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DOE OSTI2021

Machine Learning for Improved Availability of the SNS Klystron High Voltage Converter Modulators

Beam availability has increased at the SNS, however, the targeted availability is greater than 95 %, while the SNS has failed to meet lower targets in the past. The HVCM used to power the linac klystrons have been one source of lost beam time and was chosen to explore using AI/ML techniques to improve reliability. Among the possibilities being explored are automating the tuning of HVCMs and predicting component failures such as capacitor aging, rectifier assemblies containing hundreds of diodes, and insulating oil degradation. The methodology pursued includes data cleaning, de-noising, post-analysis data labeling, and machine learning model development. We explore using Long Short-Term Memory and autoencoders for anomaly detection and prognostication used to schedule maintenance. We evaluate the use of model regularizers and constraints to improve the performance of the model and investigate methods to estimate the uncertainty of the models to provide a robust prediction with statistical interoperability. This paper describes the operational experience and known failures of the HVCMs and the proposed ML methodology and the preliminary results of training the AI/ML algorithms.

Pappas, Chris↗

DOE OSTI2022

BayoTech Risk and Modeling Support of NM Gas Site

The BayoTech hydrogen generation system has been evaluated in terms of safety considerations at the NM Gas site. The consequence of a leak in different components in the system was evaluated in terms of plume dispersion and overpressure. Additionally, the likelihood of a leak scenario for different hydrogen components was identified. The worst-case plume dispersion cases, full-bore leaks, resulted in relatively large plumes. However, these cases were noted to be far less likely than the partial break cases that were evaluated. The partial break cases resulted in nearly negligible plume lengths. Similarly, the overpressure analysis of the full-bore break scenarios resulted in much larger overpressures than the partial break cases (which resulted in negligible overpressure at the lot line). There were several cases evaluated in the analysis that represented leak scenarios from both hydrogen and natural gas sources. Generally, the natural gas leak scenarios resulted in a smaller horizontal impact than that of hydrogen leaks. The worst-case consequence from a hydrogen leak resulted from the compressors, storage pods, or dispensing system. To consider the safety features that may isolate the leak, the consequence was evaluated at different times after the leak event to show the reduction of pressure. After 2 seconds, the plume dispersion from this event is contained within the perimeter of the site. The worst-case consequences show that the plume may disperse to adjacent facilities and to the street. When considering both likelihood and consequence, the risk may be considered low because the maximum frequency of a full-bore leak from any component within the hydrogen compound is 8.2 E-5/yr. This means that a full-bore leak is expected to occur less than once every 10,000 years. The risk can be further reduced by implementing mitigative countermeasures, such as CMU walls along the sides of the equipment compound. This would reduce the overall consequence of the worst-case dispersion scenarios (horizontal impact of plume). In terms of siting and safety analysis, the NFPA 2 code was used to provide a high-level evaluation of the current site plan. The most limiting equipment in terms of set-back distance are the compressors/storage units because of the high-pressure hydrogen. The site layout was evaluated for an acceptable location for the compression/storage unit based on NFPA 2 set-back distances. It is important to note that the NFPA 2 set-back distances consider both likelihood and consequence. This is important because the worst-case results evaluated herein also represent the least likely leak scenario. Other site-specific considerations were evaluated, including the parking shade structure with photovoltaic cells and refueling vehicles. These issues were dispositioned and determined to not present a safety risk.

08 HYDROGEN↗

DOE OSTI2020

Effects of Low-Carbon Energy Adoption on Airborne Particulate Matter Concentrations With Feedbacks to Future Climate Over California

