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At least 793 records · Page 44

Giant nonlinear optical responses from photon-avalanching nanoparticles

Avalanche phenomena use steeply nonlinear dynamics to generate disproportionately large responses from small perturbations, and are found in a multitude of events and materials. Photon avalanching enables technologies such as optical phase-conjugate imaging, infrared quantum counting and efficient upconverted lasing. However, the photon-avalanching mechanism underlying these optical applications has been observed only in bulk materials and aggregates, limiting its utility and impact. In this study we report the realization of photon avalanching at room temperature in single nanostructures-small, Tm 3+ -doped upconverting nanocrystals-and demonstrate their use in super-resolution imaging in near-infrared spectral windows of maximal biological transparency. Avalanching nanoparticles (ANPs) can be pumped by continuous-wave lasers, and exhibit all of the defining features of photon avalanching, including clear excitation-power thresholds, exceptionally long rise time at threshold, and a dominant excited-state absorption that is more than 10,000 times larger than ground-state absorption. Beyond the avalanching threshold, ANP emission scales nonlinearly with the 26th power of the pump intensity, owing to induced positive optical feedback in each nanocrystal. This enables the experimental realization of photon-avalanche single-beam super-resolution imaging with sub-70-nanometre spatial resolution, achieved by using only simple scanning confocal microscopy and without any computational analysis. Pairing their steep nonlinearity with existing super-resolution techniques and computational methods, ANPs enable imaging with higher resolution and at excitation intensities about 100 times lower than other probes. The low photon-avalanching threshold and excellent photostability of ANPs also suggest their utility in a diverse array of applications, including sub-wavelength imaging and optical and environmental sensing.

36 MATERIALS SCIENCE↗

Simulations of the churning mode: Toroidally symmetric plasma convection and turbulence around the X-points in a snowflake divertor

Using a reduced MHD model, extended to include field-aligned thermal conduction, we present numerical simulations of the churning mode (CM): a toroidally symmetric, non-linear plasma vortex in the vicinity of the null points in a snowflake (SF) divertor [D. D. Ryutov et al., Phys. Scr. 89, 088002 (2014)]. Simulations are carried out across a range of inter-null separations, d xx ⁠, and inter-null orientations, θ⁠, primarily in conditions relevant to the MAST-U tokamak. We find that, when d xx is small, the CM induces additional transport across the X-points when β pm ≳8%, where β pm is the ratio of the plasma pressure in the null region to poloidal magnetic pressure at the midplane. This transport also increases approximately linearly as d xx is reduced. A diffusive model of this transport is shown to predict the total transport across the null points, where diffusion coefficients of up to ∼ 10 2 m 2 s −1 centered on a small region around the X-points are used. However, the CM also results in significant changes to the flux surfaces in the null region, which is not captured by this diffusive model. The changes in magnetic geometry mean the fractional exhaust power delivered to each divertor leg is highly sensitive to β pm ⁠, d xx ⁠, and θ⁠. For small values of θ⁠, the CM can induce a change in topology, redirecting exhaust power from a secondary divertor leg on the high field side to one on the low field side. Similar behavior is found in the fraction of exhaust power going to the inner and outer divertor. Such changes in the flux surfaces may not be captured by Grad–Shafranov solvers and so may be a source of error in the magnetic reconstruction of SF experiments. We consistently find that the fractional exhaust power going to a secondary divertor leg on the high field side is small, consistent with SF experiments.

