis that simulating the presence of a large mass fraction of phyllosilicates in dust aerosols in the size range 2 m, in comparison to a simple model assumption where this is neglected, does not yield a significant effect on the magnitude and geographical distribution of the predicted IFN number. Results from sensitivity experiments are presented as well.

Dust↗

NASA NTRS2019

Microphysical Retrievals from Simultaneous Measurements by Airborne and Ground Radars during OLYMPEX

The OLYMPEX field campaign took place over the Olympic Peninsula of Washington during winter 2015-2016. During the intensive observing period, several aircraft flights obtained multi-frequency airborne radar measurements at X-, Ku-, Ka, and W-band from radars aboard the ER-2 and DC-8 aircraft. In addition, ground radars at S- and X-band performed RHI scans under the aircraft ground tracks. These coincident datasets provide a wealth of complementary information about the hydrometeor particle sizes, shapes, and orientations.In order to synthesize these measurements and test the robustness of scattering models, an optimal estimation retrieval based upon a Hitschfeld-Bordan profiling algorithm has been developed. This algorithm retrieves profiles of the particle size distribution parameters Nw and Dm, and, in the ice phase, relative proportions of aggregate, pristine, and rimed particles, using scattering models with different size-density and size-aspect ratio relationships. Under this formulation, only the pristine particles are horizontally aligned and capable of producing non-zero ZDR and KDP.From the nadir-looking airborne multifrequency radars, we find that aggregates may be readily distinguished from rimed and pristine particles owing to their uniqueness in triple-frequency space. However, rimed and pristine particles occupy a similar region in this space and thus polarimetric measurements greatly enhance their identification in our retrieval framework. With these capabilities we will present analyses of three-dimensional hydrometeor mapping obtained during various OLYMPEX cases. Some features retrieved in these cases include a layer of enhanced aggregation about 2km above the melting layer, hypothesized to be maintained by orographic uplift. This layer is often situated above a layer of denser, aligned particles. Regions of riming and supercooled liquid water beneath generating cells are also identified by our retrieval algorithm. Comparisons to in-situ observations and evaluation of scattering models will be presented.

Munchak, S. Joseph↗

NASA NTRSDate not supplied

TPSAS-NF1676L-17867-DND

In response to the exponential growth in science data analysis and visualization capabilities, data centers have been developing new processes to package and deliver large volumes of aggregated subsets of archived data. New standards are evolving to help data providers and application programmers manage the growing needs of the science community. These standards evolve from the best practices gleaned from new products and capabilities. The NASA Atmospheric Sciences Data Center (ASDC) has developed and deployed production provider-specific search and subset web applications for the CALIPSO, CERES, TES, and MOPITT missions. This presentation explores a CERES CCCM (CALIPSO, CloudSat, CERES, MODIS) data validation use case that leverages aggregated subset results from CERES CCCM (Level2), CERES SSF (Level2), and CALIPSO LIDAR (Level) datasets. Additionally, it examines the standards and formats that ASDC developers have applied to the delivered files as well as the implementation strategies for subsetting and processing the aggregated products.

Walter E Baskin↗

NASA NTRSDate not supplied

Publishing Variables Archived at GES DISC to Earth System Grid Federation (ESGF)

We present a straightforward and low-cost approach to publish variables archived at NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) to the Earth System Grid Federation (ESGF). An ESGF publication requires a single standard-name variable aggregated over time to facilitate data inter-comparison. It also contains significant metadata to enable searching in ESGF. We look up standard names on high demand in ESGF search history, and using OPeNDAP and NcML technologies we aggregate the corresponding variables available in the GES DISC archive with augmented metadata required by CMIP6 and obs4MIPs Data Specification version 2.1. At this writing 10 variables from a standard product of the Atmospheric Infrared Sounder along with the Tech Notes are published in ESGF by NASA Center for Climate Simulation (NCCS). Users can view, analyze, and subset remotely, and download these aggregated variables via links in any ESGF node after searching. We plan to work on and publish more variables and data from different NASA missions and experiments in our archive.