California plans to reduce emissions of long-lived greenhouse gases (GHGs) through adoption of new energy systems that will also lower concentrations of short-lived absorbing soot contained in airborne particulate matter (PM). Here we examine the direct and indirect effects of reduced PM concentrations under a low-carbon energy (GHG-Step) scenario on radiative forcing in California. Simulations were carried out using the source-oriented WRF/Chem (SOWC) model with 12 km spatial resolution for the year 2054. Furthermore, the avoided aerosol emissions due to technology advances in the GHG-Step scenario reduce ground level PM concentrations by ~8.85% over land compared to the Business-as-Usual (BAU) scenario, but changes to meteorological parameters are more modest. Top-of-atmospheric forcing predicted by the SOWC model increased by 0.15 W m -2 , surface temperature warmed by 0.001 K, and planetary boundary layer height (PBLH) increased by 2.20 cm in the GHG-Step scenario compared to the BAU scenario. PM climate feedbacks are small because the significant changes in ground level PM concentrations associated with the GHG-Step scenario are limited to the first few hundred meters of the atmosphere, with little change for the majority of the vertical column above that level. As an order-of-magnitude comparison, the long-term effects of global reductions in GHG emissions (RCP8.5–RCP4.5) lowered average surface temperature over the California study domain by approximately 0.76 K. The effects of long-lived climate pollutants such as CO 2 are much stronger than the effects of short-lived climate pollutants such as PM soot over California in the year 2054.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Investigation of potential aerosol transmission and infectivity of SARS-CoV-2 through central ventilation systems

Here we evaluate the concentrations and probabilities of infection for both building interior and exterior exposure sources using a well-mixed model in a connected multizone building. As a central hub of many community and economic activities, buildings provide social connectivity, but the COVID-19 pandemic has reduced social connectivity due to concerns of viral spread within buildings. Although single zone models of infectious spread are well studied, the impact of aerosolized spread of SARS-CoV-2 via air handling systems in multizone buildings remains unexplored. Here we evaluate the influence of filtration, air exchange rates, and the fraction of outdoor air on the probability of infection using the well-known well-mixed modeling approach for a multizone. We find filtration lowers the concentration and probability of infection in both source and connected rooms provided at least some air is recirculated, but that probability is not zero. Filtration has no influence without recirculation or unless the outdoor air contains virus. We find that increasing the air exchange rate removes virus from the source room faster but also increases the rate of exposure to connected rooms. Therefore, slower air exchange rates reduce infectivity in connected rooms at shorter durations, but higher air exchange rates reduce infectivity at longer durations. We further find that when outdoor air is virus free, increasing the fraction of outdoor air is helpful, but, when outdoor air is infective, pathogen exposure inside can persist for hours after a short-term release.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Spray and combustion characteristics of pure hydrothermal liquefaction biofuel and mixture blends with diesel

Hydrothermal liquefaction (HTL) is the process in which biological compounds can be converted into biocrude diesel; various feedstocks, such as algae and wet biowaste, can be utilized. Almost 20 million dry tons of wet biowaste is deposited in U.S. municipal wastewaters annually. If recovered and converted into biodiesel, it can act as a massive source of renewable energy. Preliminary experiments on a diesel engine show that HTL fuel can achieve similar performance and emission levels to diesel. In order to further understand the influence of the HTL fuel properties, the HTL fuel and blends with diesel are observed in a constant volume chamber. Previously, 10% and 20% of the HTL fuel were blended with diesel by volume and demonstrated properties that roughly matched diesel in terms of combustion. In this study, 50% and 100% HTL fuel blends are tested on the same apparatus. It was discovered that the workability of HTL is almost the same as that of diesel and is less sensitive to ambient temperatures. When the ambient temperature is reduced from 1200 K to 800 K, the change ratio of ignition delay is only 62% of diesel. By analyzing the combustion process, it can be seen that there is no need to make major modifications to the engine control strategy if HTL fuel is applied to diesel engines. Though, under low temperature and low oxygen conditions, the soot luminosity peak of HTL100 is 3.12 times than that of diesel.

09 BIOMASS FUELS↗

DOE OSTI2025

Multiphase Processing of the Water-Soluble and Insoluble Phases of Biomass Burning Organic Aerosol

