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DOE OSTI2021

Control of the Plasma-Material Interface for Long Pulse Optimization in the Experimental Advanced Superconducting Tokamak (EAST) (Final Report)

This project involved a collaborative effort, led by Dr. Rajesh Maingi of Princeton Plasma Physics Laboratory, to understand and control the plasma-material interface to improve long pulse discharge control and performance in the EAST devices. The focus is on long pulse recycling control and optimization, which can be challenging because of their broad range of materials used for plasma-facing components (PFC) and wall conditioning techniques. The purpose of the EAST device is to demonstrate long-pulse, stable, high performance plasma operation, providing a test-bed for key physics and technology issues for next step devices. As part of these tests, EAST has deployed carbon for the lower divertor PFC, tungsten for the upper divertor, and molybdenum for the main wall. In addition wall coatings are deployed for long pulse recycling control: lithium (Li) via several delivery tools, boronization, and recently also siliconization; for example, in 2013, a layer of SiC was deposited on all of the graphite tiles. Oxygen is also present at trace levels, making for a complex mix of materials and plasma-materials interactions (PMI). This mix of materials and the limited durability of wall coatings, coupled to partially optimized cryo-pumping, lead to evolution of the recycling off the PFCs, which restricts the duration of stationary, high performance, long pulse discharges. Comparing the wall conditioning techniques, Li enables the highest energy confinement and lowest recycling for the longest duration, while also suppressing ELMs in certain discharges. More specifically, research activities at the University of Tennessee focused on heat flux profile measurements in EAST, modeling the surface response, including the bonding energetics and chemical interactions between Li with carbon, tungsten, hydrogen and impurities, in addition to post situ experimental characterization and analysis of the divertor plasma facing components in EAST. This final report describes the overall progress within each of these tasks at the University of Tennessee within the project.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Efficient prediction of concentrating solar power plant productivity using data clustering

Concentrating solar power (CSP) plants convert solar energy to electricity and can be deployed with a thermal storage capability to shift electricity generation from time periods with available solar resource to those with high electricity demand or electricity price. Rigorous optimization of plant design and operational strategies can improve the market-competitiveness and commercial viability; however, such optimization may require hundreds of annual performance simulations, each of which can be computationally expensive when including considerations such as optimization of dispatch scheduling, sub-hourly time resolution, and stochastic effects due to uncertain weather or electricity price forecasts. This paper proposes a methodology to reduce the computational burden associated with simulation of electricity yield and revenue for CSP plants over a single- or multi-year period. Data-clustering techniques are employed to select a small number of limited-duration time blocks for simulation that, when appropriately weighted, can reproduce generation and revenue over a single year or within each year of a multi-year period. After selection of appropriate data features and weighting factors defining similarity between time-series profiles, the methodology captured annual revenue within 2.3%, 1.7%, or 1.2% using simulation of 10, 30, or 50 three-day exemplar time blocks, respectively, for each of three single-year location/weather/market scenarios and five plant configurations ranging from low to high solar multiple and storage capacity. When applied to multi-year datasets, the proposed methodology can capture inter-year variability that is unavailable from typical meteorological year (TMY) datasets while simultaneously requiring simulation of less than a single year of data.

14 SOLAR ENERGY↗

DOE OSTI2017

Quantifying the impacts of agricultural management and climate change on soil organic carbon changes in the uplands of Eastern China