Computer simulation↗

Markov Decision Processes for Intelligent, Risk-Informed Asset-Management Decision-Making

Advanced nuclear reactors are a promising option for aiding the world in achieving its net-zero carbon emission goals, however, there are significant challenges to attaining and maintaining economic competitiveness with other sources of electricity. To improve the economic competitiveness of advanced reactor designs, a project was initiated to explore the use of Markov Decision Processes (MDPs) to guide asset-management decision-making during advanced reactor operation. MDPs are a powerful tool for optimizing decision-making in complex environments and their application to advanced reactors can aid in planning maintenance and repair activities to minimize downtime and maximize generation. The described approach expands on previous work regarding the use of MDPs for operational decision-making through the direct incorporation of real-time plant information. The integral MDP analysis includes information from online component diagnostic tools and the plant’s real-time generation risk assessment (GRA) and probabilistic risk assessment (PRA), which evaluate plant risk from both an economic and safety perspective. The result is an asset-management optimization framework that is based on real-time data regarding plant component status and the current best-estimate of plant risk. The paper presents an overview of the theoretical framework to incorporate the different information pathways into an integral MDP analysis, along with example analyses.

Grabaskas, David↗

Position Papers for the ASCR Workshop on Reimagining Codesign

On behalf of the Advanced Scientific Computing Research (ASCR) program in the US Department of Energy (DOE) Office of Science, we are organizing a Workshop on Reimagining Codesign (ReCoDe). Codesign is the process of jointly designing interoperating components of a computing system—in particular: applications, algorithms, system software, programming models, and the hardware on which they run. The goal is to maximize the overall performance, efficiency, and other desirable qualities of the system as a whole. Codesign is a standard methodology in the embedded-systems community, where space, power, and cost constraints are commonly pitted against execution speed for a tightly constrained feature set. Over the last decade, the DOE has invested in codesign efforts to foster the development of exascale computing systems for broad classes of scientific and engineering applications. The ReCoDe workshop hopes to explore how scientific applications of interest to the DOE can be accelerated through close interactions with hardware designers and software-stack developers, in which all components adapt to each other’s requirements and constraints. We want to answer the question of what are the key tools and methodologies for accomplishing codesign in today’s computing landscape, and what will be the highest impact targets for meeting DOE’s emerging mission requirements. This workshop aims to bring together DOE, industry, and academia to identify opportunities to build on past codesign successes and identify new areas that are either emerging or that may need reimagining for the future. We want to continue to find opportunities that can be pursued as a joint effort and continue to break down the traditional customer/vendor dichotomy with true partnerships. From this work, DOE will benefit from increased application performance relative to what stock hardware or existing general-purpose roadmaps can provide, and vendors will benefit from expanding their hardware’s capabilities to address needs they might have not otherwise anticipated and thereby create more widespread interest in their products. The workshop will be structured around a set of breakout sessions, with every attendee expected to participate actively in the discussions. Afterward, workshop attendees—from DOE, industry, and academia—will produce a report for ASCR that summarizes the findings made during the workshop.

97 MATHEMATICS AND COMPUTING↗

Advanced Distributed Wind Turbine Controls Series: Part 2-Wind Energy in Isolated Grids – Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL)

In an isolated grid, wind turbines are typically deployed to provide energy to maximize energy production, reduce diesel-fuel consumption, reduce carbon emissions, and reduce costs for energy and fuel transportation. However, in addition to solely providing energy to the power system, wind turbines contain rotating masses and inverter-based controls that can enable various reliability and resilience services through advance controls. As part of the Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL) this paper demonstrates, through desktop simulations, advanced wind turbine controls that can be employed to support higher contributions of wind in isolated grids, and to demonstrate ways that wind can play a role in supporting stability of an isolated grid. This isolated grid used in these desktop simulations is comprised of a wind turbine (600 kW), solar PV (430 kW), battery energy storage system (1 MW/1MWh), a simulated diesel generator (2 MW) and various types of loads (critical, dynamic). We developed a model of the subsystems in MATLAB/Simulink and validated them with available data from real-world components on NREL's Flatirons Campus. These validated models are then configured for various case studies. We compare the output of the desktop simulation with a baseline case with the diesel generator. Active and reactive power control of the wind turbine can help improve frequency and voltage responses in the isolated grid, respectively. By utilizing a small integrated battery energy storage system in the DC-link of the wind turbine, we also demonstrate that wind turbines can help blackstart a critical load comparable to its rated power and support other renewables (e.g. solar PV) come online and pick up an additional load. This report illustrates some of these reliability and resilience services a wind turbine can provide in an isolated grid.