Fan Fang↗

NASA NTRSDate not supplied

Initial analysis of “stone” size Ryugu samples: current status

As a part of the initial analysis of the Ryugu samples, we perform a variety of analyses of millimeter-sized "stones". Our goals are to elucidate the entire formation process of C-type asteroid Ryugu from the viewpoint of petrology and mineralogy ande obtain necessary information by sample analysis, and then simulate the formation of Ryugu based on the evidencef obtained rom sample analysis. Eighteen stones (8 from Room A and 10 from Room C) were received from the ISAS curation facility on June 1, 2021, and brought into a fully nitrogen-displaced glove box at Tohoku University. At the same time, we also received the powder samples from Room A and Room C. To completely block the atmosphere from leaking into the container, all samples were put in the sample transport containers prepared by ISAS, transferred from the main chamber to the glovebox at ISAS, and then all containers were completely sealed in plastic bags with moisture and oxygen absorbers. No moisture or oxygen was detected when the bags were opened in the glove box at Tohoku University, so it was confirmed that there was no exposure to the atmosphere during transport. To date, a number of analyses have been carried out successfully and almost on schedule. The analysis started with the measurement of reflectance spectra, which are sensitive to atmospheric oxidation, hydroxylation, and adsorbed water. The visible, near-infrared, and mid-infrared reflectance spectra were measured while the samples were kept airtight. The spectra of powder samples and stone samples (as aggregates and as single stone) were successfully obtained. A major feature of the stone team's analysis is the use of synchrotron radiation facilities around the world. Since this analysis is non-destructive, stone samples whose reflectance spectra were measured were sent to KEK, SPring-8, ESRF (France), SOLEIL (France), DESY (Germany), and APS (USA). Using these synchrotron radiation facilities, high spatial resolution and sensitivity XRD, STXM, XANES, CT [1], IR-CT, FT-IR [2, 3], XRF, and Mössbauer analyses were performed. Most of the analyses were carried out under air-tight conditions on the stone samples and the particulates separated from the stone samples. These analyses allowed us to determine the three-dimensional distribution of minerals and elements, redox state, density and porosity of the stone samples. Furthermore, as a characteristic analysis of the stone team, light elemental analysis using negative Muon was performed at the MLF facility of J-PARC with an exceptionally long allocation of machine time. This is the only non-destructive method to measure the concentration of light elements in the whole (not the surface) of stone samples. Because the characteristic X-rays produced by muon irradiation are much higher in energy than the fluorescent X-rays produced by X-ray irradiation, there is little effect of self-absorption by the sample, and therefore, the concentration of light elements such as carbon, oxygen, and Na in the entire "stone" sample can be determined. Some stone samples are currently being measured for heat and strength physical properties in order to understand the physical properties of asteroid Ryugu. The data obtained from these measurements are useful for interpreting the remote-sensing data data taken from the surface layer of the asteroid Ryugu [4-7]. It is also important for understanding the behavior of the Ryugu material during impact events. The surfaces of many stone samples were observed by electron microscopy and other techniques, especially on natural “flat” surfaces formed on 5 stomes. As a result, characteristric mineral aggregates formed by the reactions with water and characteiristic impact features were observed on some of the samples. Based on the observations of surfaces and the synchrotron measurements of the whole stones, important objects such as characteristic structures and specific crystal aggregates for understanding the formation history of the asteroid were identified, and these parts were separated from the stone samples using an Xe beam (pFIB) and analyzed by various methods including transmission electron microscopy and synchrotron radiation analysis. Many stone samples, from which important objects have been separated, are embedded in epoxy resin and cut to produce many polished sections. Electron microscopy and spectroscopic measurements of the polished surfaces are being carried out to reveal the detailed mineralogical properties and elemental distribution inside the stone samples. In the fall, machine time for synchrotron radiation will begin, and we plan to analyze single crystals and characteristic objects separated from the stone samples.

