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At least 1,027 records · Page 57

U.S. Solar Photovoltaic System and Energy Storage Cost Benchmark (Q1 2020)

This report benchmarks U.S. solar photovoltaic (PV) system installed costs as of the first quarter of 2020 (Q1 2020). We use a bottom-up method, accounting for all system and project-development costs incurred during the installation to model the costs for residential (with and without storage), commercial (with and without storage), and utility-scale systems (with and without storage). We also incorporate other system characteristics and performance factors, as well as ongoing costs, to benchmark LCOE for PV-standalone systems, and LCOSS for solar+storage.

14 SOLAR ENERGY↗

Biphasic solvents for post-combustion CO 2 capture from natural gas flue Gas

Fossil fuel fired power plants are generally expected to remain one of the most significant global sources of electricity for decades to come. Consequently, carbon management technologies are needed to reduce or eliminate ongoing emissions from these sources. Amongst the many techniques for carbon capture, aqueous amine-based absorbents (monoethanolamine, MEA, in particular) are, presently, considered the leading technology for post-combustion CO 2 point-source capture. These technologies are nevertheless limited by their high capital and regeneration energy costs. Biphasic solvents have been identified as an attractive alternative to traditional MEA based absorbents due to their potential energy savings. Thus far, however, the research on biphasic solvents has largely focused on their performance in coal flue gas while more dilute natural gas flue gas applications have received relatively little attention. Here, this work examines the performances of two novel biphasic solvent blends, diethylenetriamine (DETA) and triethylenetetramine (TETA), in CO 2 capture from a natural gas flue gas simulant. Across several regeneration tests, both solvents achieved considerable energy savings over the benchmark MEA solution. Specifically, the energy consumption per mol CO 2 recovered for the DETA-based and TETA-based solvents was 46 % and 35 % less than that of the benchmark MEA solution, respectively. Molecular dynamics simulations were also performed to gain a deeper understanding of the phase separation phenomena that occur as a consequence of CO 2 absorption. These simulations indicated that phase change was driven by the strong interaction between the absorption products and water, while the degree of separation depended on the CO 2 loading.

Biphasic solvents↗

Expanded Intercomparison of Nuclear Data Libraries Using Jupiter and Jupiter High-240 Experiments

There is a limited availability of plutonium experiments with sensitivity to lead in the ICSBEP (International Handbook of Evaluated Criticality Safety Benchmark Experiments) Handbook. The Jupiter and Jupiter High-240 experiments were performed at the National Criticality Experiments Research Center as a collaborative effort between Los Alamos National Laboratory and the Japan Atomic Energy Agency to assess lead void coefficients in a plutonium-lead system containing weapons- and reactor-grade plutonium, respectively. Concurrent with benchmark development, an intercomparison of calculations using different nuclear data libraries has been performed to assess the usability of the experimental data for nuclear data adjustment in a “softer-that-fast” neutron energy spectrum. Eigenvalue calculations using MCNP with the ENDF/B-VIII.0 and TENDL-2021 nuclear data libraries calculate closest to the benchmark values for Jupiter. Calculations using JENDL-5 and ENDF/B-VIII.1 match best with the Jupiter High-240 values. Lead void worth calculations using the various nuclear data libraries are all within 3σ of their respective measured values. Perturbation studies between ENDF/B-VIII.0 and ENDF/B-VIII.1 demonstrate an approximate increase in calculated eigenvalues for the Jupiter series experiments by ~240 pcm for plutonium (mostly 239 Pu) and ~120 pcm for lead accompanied by a decrease contributed by ~113 pcm for copper and ~13 pcm for stainless steel. Nuclear data sensitivities and uncertainties investigated using Whisper show slightly lower sensitivity to scatter than a lead-reflected plutonium sphere but greater sensitivity to neutron capture. The sensitivities between Jupiter and Jupiter High-240 for lead are very similar for both ENDF/B-VIII.0 and ENDF/B-VIII.1 nuclear data. These benchmarks are more sensitive to neutron capture in lead than other plutonium benchmark experiments and would be useful for both lead and 240 Pu validation. In conclusion, with the high degree of compensating effects between copper, lead, and plutonium cross sections, additional isolated Pb-Pu and Cu-Pu benchmarks would be beneficial in improving these nuclear data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Scalable Predictive Control and Optimization for Grid Integration of Large-Scale Distributed Energy Resources: Preprint

Integration of a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problem requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (controllable DERs) including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperformed other benchmark controllers regarding computation time without compromising operational performance.