17 WIND ENERGY↗

Adaptive multibeam phased array design for a Spacelab experiment

The parametric tradeoff analyses and design for an Adaptive Multibeam Phased Array (AMPA) for a Spacelab experiment are described. This AMPA Experiment System was designed with particular emphasis to maximize channel capacity and minimize implementation and cost impacts for future austere maritime and aeronautical users, operating with a low gain hemispherical coverage antenna element, low effective radiated power, and low antenna gain-to-system noise temperature ratio.

Noji, T. T.↗

The economics of bootstrapping space industries - Development of an analytic computer model

A simple economic model of 'bootstrapping' industrial growth in space and on the Moon is presented. An initial space manufacturing facility (SMF) is assumed to consume lunar materials to enlarge the productive capacity in space. After reaching a predetermined throughput, the enlarged SMF is devoted to products which generate revenue continuously in proportion to the accumulated output mass (such as space solar power stations). Present discounted value and physical estimates for the general factors of production (transport, capital efficiency, labor, etc.) are combined to explore optimum growth in terms of maximized discounted revenues. It is found that 'bootstrapping' reduces the fractional cost to a space industry of transport off-Earth, permits more efficient use of a given transport fleet. It is concluded that more attention should be given to structuring 'bootstrapping' scenarios in which 'learning while doing' can be more fully incorporated in program analysis.

Goldberg, A. H.↗

Cycle-Powered Short Radius (1.9 m) Centrifuge: Effect of Exercise Versus Passive Acceleration on Heart Rate in Humans

In addition to extensive use of lower extremity physical exercise training as a countermeasure for the work capacity component of spaceflight deconditioning, some form of additional head-to-foot (+Gz) gravitational (orthostatic) stress may be required to further attenuate or prevent the signs and symptoms (nausea, vertigo, instability, fatigue) of the general reentry syndrome (GRS) that can reduce astronaut performance during landing. Orthostatic (head-to-foot) stress can be induced by standing, by lower body negative pressure, and by +Gz acceleration. One important question is whether acceleration training alone or with concurrent leg exercise would provide sufficient additive stimulation to attenuate the GRS. Use of a new human-powered centrifuge may be the answer. Thus, the purpose for this study was to compare heart rate (HR), i.e., a stress response during human-powered acceleration, in four men (35-62 yr) and two women (30-31 yr) during exercise acceleration versus passive acceleration (by an off-board operator) at 100% (maximal acceleration = A(max)), and at 25%, 50%, and 75% of A(max). Mean (+/-SE) A(max) was 43.7 +/- 1.3 rpm (+3.9 +/- 0.2Gz). Mean HR at exercise A(max) was 189 +/- 13 b/min (50-70 sec run time), and 142 +/- 22 b/min at passive A(max) (40-70 sec run time). Regression of mean HR on the various +Gz levels indicated explained variance (correlations squared) of r(exp 2) = 0.88 (exercise) and r(exp 2) = 0.96 (passive): exercise HR of 107 +/- 4 (25%) to 189 +/- 13 (100%) b/min were 43-50 b/min higher (p less than 0.05) than comparable passive HR of 64 +/- 2 to 142 +/- 22 b/min. Thus, exercise adds significant physiological stress during +Gz acceleration. Inflight use of this combined exercise and acceleration countermeasure may maintain work capacity as well as normalize acceleration and orthostatic tolerances which could attenuate or perhaps eliminate the GRS.