In order to implement optimal farming practices for increasing soil organic carbon (SOC) in agro-ecosystems, there is a need for understanding how management practices and climate change alter SOC levels. This study quantified the influence of agricultural management practices and climatic factors on SOC changes in Eastern China’s upland-crop fields in northern Jiangsu Province for the period of 2010–2039, by using the DeNitrification-DeComposition (DNDC, version 9.5) model. We utilized the currently most detailed soil database, which is at a scale of 1:50,000, containing 17,024 soil polygons derived from 983 upland soil profiles. Across all the examined scenarios of agricultural management practices, our results show that the carbon sequestration potential in the upper layer soil (0–50 cm) of the study area varied from 6.93 to 155.11 Tg C during 2010–2039, with an average rate of 59 to 1317 kg C ha-1 year-1. As a promising alternative, the combined scenario of crop residue return rate of 50% and farmyard manure incorporation rate of 50% is recommended for agricultural management practice in this region. Meanwhile, climate conditions play a significant role in the annual SOC changes as well. Air temperature increase of 2–4 °C leads to 3.41–7.51 Tg C decrease in SOC under conventional management for the entire study region. Decreasing or increasing precipitation by 20% would increase 0.57 Tg C or decrease 1.09 Tg C under the conventional management scenario, respectively. Additionally, among all the soil groups, the fluvo-aquic soils have the highest C sequestration rate in most scenarios. Our findings could be used to inform optimal agricultural management toward climate mitigation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Liquid Chromatography Coupled to Refractive Index or Mass Spectrometric Detection for Metabolite Profiling in Lysate-based Cell-free Systems

Engineering cellular metabolism for targeted biosynthesis can require extensive design-build-test-learn (DBTL) cycles as the engineer works around the cell's survival requirements. Alternatively, carrying out DBTL cycles in cell-free environments can accelerate this process and alleviate concerns with host compatibility. A promising approach to cell-free metabolic engineering (CFME) leverages metabolically active crude cell extracts as platforms for biomanufacturing and for rapidly discovering and prototyping modified proteins and pathways. Realizing these capabilities and optimizing CFME performance requires methods to characterize the metabolome of lysate-based cell-free platforms. That is, analytical tools are necessary for monitoring improvements in targeted metabolite conversions and in elucidating alterations to metabolite flux when manipulating lysate metabolism. In this work, metabolite analyses using high-performance liquid chromatography (HPLC) coupled with either optical or mass spectrometric detection were applied to characterize metabolite production and flux in E. coli S30 lysates. Specifically, this report describes the preparation of samples from CFME lysates for HPLC analyses using refractive index detection (RID) to quantify the generation of central metabolic intermediates and by-products in the conversion of low-cost substrates (i.e., glucose) to various high-value products. The analysis of metabolite conversion in CFME reactions fed with 13 C-labeled glucose through reversed-phase liquid chromatography coupled to tandem mass spectrometry (MS/MS), a powerful tool for characterizing specific metabolite yields and lysate metabolic flux from starting materials, is also presented. Altogether, applying these analytical methods to CFME lysate metabolism enables the advancement of these systems as alternative platforms for executing faster or novel metabolic engineering tasks.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

A mathematical model of tree harvesting in age-structured forests subject to beetle infestations

In this paper, we investigate a mathematical model for age-structured forest–beetle interactions that includes harvesting of trees. The aim is to broaden the understanding of the synergistic effects of harvesting and insect infestation on the age structure of the forests and the harvesting benefit. In the first part of this study, we consider different scenarios of the forest infestation by beetles and observe that the quantitative age profile of the forest depends significantly on whether the beetle population is in its endemic or epidemic states. In the second part, we also include harvesting of the forest trees and analyze two different harvesting strategies: cutting all trees older than a certain age, and cutting a fixed proportion of trees older than a certain age. Numerical simulations are implemented to determine the optimal cutting age for both harvesting strategies. The numerical simulations reveal that, independent of the steady state of the beetle population (that is, no beetles, endemic or epidemic state) clear cutting all trees older than a given age provides a higher harvesting benefit. Our numerical simulations further indicate that to obtain a fixed harvesting yield, a forest under a beetle epidemic state has to be cut at a younger age than if the forest were at an endemic beetle state or a no-beetle state.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Accelerated aging test of new plastic scintillators

Fogging in plastic scintillators is a degradation mechanism that reduces light collection efficiency. In an effort to reduce maintenance costs, multiple groups have attempted to understand and prevent this problem by changing plastic compositions and system level designs. New formulations have been produced that are promising with respect to fogging resistance. In this paper, we study a variety of new compositions by subjecting them to an accelerated aging experiment with varying temperature and humidity profiles. Compositions are analyzed for their resistance to degradation after saturation periods, with those containing polymethyl methacrylate and divinyl benzene being the most promising. Pulse height spectra revealed that after environmental aging, many of the samples suffered a reduction in light yield to different degrees, a result that could be due to heating of the samples and may be prevented by further production optimization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2016