Biomass burning is one of the most significant sources of organic aerosol in the atmosphere. Biomass burning organic aerosol (BBOA) has been observed to undergo liquid– liquid phase separation (LLPS) to give core–shell morphology with the hydrophobic phase encapsulating the hydrophilic phase, potentially impacting the evolution of light-absorbing components, i.e., brown carbon (BrC), through multiphase processes. Here, we demonstrate how multiphase processing differs between the watersoluble (i.e., hydrophilic) and insoluble (i.e., hydrophobic) phases of BBOA in terms of reactive uptake of ozone in a coated-wall flow tube. Effects of relative humidity (RH) and ultraviolet (UV) irradiation were investigated. Experimental timeseries were used to inform simulations using multilayer kinetic modeling. Among non-irradiated thin films, the uptake coefficient was greatest for the water-soluble phase at 75% RH (3 × 10 –5 , corresponding to a diffusion coefficient of BrC, D BrC , of 3 × 10 –9 cm 2 s –1 ) and least for the same phase at 0% RH (1 × 10 –5 , corresponding to D BrC of 1 × 10 –10 cm 2 s –1 ). The uptake coefficient for the water-insoluble phase fell between these two (about 1.5 × 10 –5 ), regardless of RH, and the corresponding D BrC increased only slightly (8 × 10 –10 cm 2 s –1 at 0% RH to 9 × 10 –10 cm 2 s –1 at 75% RH). The uptake coefficients of both phases at 0% RH decreased significantly after UV irradiation, consistent with a transition from viscous liquid to solid and supported by qualitative microscopy observations. Modeling multiphase ozone oxidation of primary BrC components in the atmosphere demonstrated, first, that LLPS may extend the lifetime of water-soluble BBOA encapsulated by water-insoluble species by a factor of 1.5 at moderate to high RH and, also, that UV irradiation may extend the lifetime of both phases by more than a factor of 2.5.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Open-source simulation platform for air source heat pump integrated with thermal energy storage

Here, this article introduces a modular simulation platform for assessing thermal energy storage (TES) integrated with air source heat pumps (ASHP). The Python platform is an open-source library that includes classes for modeling air-air and air-water heat pumps, TES devices, and the heating load of residential buildings. To validate the ASHP model, the study utilized experimental data obtained from a commercial heat pump evaluated at the National Renewable Energy Laboratory (NREL). The results indicate a mean deviation of 0.7% for COP across the operating range, with a maximum relative deviation of 12.6%. In terms of system heating capacity, the model had an average deviation of 4.3% compared to experimental results, with a maximum deviation of 8.2%. Three classes were implemented for modeling distinct types of TES devices: a generic TES based on energy balances, a sensible isothermal water tank, and a stratified water tank. Details of the mathematical models are provided, along with their respective strengths and limitations. An example is provided showcasing the integration of a residential 10 kWh thermal storage unit with an ASHP operating in Denver, CO. The comparison of two different discharge criteria for the TES unit highlights the importance of control strategies in the system performance.

25 ENERGY STORAGE↗

DOE OSTI2020

Comparative scintillation performance of EJ-309, EJ-276, and a novel organic glass

An organic glass scintillator developed by Sandia National Laboratories was characterized in terms of its light output and pulse shape discrimination (PSD) properties and compared to commercial liquid (EJ-309) and plastic (EJ-276) organic scintillators. The electron light output was determined through relative comparison of the 137 Cs Compton edge location. The proton light yield was measured using a double time-of-flight technique at the 88-Inch Cyclotron at Lawrence Berkeley National Laboratory. Using a tunable broad-spectrum neutron source and an array of pulse-shape-discriminating observation scintillators, a continuous measurement of the proton light yield was performed for EJ-309 (200 keV–3.2 MeV), EJ-276 (170 keV–4.9 MeV), and the organic glass (50 keV–20 MeV) . Finally, the PSD properties of the organic glass, EJ-309, and EJ-276 were evaluated using an AmBe source and compared via a figure-of-merit metric. The organic glass exhibited a higher electron light output than both EJ-309 and EJ-276. Its proton light yield and PSD performance were comparable to EJ-309 and superior to that of EJ-276. Finally, with these performance characteristics, the organic glass scintillator is well poised to replace current state-of-the-art PSD-capable scintillators in a range of fast neutron detection applications.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