Tomoki Nakamura↗

NASA NTRS2020

Performance Assessments of the SNPP and N20 VIIRS DNB Using Observations of Bright Stars

The Visible Infrared Imaging Radiometer Suite (VIIRS) on-board the Suomi-NPP (SNPP) and NOAA-20 (N20) spacecrafts is a multi-spectral Earth-observing instrument with spectral channels ranging from the visible to the long-wave infrared. In addition to these spectral channels, the VIIRS instrument features a panchromatic Day/Night band (DNB) with 3 gain stages (low, mid, and high) which allows for Earth-view (EV) radiance retrievals over 7 orders of magnitude. The DNB is able to collect data ranging from dim city lights during nighttime up to reflected sunlight from cloud-tops during daytime. The DNB data collection is divided into 32 aggregation modes, where sub-pixel aggregation is used to maintain a nearly constant pixel footprint on ground during EV data collection throughout each scan. The DNB is also sensitive enough to observe bright stars through the instrument space-view (SV) port. Data from these bright stars can be used to track the temporal stability of the sensor gain and as a method of intercomparison between the two VIIRS instruments. In this work, we will present several sensor performance assessments of the VIIRS DNB using stars. In addition to the sensor gain trending, these assessments will include a comparison of the differences between the daytime and nighttime data due to the effects of stray-light, a comparison of the measured signal as a function of aggregation mode, a comparison between the two high-gain sub-stages, and half-angle mirror side for both the SNPP and N20 VIIRS DNB.

VIIRS↗

NASA NTRSDate not supplied

Ryugu-Like Phyllosilicate Clast from A Giant Cluster IDP of Probable Cometary Origin: Evidence for Material Exchange Between Asteroidal and Cometary Regions

The presence of hydrous minerals in comets is currently an open question. They were commonly produced inside primitive meteorite parent bodies but apparently not inside the active comets that never contained liquid water. Despite examination of hundreds of particles returned from the Jupiter Family comet Wild 2 by the Stardust(SD) spacecraft, no phyllosilicates have yet been found. Near IR spectra obtained by the Rosetta spacecraft of short-period comet 67P Churyumov-Gerasimenko (67P CG) similarly did not reveal the presence of phyllosilicate minerals. IR spectral features in ejecta from comet Temple 1were interpreted as hydrated minerals but this match is controversial. Studies of a giant cluster interplanetary dust particle (IDP) have demonstrated that the IDP has a large number of chemical and physical properties consistent with its derivation from a comet including 1) its porous aggregate morphology similar to fragile aggregate particles imaged from comet 67P CG, 2) an unequilibrated mineral assemblage, 3) mineral isotopic compositions similar to like minerals in comet Wild 2, 4) uncorrelated Fe-Mn ratios of olivines that mimic those from Wild 2, 5) high presolar silicate abundance [8] and 6) Kool grains which are observed in comet Wild 2 but not in chondrites. Our examination of 70+>5 μm fragments from the IDP have shown that it is overwhelmingly composed of anhydrous silicates. We have observed, however, a 5 x 15 μm porous aggregate fragment (LT10), which contains a rare phyllosilicate clast encased in anhydrous mineral and rock fragments. We conducted detailed TEM and O isotopic analyses of this particle to constrain its origin.

D J Joswiak↗

NASA NTRS2023

Modeling Dust Mineralogical Composition: Sensitivity to Soil Mineralogy Atlases and Their Expected Climate Impacts