Systems level analysis of the Chlamydomonas reinhardtii metabolic network reveals variability in evolutionary co-conservation

Metabolic networks, which are mathematical representations of organismal metabolism, are reconstructed to provide computational platforms to guide metabolic engineering experiments and explore fundamental questions on metabolism. Systems level analyses, such as interrogation of phylogenetic relationships within the network, can provide further guidance on the modification of metabolic circuitries. Chlamydomonas reinhardtii , a biofuel relevant green alga that has retained key genes with plant, animal, and protist affinities, serves as an ideal model organism to investigate the interplay between gene function and phylogenetic affinities at multiple organizational levels. Here, using detailed topological and functional analyses, coupled with transcriptomics studies on a metabolic network that we have reconstructed for C. reinhardtii , we show that network connectivity has a significant concordance with the co-conservation of genes; however, a distinction between topological and functional relationships is observable within the network. Dynamic and static modes of co-conservation were defined and observed in a subset of gene-pairs across the network topologically. In contrast, genes with predicted synthetic interactions, or genes involved in coupled reactions, show significant enrichment for both shorter and longer phylogenetic distances. Based on our results, we propose that the metabolic network of C. reinhardtii is assembled with an architecture to minimize phylogenetic profile distances topologically, while it includes an expansion of such distances for functionally interacting genes. This arrangement may increase the robustness of C. reinhardtii 's network in dealing with varied environmental challenges that the species may face. As a result, the defined evolutionary constraints within the network, which identify important pairings of genes in metabolism, may offer guidance on synthetic biology approaches to optimize the production of desirable metabolites.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Charge exchange recombination spectroscopy at Wendelstein 7-X

The Charge Exchange Recombination Spectroscopy (CXRS) diagnostic has become a routine diagnostic on almost all major high temperature fusion experimental devices. For the optimized stellarator Wendelstein 7-X (W7-X), a highly flexible and extensive CXRS diagnostic has been built to provide high-resolution local measurements of several important plasma parameters using the recently commissioned neutral beam heating. This paper outlines the design specifics of the W7-X CXRS system and gives examples of the initial results obtained, to include typical ion temperature profiles for several common heating scenarios, toroidal flow and radial electric field derived from velocity measurements, beam attenuation via beam emission spectra, and normalized impurity density profiles under some typical plasma conditions.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Toroidal modeling of runaway electron loss due to 3-D fields in DIII-D and COMPASS

The 3-D field induced relativistic runaway electron (RE) loss has been simulated for DIII-D, COMPASS and ITER plasmas, utilizing the MARS-F code incorporated with the recently developed and updated RE orbit module (REORBIT). Modeling shows effectively 100% loss of a post-disruption, high-current runaway beam in DIII-D, due to the 1 kG level of magnetic field perturbation produced by a fast growing n = 1 resistive kink instability. The RE loss is shown to be independent of the particle energy or the initial location of particles in the configuration space. Applied resonant magnetic perturbation (RMP) fields from in-vessel coils are not effective for RE beam mitigation in DIII-D, but do produce finite (>10%) RE loss in COMPASS, consistent with experimental observations in above two devices. The major reasons for this difference in RE control by RMP between these two devices are (i) the coil proximity to the RE beam and (ii) the effective coil current scaling versus the machine size and the toroidal magnetic field. About 10% RE loss fraction is also predicted for an ITER 15 MA scenario with pre-disruption plasma, highlighting the role of the plasma response. Up to 30% loss is computed, however, by artificially scaling the equilibrium pressure to zero. This is due to the more resistive plasma response and stronger resulting field line stochasticity. Distributions of the lost REs to the limiting surface show poloidally peaked profile near the high-field-side in both DIII-D and COMPASS, covering about 100o poloidal angle. Higher perturbation field level and/or higher particle energy also result in REs being lost to the low-field-side of the limiting surface of these two devices, increasing the effective wetted area. Finally, for the modeled ITER plasmas, the applied RMP field, with optimal poloidal spectrum that maximizes the edge localized mode control, leads to REs being lost to the lower divertor region of the limiting surface within a narrow poloidal band.