The Energetics of the Central Engine in the Powerful Quasar 3C 298

The compact steep-spectrum radio source 3C 298 (redshift of 1.44) has the largest 178 MHz luminosity in the Third Cambridge Revised Catalogue (3CR); its radio lobes are among the most luminous in the universe. The plasma state of the radio lobes is modeled with the aid of interferometric radio observations (in particular, the new Low Frequency Array observation and archival MERLIN data) and archival single-station data. It is estimated that the long-term time-averaged jet power required to fill these lobes with leptonic plasma is $\overline{Q}\,\approx 1.28\pm 0.51\times {10}^{47}\,\mathrm{erg}\,{{\rm{s}}}^{-1}$, rivaling the largest time-averaged jet powers from any quasar. Supporting this notion of extraordinary jet power is a 0.5–10 keV luminosity of ≈ 5.2 × 10 46 erg s –1 , comparable to luminous blazars, yet there is no other indication of strong relativistic beaming. We combine two new high signal-to-noise ratio optical spectroscopic observations from the Hobby-Eberly Telescope with archival Hubble Space Telescope, Two Micron All Sky Survey, and Galaxy Evolutionary Explorer data to compute a bolometric luminosity from the accretion flow of L bol ≈ 1.55 ± 0.15 × 10 47 erg s –1 . The ratio, $\overline{Q}/{L}_{\mathrm{bol}}\approx 1$, is the approximate upper limit for quasars. Characteristic of a large $\overline{Q}/{L}_{\mathrm{bol}}$, we find an extreme-ultraviolet (EUV) spectrum that is very steep (the "EUV deficit" of powerful radio quasars relative to radio-quiet quasars), and this weak ionizing continuum is likely a contributing factor to the relatively small equivalent widths of the broad emission lines in this quasar.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Power at Sea: Use of Wave Energy Converters for Powering Offshore Oil and Gas Operations

New innovative services and goods based on artificial intelligence, next-generation robotics, autonomy, digitization, and electrification are taking root in the ocean economy. More typical competitive forces, such as value enhancement and safety improvement, are also present, as suppliers constantly strive to improve their competitive positioning. Concurrently, the Oil and Gas sector is experiencing mounting pressure to decrease its operational carbon emissions, forcing efforts to reduce or eliminate liquid fuel consumption offshore. Companies in the ocean economy are having to react to this combination of macro- and micro-level drivers and innovate at an ever more rapid pace. However, before many of these new capabilities can be implemented, new, clean, reliable power sources are needed, especially as liquid fuel grows increasingly out of favor. For many of these loads—both old and new and ranging from watts to megawatts—wave energy systems provide the best solution for remote power generation. As such, research, development and demonstration activities are underway to prove wave energy's ability to provide reliable, consistent energy supplies for certain offshore Oil and Gas activities, paving the way for near term commercialization. Furthermore, this paper outlines these drivers, competitive reaction to them, and why and how wave energy can be a preferable choice for power at sea.

16 TIDAL AND WAVE POWER↗

DOE OSTI2019

Data from: Associative nitrogen fixation (ANF) in switchgrass (Panicum virgatum) across a nitrogen input gradient

Associative N fixation (ANF), the process by which dinitrogen gas is converted to ammonia by bacteria in casual association with plants, has not been well-studied in temperate ecosystems. We examined the ANF potential of switchgrass (Panicum virgatum L.), a North American prairie grass whose productivity is often unresponsive to N fertilizer addition, via separate short-term 15N2 incubations of rhizosphere soils and excised roots four times during the growing season. Measurements occurred along N fertilization gradients at two sites with contrasting soil fertility (Wisconsin, USA Mollisols and Michigan, USA Alfisols). In general, we found that ANF potentials declined with long-term N addition, corresponding with increased soil N availability. Although we hypothesized that ANF potential would track plant N demand through the growing season, the highest root fixation rates occurred after plants senesced, suggesting that root diazotrophs exploit carbon (C) released during senescence, as C is translocated from aboveground tissues to roots for wintertime storage. Measured ANF potentials, coupled with mass balance calculations, suggest that ANF appears to be an important source of N to unfertilized switchgrass, and, by extension, to temperate grasslands in general.