Greenleaf, J. E.↗

OGLE-2019-BLG-0960 Lb: the Smallest Microlensing Planet

We report the analysis of OGLE-2019-BLG-0960, which contains the smallest mass-ratio microlensing planet found to date (q = 1.2–1.6 × 10^(−5) at 1σ). Although there is substantial uncertainty in the satellite parallax measured by Spitzer, the measurement of the annual parallax effect combined with the finite source effect allows us to determine the mass of the host star (M(L) = 0.3–0.6 Mꙩ), the mass of its planet (m(p) = 1.4–3.1 Mꚛ), the projected separation between the host and planet (a(⊥) = 1.2–2.3 au), and the distance to the lens system (D(L) = 0.6–1.2 kpc). The lens is plausibly the blend, which could be checked with adaptive optics observations. As the smallest planet clearly below the break in the mass-ratio function, it demonstrates that current experiments are powerful enough to robustly measure the slope of the mass-ratio function below that break. We find that the cross-section for detecting small planets is maximized for planets with separations just outside of the boundary for resonant caustics and that sensitivity to such planets can be maximized by intensively monitoring events whenever they are magnified by a factor A > 5. Finally, an empirical investigation demonstrates that most planets showing a degeneracy between (s > 1) and (s < 1) solutions are not in the regime (|log s| ≫ 0) for which the "close"/"wide" degeneracy was derived. This investigation suggests that there is a link between the "close"/"wide" and "inner/outer" degeneracies and also that the symmetry in the lens equation goes much deeper than symmetries uncovered for the limiting cases.

Jennifer C. Yee↗

Spinel Cu–Mn–Cr Oxide Nanoparticle-Pigmented Solar Selective Coatings Maintaining >94% Efficiency at 750 °C

High-temperature concentrating solar power (CSP) system is capable of harvesting and storing solar energy as heat towards cost-effective dispatchable solar electricity. Solar selective coating is a critical component to boost its efficiency by maximizing solar absorptance and minimizing thermal emittance losses. However, maintaining a high solar-thermal conversion efficiency >90% for long-term operation at ≥750 ºC remains a significant challenge. Herein, we report spray-coated spinel Cu-Mn-Cr oxide nanoparticle-pigmented solar selective coatings on Inconel tube sections maintaining ≥94% efficiency at 750 ºC and ≥92.5% at 800 ºC under 1000x solar concentration after 60 simulated day-night thermal cycles in air, each cycle comprising 12h at 750 ºC/800 ºC and 12h cooling to 25 ºC. The solar spectral selectivity is intrinsic to the band-to-band and d-d transitions of non-stoichiometric spinel Cu-Mn-Cr oxide nanoparticles. Furthermore, this feature offers a large fabrication tolerance in nanoparticle volume fraction and coating thickness, facilitating low-cost and scalable spray-coated high-efficiency solar selective absorbers for high-temperature CSP systems.

14 SOLAR ENERGY↗

Progress in GaAs/CuInSe2 tandem junction solar cells

Much more power is required for spacecraft of the future than current vehicles. To meet this increased demand for power while simultaneously meeting other requirements for launch, deployment, and maneuverability, the development of higher-efficiency, lighter-weight, and more radiation resistant photovoltaic cells is essential. Mechanically stacked tandem junction solar cells based on (AlGaAs)GaAs thin film CLEFT (Cleavage of Lateral Epitaxial Film for Transfer) top cells and CuInSe2(CIS) thin film bottom cells are being developed to meet these power needs. The mechanically stacked tandem configuration is chosen due to its interconnect flexibility allowing more efficient array level performance. It also eliminates cell fabrication processing constraints associated with monolithically integrated multi-junction approaches, thus producing higher cell fabrication yields. The GaAs cell is used as the top cell due to its demonstrated high efficiency, and good radiation resistance. Furthermore, it offers a future potential for bandgap tuning using AlGaAs as the absorber to maximize cell performance. The CuInSe2 cell is used as the bottom cell due to superb radiation resistance, stability, and optimal bandgap value in combination with an AlGaAs top cell. Since both cells are incorporated as thin films, this approach provides a potential for very high specific power. This high specific power (W/kg), combined with high power density (W/sq m) resulting from the high efficiency of this approach, makes these cells ideally suited for various space applications.