Soil dust aerosols are a key component of the climate system, as they interact with short- and long-wave radiation, alter cloud formation processes, affect atmospheric chemistry and play a role in biogeochemical cycles by providing nutrient inputs such as iron and phosphorus. The influence of dust on these processes depends on its physicochemical properties, which, far from being homogeneous, are shaped by its regionally varying mineral composition. The relative amount of minerals in dust depends on the source region and shows a large geographical variability. However, many state-of-the-art Earth system models (ESMs), upon which climate analyses and projections rely, still consider dust mineralogy to be invariant. The explicit representation of minerals in ESMs is more hindered by our limited knowledge of the global soil composition along with the resulting size-resolved airborne mineralogy than by computational constraints. In this work we introduce an explicit mineralogy representation within the state-of-the-art Multiscale Online Nonhydrostatic AtmospheRe CHemistry (MONARCH) model. We review and compare two existing soil mineralogy datasets, which remain a source of uncertainty for dust mineralogy modeling and provide an evaluation of multiannual simulations against available mineralogy observations. Soil mineralogy datasets are based on measurements performed after wet sieving, which breaks the aggregates found in the parent soil. Our model predicts the emitted particle size distribution (PSD) in terms of its constituent minerals based on brittle fragmentation theory (BFT), which reconstructs the emitted mineral aggregates destroyed by wet sieving. Our simulations broadly reproduce the most abundant mineral fractions independently of the soil composition data used. Feldspars and calcite are highly sensitive to the soil mineralogy map, mainly due to the different assumptions made in each soil dataset to extrapolate a handful of soil measurements to arid and semi-arid regions worldwide. For the least abundant or more difficult-to-determine minerals, such as iron oxides, uncertainties in soil mineralogy yield differences in annual mean aerosol mass fractions of up to ∼ 100 %. Although BFT restores coarse aggregates including phyllosilicates that usually break during soil analysis, we still identify an overestimation of coarse quartz mass fractions (above 2 µm in diameter). In a dedicated experiment, we estimate the fraction of dust with undetermined composition as given by a soil map, which makes up ∼ 10 % of the emitted dust mass at the global scale and can be regionally larger. Changes in the underlying soil mineralogy impact our estimates of climate-relevant variables, particularly affecting the regional variability of the single-scattering albedo at solar wavelengths or the total iron deposited over oceans. All in all, this assessment represents a baseline for future model experiments including new mineralogical maps constrained by high-quality spaceborne hyperspectral measurements, such as those arising from the NASA Earth Surface Mineral Dust Source Investigation (EMIT) mission.

Soil dust↗

NASA NTRSDate not supplied

Surface Exposure History of Asteroid Bennu Based on Cosmogenic Radionuclides in OSIRIS-Rex Samples

The surface of asteroid Bennu changes over time because of impacts, mass movement, and particle ejections [1-4]. The OSIRIS-REx samples were collected from a 20-m-diameter crater on Bennu called Hokioi. One of the driving hypotheses of the mission is that Hokioi is part of a population of small (<25 m) craters that are less than 0.1 Myr old and contain relatively unweathered material [1,4]. Our goal is to understand the recent surface exposure history of Bennu, utilizing radionuclides (10Be, 26Al, 36Cl, 41Ca) produced by both galactic and solar cosmic rays. We received ~12 mg of aggregate sample OREX-803014-0. We picked five of the larger particles with masses ranging from 0.24 to 0.68 mg. We dissolved each particle, along with 0.15 mg Be and 1.0 mg Cl carrier, in HF/HNO3 mixture, and did the same for the remaining aggregate sample of 9.8 mg. After dissolution, we took a small aliquot for chemical analysis, added 0.7 mg of Al carrier, and separated Be, Al, and Cl for analysis of cosmogenic 10Be, 26Al, and 36Cl by accelerator mass spectrometry [5]. Preliminary 26Al results show concentrations of 21–27 dpm/kg for the Bennu samples, with an average of 22.5 ± 0.6 dpm/kg for the five particles and 21.1 ± 0.7 dpm/kg for the remaining aggregate. These values are close to the expected 26Al saturation values of 25–30 dpm/kg for the top 1 m of Bennu’s regolith, suggesting a minimum exposure age of 1.5–2.0 Myr near the surface. Our initial Bennu results also resemble those found for Ryugu samples [6,7]; thus, we can hypothesize that the two asteroids have had similar surface exposure histories.