09 BIOMASS FUELS↗

DOE OSTI2024

Measurement report: A comparison of ground-level ice-nucleating-particle abundance and aerosol properties during autumn at contrasting marine and terrestrial locations

Abstract. Ice-nucleating particles (INPs) are an essential class of aerosols found worldwide that have far-reaching but poorly quantified climate feedback mechanisms through interaction with clouds and impacts on precipitation. These particles can have highly variable physicochemical properties in the atmosphere, and it is crucial to continuously monitor their long-term concentration relative to total ambient aerosol populations at a wide variety of sites to comprehensively understand aerosol–cloud interactions in the atmosphere. Hence, our study applied an in situ forced expansion cooling device to measure ambient INP concentrations and test its automated continuous measurements at atmospheric observatories, where complementary aerosol instruments are heavily equipped. Using collocated aerosol size, number, and composition measurements from these sites, we analyzed the correlation between sources and abundance of INPs in different environments. Toward this aim, we have measured ground-level INP concentrations at two contrasting sites, one in the Southern Great Plains (SGP) region of the United States with a substantial terrestrially influenced aerosol population and one in the Eastern North Atlantic Ocean (ENA) region with a primarily marine-influenced aerosol population. These measurements examined INPs mainly formed through immersion freezing and were performed at a ≤ 12 min resolution and with a wide range of heterogeneous freezing temperatures (Ts above −31 °C) for at least 45 d at each site. The associated INP data analysis was conducted in a consistent manner. We also explored the additional offline characterization of ambient aerosol particle samples from both locations in comparison to in situ data. From our ENA data, on average, INP abundance ranges from ≈ 1 to ≈ 20 L−1 (−30 °C ≤ T ≤ −20 °C) during October–November 2020. Backward air mass trajectories reveal a strong marine influence at ENA with 75.7 % of air masses originating over the Atlantic Ocean and 96.6 % of air masses traveling over open water, but analysis of particle chemistry suggests an additional INP source besides maritime aerosols (e.g., sea spray aerosols) at ENA. In contrast, 90.8 % of air masses at the SGP location originated from the North American continent, and 96.1 % of the time, these air masses traveled over land. As a result, organic-rich SGP aerosols from terrestrial sources exhibited notably high INP abundance from ≈ 1 to ≈ 100 L−1 (−30 °C ≤ T ≤ −15 °C) during October–November 2019. The probability density function of aerosol surface area-scaled immersion freezing efficiency (ice nucleation active surface site density; ns) was assessed for selected freezing temperatures. While the INP concentrations measured at SGP are higher than those of ENA, the ns(T) values of SGP (≈ 105 to ≈ 107 m−2 for −30 °C ≤ T ≤ −15 °C) are reciprocally lower than ENA for approximately 2 orders of magnitude (≈ 107 to ≈ 109 m−2 for −30 °C ≤ T ≤ −15 °C). The observed difference in ns(T) mainly stems from varied available aerosol surface areas, Saer, from two sites (Saer,SGP > Saer,ENA). INP parameterizations were developed as a function of examined freezing temperatures from SGP and ENA for our study periods.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Measurement and calibration of non-linear shear terms in galaxy cluster fields

Introduction Galaxy cluster lensing is a powerful tool for measuring the mass of galaxy clusters, but accurate shear measurement and calibration are critical to obtaining reliable results. This study focuses on the measurement and calibration of weak lensing shears to improve mass estimates in cluster lensing. To deal with the problem, we first developed an image simulation pipeline, jedisim, which utilizes galaxy images extracted from the Hubble Space Telescope (HST) Ultra Deep Field (UDF) and the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS). Methods The simulations represent realistic galaxy distributions and morphologies as input sources. The foreground halo with a Navarro–Frenk–White (NFW) profile is constructed such that the lensing signals of background galaxies can be measured by the Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST) Science Pipelines. By comparing the measured reduced shear g meas and the true reduced shear g true , we observe non-linearity up to g ≲ 0.6 . We fit polynomials to the data with quadratic correction adequate to g ≲ 0.4 . Meanwhile, we conduct mass estimates using the pzmassfitter code on four different clusters. Results The mass estimate results are significantly improved after applying the shear calibration derived from the present work—from 4.954 ± 0.504 × 1 0 14 M ⊙ to 10.507 ± 0.498 × 1 0 14 M ⊙ after calibration for a simulated cluster with the mass of 10 × 1 0 14 M ⊙ . In multiple cases of validation, the estimated results are all consistent with true cluster mass. Discussion This study yields the first relationship between reality and shape measurement of the LSST Science Pipelines and serves as the first step toward the overall goal of mass calibration in cluster lensing. By addressing the challenges in shear measurement and calibration, we aim to enhance the accuracy and reliability of mass estimates in galaxy cluster lensing studies.