Kim, N. P.↗

The future evolution of energy-water-agriculture interconnectivity across the US

Abstract Energy, water, and agricultural resources across the globe are highly interconnected. This interconnectivity poses science challenges, such as understanding and modeling interconnections, as well as practical challenges, such as efficiently managing interdependent resource systems. Using the US as an example, this study seeks to define and explore how interconnectivity evolves over space and time under a range of influences. Concepts from graph theory and input–output analysis are used to visualize and quantify key intersectoral linkages using two new indices: the ‘Interconnectivity Magnitude Index’ and the ‘Interconnectivity Spread Index’. Using the Global Change Analysis Model (GCAM-USA), we explore the future evolution of these indices under four scenarios that explore a range of forces, including socioeconomic and technological change. Analysis is conducted at both national and state level spatial scales from 2015 to 2100. Results from a Reference scenario show that resource interconnectivity in the US is primarily driven by water use amongst different sectors, while changes in interconnectivity are driven by a decoupling of the water and electricity systems, as power plants become more water-efficient over time. High population and GDP growth results in relatively more decoupling of sectors, as a larger share of water and energy is used outside of interconnected sector feedback loops. Lower socioeconomic growth results in the opposite trend. Transitioning to a low-carbon economy increases interconnectivity because of the expansion of purpose-grown biomass, which strengthens the connections between water and energy. The results highlight that while some regions may experience similar sectoral stress projections, the composition of the intersectoral connectivity leading to that sectoral stress may call for distinctly different multi-sector co-management strategies. The methodology we introduce here can be applied in diverse geographical and sectoral contexts to enable better understanding of where, when, and how coupling or decoupling between sectors could evolve and be better managed.

Khan, Zarrar (ORCID:0000000281478553)↗

A Learning-based Power Management Method for Networked Microgrids Under Incomplete Information

In this paper, we present a model-free reinforcement learning (RL)-based technique to solve the power management problem of networked microgrids (MGs), when the utility has only limited or no detailed knowledge of the MG asset models.The proposed method consists of two levels: at the first level, using an approximate RL strategy and aggregated data, a utility agent determines the locational price signals to maximize its profit under incomplete information on the MGs’ private data behind their points of common coupling (PCC). The proposed RL strategy enables the utility to adapt to changing system conditions and learn from previous experiences, while respecting the data ownership of the MGs. At the second level, the MGs receive the price signals to dispatch their generation/storage assets individually over look-ahead decision time window, while considering power flow constraints. The performance of the proposed RL technique has been verified under realistic operational scenarios.

Zhang, Qianzhi↗

Intelligent industrial demand response to increase grid flexibility and reliability: A review

The rapid transition toward renewable energy has introduced challenges in grid stability due to the intermittency of non-dispatchable sources like solar and wind. Industrial Demand Response (IDR) offers a promising, cost-effective solution that adjusts energy consumption patterns to align with supply, increases renewable utilization, and reduces costs. This review provides an updated analysis of IDR, sorting technologies into five categories: energy storage, scheduled energy usage, operational flexibility, on-site generation, and intelligent operations. Energy storage solutions, while requiring little flexibility, often have the longest payback periods. While slightly better, on-site generation also has longer payback periods, ranging from 5 to 20 years or more. Scheduled energy usage, operational flexibility, and intelligent operations allow significant peak reduction at lower capital costs but require greater flexibility. While 15–20 % peak reduction is within the range of all five categories, scheduled energy use and on-site energy generation are shown to have reductions of up to 70–80 % in select scenarios. Combining multiple IDR strategies from these five categories maximizes both financial and operational benefits. Synergistic approaches are shown to enhance grid stability while reducing costs. As the grid evolves, IDR will enable a more flexible, renewable-powered future that will benefit industrial facilities and the broader energy system.