K C Welten↗

NASA NTRSDate not supplied

Identifying Trends in Landing Profiles After Long Duration Spaceflight

BACKGROUND As NASA’s mission programs begin to shift from Low Earth Orbit (LEO) to planetary mission profiles, the importance of understanding the phenomena a human experience when returning from spaceflight is of increased importance. The purpose of this study was to assess trends across individuals in the symptoms experienced during the landing process of long duration ISS missions. METHODS Data for this study is an aggregation of mission level data from forms used by crew surgeons at R+0, electronic medical records, notes from weekly Space Medicine Operation Team meetings, records in the Shuttle Mission Data Archive, and data collected by research teams in the Human Research Program (HRP). Aggregated data was used in descriptive analysis of the trends in medical events and countermeasure use. The data was also used to identify high value targets for emphasis in on going surveillance efforts. RESULTS Completeness of reporting varied greatly over time and across missions dependent on information sources available for data extraction. Landing forms provided the most complete data but still missed or left unconfirmed, several, common symptoms, and countermeasures. Data aggregation did show to cover gaps within individual data sources. Commonly reported symptoms included nystagmus, vertigo, and nausea. Common protocols for fluid loading and meclizine are reflected within the data set. DISCUSSION The data set generated in this project provides a foundation that show how symptoms of astronauts as they return to Earth varies across the long duration ISS missions. While there is an abundance of information provided within the data set, there are still inconsistencies in reporting especially in the absence of the landing day form. Further data collection practices should be standardized to ease the burden on crew surgeons during R+0 exams and better collect high value variables.

Sam Jacobs↗

DOE OSTI2021

Simulation of PV Variability as a Function of PV Generation and Plant Size: Preprint

The deployment of photovoltaic (PV) systems continues to show significant expansion; however, this growth has brought added attention to issues around the variability of the solar resource. Both spatial and temporal variability exist. Temporal scales can range from the sub-second to multiyear, whereas spatial scales can range from a few meters to tens of kilometers. There are multiple methods described in the literature to quantify PV variability at various spatial and temporal scales. This study focuses on short-term temporal variability and uses similar approaches with the addition of PV plant size a parameter to quantify variability. The method employed here incorporates the normalization of clear- and cloudy-sky conditions and PV plant size to quantify nominal variability metrics. The distribution and fluctuations of these metrics provide relevant information that is useful for system operations. The National Solar Radiation Database (NSRDB) is used to simulate PV variability as a function of PV generation and plant size. Hypothetical but realistic system information at 33 locations is used to model PV generation by feeding NSRDB solar irradiance data to the National Renewable Energy Laboratory’s System Advisor Model (SAM). Over the selected region, it is found that the aggregated ramp rates for the 1-minute data are associated with standard deviations ranging from 0.002–0.055 on a daily basis; however, hourly intervals induce higher aggregated ramp rates than the other timescales. Even though minute-to-minute variations are significant for the 1-minute timescale, the standard deviation aggregated into a daily metric is smaller because of the cancellation of values.

41 EE - Solar Energy Technologies Office (EE-4S)↗

DOE OSTI2022

Consensus-Based Approach for Active Power Control and Reserve Estimation in Distributed PV Systems: Preprint

With the increased adoption of distributed energy resources (DER), they are expected to contribute to power system reliability services and enhance power system stability. This paper presents a distributed consensus control approach for the real-time active power reserve estimation and power management in distributed PV (photovoltaic) systems. The proposed method estimates the cumulative active power reserve from numerous PV generators using only the sparse communication network for a DER aggregator to provide active power regulation services. The real-time active power reserve estimation using the proposed approach can be used by DER aggregators to manage curtailment in distributed PV systems to maintain stipulated reserves and further to provide power system frequency regulation. Using the proposed approach, the DER aggregator only requires measurements at the feeder substation and it does not require information from individual DER units, thereby improving system resiliency. The proposed distributed consensus control method is validated on IEEE 123 testbed using PSCAD simulations.

active power reserve↗

DOE OSTI2021

Hierarchal framework for integrating distributed energy resources into distribution systems

Methods and apparatus are disclosed for providing a hierarchical framework for integrating distributed energy resources into power distribution systems. In one example of the disclosed technology, a method implemented with an aggregation server includes receiving a respective utility function associated with each of at least two of a plurality of distributed energy resources representing an amount of energy produced or consumed by the respective associated distributed energy resource as a function of energy price, producing an aggregated utility function associated with the plurality of distributed energy resources based on the received utility functions, transmitting the produced aggregated utility function to a coordinator, receiving a clearing value from the coordinator, and transmitting the received clearing value to each of the plurality of distributed energy resources.