Astronomy & Astrophysics↗

DOE OSTI2020

Lignin-derived electrochemical energy materials and systems

Electrochemical energy storage systems such as supercapacitors, rechargeable batteries and fuel cells have been proven the most effective technologies for energy conversion, storage, and management at different scales. Although a large number of electrochemical energy technologies have been developed in the past and they will continue to be optimized in terms of cost, lifetime, and performance, there is a substantial growing demand for advanced electrochemical energy systems. To deploy these advanced systems, the electrode and electrolyte materials with higher performance, longer life, and lower cost, must be developed. Lignin is the second most abundant natural polymer after cellulose, a byproduct from emerging cellulosic biorefineries, and a waste product from pulp and paper industries. Numerous researches have successfully demonstrated that lignin from different sources can be used as precursors or feedstocks for preparing high-performance electrochemical energy materials and components such as electrodes, electrolytes, membrane separators, and additives. Moreover, techno-economic analyses indicate that it is possible to prepare cost-effective carbons from lignin at engineering scales, compared to current carbon products. These facts suggest that scalable conversion of lignin into high-value energy materials will offer a promising pathway to not only promote the utilization and valorization of lignin but also boost the development of the advanced electrochemical energy systems. This review presents state of the arts of renewable energy materials derived from various lignin and their applications in electrochemical energy systems with emphasis on supercapacitors, rechargeable batteries, and fuel cells. Meanwhile, this article also aims to carve out the critical barriers for lignin-derived high-performance materials for energy applications, intending to identify viable approaches for synthesis of sustainable new energy materials.

09 BIOMASS FUELS↗

DOE OSTI2020

A long-term pilot-scale algal cultivation on power plant flue gas – Cultivation stability and biomass accumulation

A long-term culture of a selected freshwater microalgal assemblage on power plant flue gas was realized using a pilot-scale photobioreactor. Different culture conditions of light cycle, harvesting amount, pH stabilization, and sulfur addition were tested during a 12-month continuous operation at a natural gas fired power plant. The results concluded that the daily harvesting amount of 60% with no light-cycle and NH 4 NO 3 as the nitrogen source and pH stabilization agent, resulted in optimal cultivation performance. Biomass concentration and biomass productivity reached 1.07 ± 0.23 g L -1 and 0.43 ± 0.14 g L -1 d -1 , respectively. During the year-long cultivation period, the algal assemblage was relatively stable with average abundances of 88 ± 4% and 12 ± 4% for algae and bacteria, respectively, and no significant differences between individual case scenarios. The stable culture fostered a stable biomass composition. Protein, carbohydrate, and lipid contents of the algal biomass were 58.60 ± 2.41%, 19.5 ± 2.44%, and 9.70 ± 1.68%, respectively.

09 BIOMASS FUELS↗

DOE OSTI2025

Comprehensive assessment of deep reinforcement learning approaches for economic dispatch in nuclear-driven microgrids

As the electrical grid integrates more variable renewable energy sources such as wind and solar, the demand for distributed and flexible systems to address this increased variability becomes critical. Nuclear-driven microgrids provide a promising solution by offering stable generation to complement intermittent renewables, ensuring grid reliability and operating efficiency. This paper proposes a recurrent deep reinforcement learning framework for optimal economic dispatch in a nuclear-powered microgrid integrating renewable energy sources, small modular reactors, battery storage systems, and balance-of-plant dynamics. A three-agent control architecture is developed, where demand and renewable energy agents act as forecasters, and a reinforcement learning-based dispatch agent performs real-time energy allocation. A nonlinear programming formulation is first used to generate an optimal baseline for benchmarking. The proposed dispatch controller, based on Proximal Policy Optimization enhanced with Long Short-Term Memory networks, exploits temporal correlations in system dynamics by taking advantage of the time series used as inputs to improve policy robustness under uncertainty. Comparative analysis against established deep reinforcement learning methods, including Proximal Policy Optimization with a feedforward architecture, Soft Actor-Critic, and Twin Delayed Deep Deterministic Policy Gradient, demonstrates superior performance. Numerical results indicate that the proposed controller achieves a 0.39% cost reduction relative to the nonlinear programming benchmark and outperforms other learning-based methods by generating additional revenue of up to 0.35%. All reinforcement learning controllers compute dispatch actions in less than 0.3 s, resulting in a computational speedup of more than three orders of magnitude over the nonlinear programming baseline. The findings of this paper highlight their applicability for real-time operation and control in nuclear-integrated microgrids under volatile operating conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Controls on the 36 Cl/Cl input ratio of paleo-groundwater in arid environments: New evidence from 81 Kr/Kr data