3-D field↗

DOE OSTI2015

Geant4 Computing Performance Benchmarking and Monitoring

Performance evaluation and analysis of large scale computing applications is essential for optimal use of resources. As detector simulation is one of the most compute intensive tasks and Geant4 is the simulation toolkit most widely used in contemporary high energy physics (HEP) experiments, it is important to monitor Geant4 through its development cycle for changes in computing performance and to identify problems and opportunities for code improvements. All Geant4 development and public releases are being profiled with a set of applications that utilize different input event samples, physics parameters, and detector configurations. Results from multiple benchmarking runs are compared to previous public and development reference releases to monitor CPU and memory usage. Observed changes are evaluated and correlated with code modifications. Besides the full summary of call stack and memory footprint, a detailed call graph analysis is available to Geant4 developers for further analysis. The set of software tools used in the performance evaluation procedure, both in sequential and multi-threaded modes, include FAST, IgProf and Open|Speedshop. In conclusion, the scalability of the CPU time and memory performance in multi-threaded application is evaluated by measuring event throughput and memory gain as a function of the number of threads for selected event samples.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Design-Space Exploration for Inverse-Design of Wind Turbine Blades Using Data-Driven Methods

The state-of-the-practice aerodynamic design methods for wind turbine blades is typically based on Blade-Element Momentum (BEM) theory using a pre-designed frozen family of airfoils. The airfoils are themselves typically designed using panel methods. The design of the next-generation of large flexible rotors will need to capture the non-linear aerodynamics and three-dimensional flow to reduce the levelized cost of wind energy. Data-driven methods for aerodynamic design using data generated by computational fluid dynamics offer an attractive alternative to BEM-based methods that captures the non-linear aerodynamics of the component airfoils as well as the root and tip sections. In this work, we develop and demonstrate a framework to "smartly" explore the relevant design space in combination with an appropriate automated CFD pipeline to evaluate the aerodynamics of each design. The design-space exploration framework uses appropriate perturbations to the airfoil shape and induction profile from a baseline shape in combination with the inverse-design using BEM. The resulting designs are evaluated using an automated CFD pipeline using the in-house CFD solver framework "Mercury". We perform verification and validation to establish the capability of the Mercury framework to predict the aerodynamic performance of wind turbines. The CFD simulation of the perturbed blade shapes are optimized to restart from the converged baseline simulation to reduce the computational time. Finally, we demonstrate the design-space exploration technique for the design of the outboard section and the full rotor using perturbations to the shape and operating conditions of the NREL 5-MW turbine.

aerodynamic design methods↗

DOE OSTI2019

Genome-Wide Analysis of Nitrate Transporter (NRT/NPF) Family in Sugarcane Saccharum spontaneum L.

Nitrate is the predominant nitrogen source for plant growth and development. However, sugarcane, globally used as the primary sugar crop and biofuel feedstock, displays a low nitrate use efficiency due to a low capacity in storing nitrate in shoots. It is well studied that the nitrate transporter (NRT/NPF) family functions as the gatekeeper in governing nitrogen uptake and distribution, and optimizing nitrogen utilization in plants. This makes it a promising target for improving nitrogen use efficiency in sugarcane. Here, we carried out a comprehensive analysis of NRT/NPF genes at a genome-wide scale in Saccharum spontaneum. A BLAST search of NRT/NPF genes was initially performed against recently released sugarcane genome, followed by phylogenetic, gene structure and protein motif analysis. Additionally, NRT/NPF gene expression profile from various tissues was obtained from RNA-seq data analysis. As a result, we identified 178 NPF, 20 NRT2, and 6 NRT3 genes which spread across all 8 monoploid chromosomes. NPF and NRT3 exhibit high levels of genetic diversities as opposed to NRT2 which is more evolutionarily conserved. Interestingly, several SsNPF genes are products of gene fusions of several tandem duplications, which provide valuable structural resources for functional characterization of nitrate transporters. Moreover, several genes are tissue-specific expressed, indicating roles in tissue-specific nitrate translocations. A substantial number of NRT/NPF genes are heterogeneous in terms of their gene structures and mRNA abundance. Taken together, our work provides a genetic foundation for future investigations of molecular and physiological functions of sugarcane nitrate transporters.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Isotope dependence of transport in ST40 hot ion mode plasmas