Lian, Jianming↗

DOE OSTI2022

Multi-Kernel Adaptive Support Vector Machine for Scalable Predictive Maintenance

Application of data-driven solutions across an industry is challenging, since the data are often stored locally, and increasing privacy and security concerns restrict access to the data. In addition, it is highly unlikely that all potential data patterns are captured in a single data source. Because it is highly unlikely that all potential data patterns are captured in a single data source, machine learning (ML) models developed from a single source cannot be robust enough. An alternative is to train the ML model at each source and develop a distributed knowledge discovery and aggregation approach to build global knowledge. In this paper, we develop and demonstrate a distributed ML model, federated transfer learning (FTL), using a multi-kernel-based adaptive support vector machine (MK-A-SVM). For federated learning (FL), the multi-kernel (MK) approach enables feature-specific model aggregation under data heterogeneity; whereas for transfer learning (TL) the adaptive model enables utilization of an aggregated model from a different task. The proposed approach is validated using nuclear power plant (NPP) vertical motor-driven pump data to predict the health condition of vertical motor-driven pumps as an anomaly detection. The efficiency of the proposed approach is also quantified and compared with neural network.

42 ENGINEERING↗

DOE OSTI2023

Power system restoration incorporating diverse distributed energy resources

An example system includes an aggregator configured to receive a service collaboration request and iteratively determine, based on minimum and maximum power values for DERs under its management, an optimized operation schedule. The aggregator may also be configured to iteratively determine, based on the optimized operation schedule, an estimated flexibility range for devices under its management and output an indication thereof. The system may also include a power management unit (PMU) configured to iteratively receive the indication and determine, based on a network model that includes the estimated flexibility range, a reconfiguration plan and an overall optimized operation schedule for the network. The PMU may also be configured to iteratively cause reconfiguration of the network based on the plan. The PMU and aggregator may also be configured to iteratively, at a fast timescale, cause energy resources under their management to modify operation based on the overall optimized operation schedule.

Ding, Fei↗

DOE OSTI2020

Wash Penalty Factors: Insight into the Effects of Water Wash Down of Building Materials for Radionuclide/Nuclear (Rn) Decontamination - 20153

The release of radiological material to the urban environment can have a devastating socio-economic impact. In an urban release scenario, areas around the dispersal epicenter and any areas contaminated via atmospheric deposition may require extensive decontamination. Most recently, our group reported the decontamination efficacy of pressurized water washing of common porous building materials, and compared the penetration depth of the contaminations before and after exposure to pressurized tap water. Here, we continue evaluation of the decontamination efficacy of wash solutions based on potassium (K{sup +}) salt for cesium (Cs), strontium (Sr), and europium (Eu) contaminations on common building surfaces. The surfaces included: the cement used in concrete, the aggregate used in concrete, intact concrete, roadway asphalt, asphalt shingles, and latex paint. We deposited solutions of {sup 137}Cs, {sup 85}Sr, and {sup 152}Eu onto numerous common building materials and exposed these materials to a static bath or low-pressure flow of tap water, 0.1 M potassium chloride (KCl), and 0.5 M KCl. The decontamination efficacy and the depth profile for residual contamination were measured to determine the conditions under which applying a wash solution has benefit compared to physically removing the surface material. To aid in these analyses, we introduced a 'wash penalty factor' to quantify the degree to which contamination migrated into the bulk material by the action of the wash method. On asphalt, 70-80% of the radionuclides were found to be within 0.02 mm of the surface. Cs{sup +} bonded to negative charge sites on the surface of the mineral aggregate (used in concrete) so decontamination was improved by ion exchange with K{sup +}. Sr{sup 2+} is soluble and removed by water, while not bonding to aggregate or demonstrating solubility in the liquid asphalt. Eu{sup 3+} is precipitated and not removed in gentle wash but displays mobility within the pore space that suggests its presence as a colloid. Concrete is more porous than asphalt, and 80% of the radionuclides were within 0.2 mm of the surface for {sup 137}Cs and {sup 152}Eu and 50- 80% for {sup 85}Sr. On concrete, Cs{sup +} bonds similarly to asphalt. Sr{sup 2+} bonds to the cement or precipitates from the alkaline pore water. Eu{sup 3+} sorbs to the cement and then precipitates. In brick, the results for Cs{sup +} and Sr{sup 2+} suggested that diffusion of ions from deeper in the coupon was important. Eu{sup 3+} is removed poorly due to precipitation. We will explain and report example wash penalty factors that vary from 0 to > 1 for the various methods and the implications for deciding when to implement wash down methods. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Autonomous Intelligent Charging/Discharging of Electric Vehicles using Distributed Multi-Agent ADMM Framework for Grid Ancillary Services