In this study, measurements of the long-lived 81 Kr and 36 Cl radioisotopes in groundwater from the Negev Desert (Israel) were used to assess the 36 Cl/Cl input ratios and Cl – contents for paleorecharge into the Nubian Sandstone Aquifer (NSA). The reconstructed Cl – content of the recharge flux was on the order of 300–400 mg/L. An initial 36 Cl/Cl ratio of 50 × 10 –15 was assessed for the groundwater replenishment in the Negev Desert since the late Pleistocene, in agreement with the 36 Cl/Cl ratios in recent local rainwater. This is despite possible changes in the climatic conditions and the 36 Cl production rates in the atmosphere over this timeframe. This similarity in values is explained by the major role played by the erosion and weathering of near-surface materials in the desert environment that dominate the hydrochemistry of rains, floods, and the consequent groundwater recharge. Spatial variation in the reconstructed initial 36 Cl/Cl ratio is accounted for by the differences in the mineral aerosol sources for specific recharge areas of the NSA. Accordingly, regional variations in the 36 Cl/Cl input in groundwater reservoirs surrounding the Mediterranean Sea indicate various processes that govern the 36 Cl/Cl system. Finally, the results of this study highlight the great advantage of integrating 81 Kr age information in evaluating the initial 36 Cl/Cl and Cl – input, which is essential for the calibration of 36 Cl radioisotope as an available long-term dating tool for a given basin.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Immunophenotypic characterization and therapeutics effects of human bone marrow- and umbilical cord-derived mesenchymal stromal cells in an experimental model of sepsis

Highlights: • Mesenchymal stromal cells (MSCs) may be a therapeutic option for sepsis. • Bone marrow (BM) vs. umbilical cord (UC) -MSCs induce different M1/M2 gene profiles. • In a CLP model of sepsis, only BM-MSCs improved survival and bacterial clearance. Sepsis is a complicated multi-system disorder characterized by a dysregulated host response to infection. Despite substantial progress in the understanding of mechanisms of sepsis, translation of these advances into clinically effective therapies remains challenging. Mesenchymal Stromal Cells (MSCs) possess immunomodulatory properties that have shown therapeutic promise in preclinical models of sepsis. The therapeutic effects of MSCs may vary depending on the source and type of these cells. In this comparative study, the gene expression pattern and surface markers of bone marrow-derived MSCs (BM-MSCs) and umbilical cord-derived MSCs (UC-MSCs) as well as their therapeutic effects in a clinically relevant mouse model of polymicrobial sepsis, cecal ligation and puncture (CLP), were investigated. The results showed remarkable differences in gene expression profile, surface markers and therapeutic potency in terms of enhancing survival and pro/anti-inflammatory responses between the two MSC types. BM-MSCs improved survival concomitant with an enhanced systemic bacterial clearance and improved inflammatory profile post CLP surgery. Despite some improvement in the inflammatory profile of the septic animals, treatment with UC-MSCs did not enhance survival or bacterial clearance. Overall, the beneficial therapeutic effects of BM-MSCs over UC-MSCs may likely be attributed to their pro-inflammatory function, and to some extent anti-inflammatory features, reflected in their gene expression pattern enhancing macrophage polarization to M1/M2 phenotypes resulting in a balanced pro- and anti-inflammatory response against polymicrobial sepsis.

60 APPLIED LIFE SCIENCES↗