The ST40 compact, high-field spherical tokamak, operating at 2.1 T and with 1.8 MW of neutral beam heating, achieved central carbon impurity ion temperatures in excess of 10 keV, surpassing their business milestone of 100 M °C (8.6 keV). The high temperature discharges were in the hot ion mode, with $T_i \gg T_e$, and they were achieved in both hydrogen and deuterium plasmas with deuterium neutral beam injection. In order to achieve the high temperature scenarios, careful wall conditioning and scenario optimization was carried out in $H^0 \rightarrow H^+$, $D^0 \rightarrow H^+$, and finally in $D^0 \rightarrow D^+$ plasmas. The TRANSP transport code was employed to study the dependence of confinement and transport on isotopic mass, and the conditions that led to the high measured central ion temperatures in the $D^0 \rightarrow H^+$ and $D^0 \rightarrow D^+$ plasmas. The kinetic profiles input into TRANSP were inferred from line-of-sight and limited radial measurements as well as consistency with a number of other experimental constraints. The TRANSP results first showed that the main species central ion temperature was only 0.5–1 keV lower than the measured carbon impurity temperature, and thus in the high performance plasmas also surpassed the 100 M °C level. TRANSP also showed that while the electron thermal conduction loss was dominant, reductions in central ion transport, and an effective decoupling of the ions from the electrons, led to an increase in central ion temperatures with increasing plasma mass. In fact, the associated confinement times exhibited a strong dependence on the isotopic mass of the thermal plasma. These preliminary results are foundations for dedicated experiments with full kinetic profile measurements on ST40 in the next run campaign.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Foreground-immune CMB lensing reconstruction with polarization

Extragalactic foregrounds are known to generate significant biases in temperature based CMB lensing reconstruction. Several techniques, which include "source hardening'" and "shear-only estimators'' have been proposed to mitigate contamination and have been shown to be very effective at reducing foreground-induced biases. Here we extend both techniques to polarization, which will be an essential component of CMB lensing reconstruction for future experiments and investigate the "large lens'' limit analytically to gain insight on the origin and scaling of foreground biases, as well as the sensitivity to their profiles. Furthermore, using simulations of polarized point sources, we estimate the expected bias to both Simons Observatory and CMB-S4 like (polarization-based) lensing reconstruction, finding that biases to the former are minuscule while those to the latter are potentially non-negligible at small scales ($L$ ~ $1000-2000$). In particular, we show that for a CMB-S4 like experiment, an optimal linear combination of point-source hardened estimators can reduce the (point-source induced) bias to the CMB lensing power spectrum by up to two orders of magnitude, at a ~ 4% noise cost relative to the global minimum variance estimator.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

AWB-GCN: A Graph Convolutional Network Accelerator with Runtime Workload Rebalancing

The recent development of deep learning has been mostly focusing on Euclidean data, such as images, videos, audios, etc. However, most real-world information and relation are often expressed as graphs. To efficiently learn from graph data, graph convolutional networks (GCNs) emerge as a promising approach, showing advantages in several practical applications such as social network analysis, knowledge discovery, 3D modeling, motion capturing, etc. Real-world graphs are usually extremely large and imbalanced, posting significant performance demand and design challenges on the hardware dedicated for GCN inference. In this paper, we propose an architecture design called UW-GCN to accelerate graph convolutional network inference. To tackle the major performance bottleneck from workload imbalance, we propose dynamic neighborhood stealing and remote chunk shuffling techniques, relying on hardware flexibility to achieve hardware auto-tuning under negligible area or delay overhead. Specifically, UW-GCN is able to smartly profile the sparse graph pattern while continuously adjusting the workload distribution via routing reconfiguration among parallel processing elements (PEs). The ideal configuration is then reused in the remaining iterations. To the best of our knowledge, this is the first accelerator design particularly for GCN and the first work relying on hardware auto-tuning, which is normally based on software, to achieve near-optimal workload balance in processing sparse structures.