The increasing popularity of Electric Vehicles (EVs) in the distribution grid along with technological advancement in EV electronics such as vehicle to grid (V2G) technique has enabled them to participate in grid ancillary services. To achieve this, the EVs need to establish a contract with third-party aggregators and connect to a charging unit, either residential or commercial. At any time they are connected, the EVs can decide to take part in the ancillary services program offered to them by the aggregators. If agreed, the aggregators will use the EVs as a power source capable of charging/discharging power according to the input signal, and in return, they will be compensated. This inter-temporal nature of charging/discharging is also transforming the traditional optimal power flow (OPF) problem into a dynamic OPF problem. This chapter aims at developing a multi-layer time-dependent optimization algorithm to utilize EV potential and provide ancillary services while maximizing its utilization function. Specifically, in the upper layer, an autonomous distributed ADMM algorithm is developed to optimize the cost for charging/discharging EVs while using them to regulate the voltage at each bus in the distribution grid. The distributed ADMM algorithm is also expanded to the lower layer where the individual EVs active and reactive power is controlled for voltage regulation while maintaining the desired state of the charge of the vehicle at the end of the charging period. Here, the effectiveness and performance improvement of the proposed multi-layer algorithm is illustrated through analytical analysis and simulation results.

Rahman, Towfiq↗

DOE OSTI2020

Autonomous Intelligent Charging/Discharging of Electric Vehicles using Distributed Multi-Agent ADMM Framework for Grid Ancillary Services

The increasing popularity of Electric Vehicles (EVs) in the distribution grid along with technological advancement in EV electronics such as vehicle to grid (V2G) technique has enabled them to participate in grid ancillary services. To achieve this, the EVs need to establish a contract with third-party aggregators and connect to a charging unit, either residential or commercial. At any time they are connected, the EVs can decide to take part in the ancillary services program offered to them by the aggregators. If agreed, the aggregators will use the EVs as a power source capable of charging/discharging power according to the input signal, and in return, they will be compensated. This inter-temporal nature of charging/discharging is also transforming the traditional optimal power flow (OPF) problem into a dynamic OPF problem. This chapter aims at developing a multi-layer time-dependent optimization algorithm to utilize EV potential and provide ancillary services while maximizing its utilization function. Specifically, in the upper layer, an autonomous distributed ADMM algorithm is developed to optimize the cost for charging/discharging EVs while using them to regulate the voltage at each bus in the distribution grid. The distributed ADMM algorithm is also expanded to the lower layer where the individual EVs active and reactive power is controlled for voltage regulation while maintaining the desired state of the charge of the vehicle at the end of the charging period. The effectiveness and performance improvement of the proposed multi-layer algorithm is illustrated through analytical analysis and simulation results.

Rahman, Towfiq↗