Demand flexibility↗

Optimizing workplace charging facility deployment and smart charging strategies

This study introduces a workplace charging (WPC) optimization model that maximizes the total satisfied electric miles of employees’ plug-in electric vehicles, subject to a given annual budget. The model optimizes both planning decisions of charger number and power levels and operation decisions of charging spot assignment and charging schedule for the given temporal distribution of charging demands and varied electricity prices. Results of experiments based on national average travel data indicate that the actual WPC strategy varies by budget level. Through optimization, the strategy could reduce impacts of the varied electricity price by shifting charging schedules to periods when electricity prices are low. Also, the model is expanded to study the trade-off between providing WPC and addressing consequence of degraded charging service by including the per-mile shadow cost of unsatisfied charging demand. Finally, we observe that their relative competitiveness mainly depends on the actual shadow cost of WPC.

33 ADVANCED PROPULSION SYSTEMS↗

Direct Evidence of Charge Transfer upon Anion Intercalation in Graphite Cathodes through New Electronic States: An Experimental and Theoretical Study of Hexafluorophosphate

Graphite intercalation compounds continue to be central to technologies for electrochemical energy storage from anodes in established Li-ion batteries to cathodes in beyond Li-ion concepts paired with multivalent anodes. When used as a cathode, graphite intercalates a variety of anions with PF 6 - being among the most common. Paired with Li intercalation at the anode, the corresponding dual carbon battery yields high energy and power densities. Given the available choice of anions as intercalants, it is important to elucidate how the graphite structure accommodates them in order to tailor the molecular species to maximize charge and reversibility. However, the changes in electronic structure of the host graphite lattice upon anion intercalation are poorly understood compared to cations, which represent a fundamentally different reaction. Herein, PF 6 -intercalated graphite has been studied using techniques sensitive to electronic structure, namely, X-ray Raman spectroscopy (XRS), X-ray absorption near-edge spectroscopy (XANES), and X-ray emission spectroscopy (XES). Complementary full-potential, all-electron density functional theory calculations yielded excellent agreement with the spectra, thus providing insight into charge compensation in the graphite lattice. In particular, a pre-$π^*$ feature emerged in XRS/XANES, which is direct evidence of the removal of charge from the host lattice to compensate the intercalated anions, leading to an overall lowering of the Fermi energy level. This is expected to be characteristic of many intercalants in anion-intercalated graphite. The unambiguous identification of the origin of the pre-$π^*$ spectral feature, which is frequently seen in graphitic systems, is of broad interest to the spectroscopy of graphitic systems beyond the practical implications of anion-induced changes in the electronic properties for real devices.

36 MATERIALS SCIENCE↗

Comparative Thermal Performance of Downdraft and Updraft Forced Convection in a Representative 3x3 PWR Fuel Assembly

A plethora of theoretical, numerical, and experimental investigations have relied on updraft forced convection of operating fuel assemblies for light water-cooled fuel assemblies. The inertial scales of turbulence in updraft flow through PWR fuel assemblies are primarily influenced by upstream mixing patterns within the lower plenum and consequent acceleration of flow through the lower core and support plates into the bottom nozzles. In secondary heat transfer applications such as steam generation, recuperation and economization, downdraft flow is utilized to retrieve maximal sensible heat from the primary coolant. Sub-channel volumes aligned vertically could also benefit from force of gravity in developing turbulent flows. A large reduction in pumping power, associated cost of operation and maintenance, and improved balance of plant is suggested to be possible through downdraft forced convection in PWR-type reactors. This article explores the impact of downdraft forced convection within the well-studied 3x3 sub-channel within a range of 20 hydraulic diameters across a representative intermediate flow mixing grid. A range of inflow Reynolds number from 10,000 to 60,000 is simulated over a range of equivalent heat loads of 20% to 100% spanning 20 hydraulic diameters. The fuel rods are represented in true geometric detail, and a constant-value heat profile is assumed for the investigation. At each inflow condition, the turbulence intensity, peak velocity, local heat transfer coefficient, peak wall heat flux, and peak wall temperature are collected across the sub-channel and compared with an updraft configuration evaluated at the same conditions.

Rao, Vivek↗