Geng, Tong↗

DOE OSTI2021

Coordinated Optimization and Control of Residential Solid State Power Substations in Electrical Distribution Network

This paper proposes a computationally efficient mixed integer linear programming (MILP) model for the coordinated optimization of solid-state power substations (SSPSs) in a feeder considering the full unbalanced three-phase structure of the distribution grid and its characteristics. The proposed model determines the optimal real and reactive power of each SSPS at the point of common coupling (PCC) that minimizes the operating cost and maximizes the system performance, e.g., voltage regulation and phase balancing. To improve the computational efficiency, an inscribed octagon is introduced to approximate the quadratic capacity constraints of components. Numerical simulation results show the effectiveness of the proposed model and significant improvements in voltage profiles and power imbalance between phases.

Liu, Guodong↗

DOE OSTI2016

Bohm-criterion approximation versus optimal matched solution for a cylindrical probe in radial-motion theory

The theory of positive-ion collection by a probe immersed in a low-pressure plasma was reviewed and extended by Allen et al. [Proc. Phys. Soc. 70, 297 (1957)]. The numerical computations for cylindrical and spherical probes in a sheath region were presented by F. F. Chen [J. Nucl. Energy C 7, 41 (1965)]. Here, in this paper, the sheath and presheath solutions for a cylindrical probe are matched through a numerical matching procedure to yield “matched” potential profile or “M solution.” The solution based on the Bohm criterion approach “B solution” is discussed for this particular problem. The comparison of cylindrical probe characteristics obtained from the correct potential profile (M solution) and the approximated Bohm-criterion approach are different. This raises questions about the correctness of cylindrical probe theories relying only on the Bohm-criterion approach. Also the comparison between theoretical and experimental ion current characteristics shows that in an argon plasma the ions motion towards the probe is almost radial.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Evaluating Utility-Scale PV-Battery Hybrids in an Operational Model for the Bulk Power System

Systems that combine solar photovoltaic and battery energy storage technologies (PV-BES) are increasingly being proposed and deployed on the bulk power system. The operations and value of PV-BES systems have been extensively studied from the project developer's perspective through analyses that maximize plant-level revenue. However, PV-BES hybrids' operational characteristics are seldom studied from the perspective of bulk power system operators, who seek to optimize the performance of a suite of generation and storage assets that are connected via the transmission network. This work presents modeling approaches for representing and evaluating PV-BES hybrids in a model that optimizes operations across the bulk power system. Its novel contributions include demonstrating a technique to modify a unit commitment and dispatch model to represent the operational synergies of PV-BES hybrids. In particular, we describe the challenges and an approach for representing so-called DC-coupled PV-BES - which utilize a single bi-directional inverter - as a dispatchable resource in a commercial, production cost model (PCM), PLEXOS. We demonstrate this technique in a PCM study of the Los Angeles Department of Water and Power (LADWP) test system, by replacing existing PV and battery generators on the test system with our PV-BES hybrids. We then pursue scenario analysis that is designed to isolate the various drivers of operational strategies for DC-coupled PV-BES hybrids, including the nature of coupling, PV penetration on the system, and varying inverter loading ratios (or degrees of over-sizing of the PV field). Results from the analysis include utilization profiles for the PV DC energy across available pathways, dispatch profiles for the battery component, and the hybrid technologies' impacts on system-wide production costs. The approach presented in this paper can be used in any PCM that is looking to study PV-BES hybrids as a resource in different power system configurations and services.

14 SOLAR ENERGY↗