DER↗

Scalable Predictive Control and Optimization for Grid Integration of Large-Scale Distributed Energy Resources

Integrating a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problems requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (controllable DERs), including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperforms other benchmark controllers regarding computation time without compromising operational performance.

DER↗

SBbadger: biochemical reaction networks with definable degree distributions

Abstract Motivation An essential step in developing computational tools for the inference, optimization and simulation of biochemical reaction networks is gauging tool performance against earlier efforts using an appropriate set of benchmarks. General strategies for the assembly of benchmark models include collection from the literature, creation via subnetwork extraction and de novo generation. However, with respect to biochemical reaction networks, these approaches and their associated tools are either poorly suited to generate models that reflect the wide range of properties found in natural biochemical networks or to do so in numbers that enable rigorous statistical analysis. Results In this work, we present SBbadger, a python-based software tool for the generation of synthetic biochemical reaction or metabolic networks with user-defined degree distributions, multiple available kinetic formalisms and a host of other definable properties. SBbadger thus enables the creation of benchmark model sets that reflect properties of biological systems and generate the kinetics and model structures typically targeted by computational analysis and inference software. Here, we detail the computational and algorithmic workflow of SBbadger, demonstrate its performance under various settings, provide sample outputs and compare it to currently available biochemical reaction network generation software. Availability and implementation SBbadger is implemented in Python and is freely available at https://github.com/sys-bio/SBbadger and via PyPI at https://pypi.org/project/SBbadger/. Documentation can be found at https://SBbadger.readthedocs.io. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗

Unsupervised Anomaly Detection in High-Dimensional Flight Data Using Convolutional Variational Auto-Encoder

The modern National Airspace System (NAS) is an extremely safe system. The industry has experienced a steady decrease in fatalities over the years. This can be contributed to both improved flight critical systems with redundant hardware and software protections as well as an increased focus on active monitoring and response to real time and historically identified vulnerabilities by implementing more resilient procedures and protocols. The main practice for identifying vulnerabilities in operations leverages domain expertise using knowledge about how the system should behave with the expected tolerances to known safety margins. This approach works well when the system has a well-defined operating condition. However, the operations in the NAS can be highly complex with various nuances that render it difficult to clearly pre-define all known safety vulnerabilities. With the advancement of data science and machine learning techniques, the potential to automatically identify emerging vulnerabilities in the observed operations has become more practical in recent years. The state-of-the-art anomaly detection approaches in aerospace data usually rely on supervised or semi-supervised learning. However, in many real-world problems such as flight safety creating labels for the data requires huge amount of efforts and is largely expensive. As a result, in this article, we develop a Convolutional Variational Auto-Encoder (CVAE), an unsupervised learning approach for anomaly detection in high-dimensional heterogeneous time-series data. We validate performance of CVAE compared to the state-of-the-art supervised learning approach (as an upper bound) as well as an supervised clustering based on K-Means (as a lower bound) on Yahoo!'s benchmark time series anomaly detection data. Finally, we showcase performance of CVAE on a case study of identifying anomalies in the first 60 seconds of commercial flights' take-offs using Flight Operational Quality Assurance (FOQA) data.

Milad Memarzadeh↗

The 0E2 benchmarks for PWR UO 2 decay heat: an analysis from the NEA WPNCS

This paper presents the work performed in the subgroup 16 of the Working Party for Nuclear Criticality Safety (WPNCS) of the OECD Nuclear Energy Agency. The main goal was to define two decay heat benchmarks for Spent Nuclear Fuel (one pincell and one assembly), perform calculations and compare and analyze the results in light of existing calorimetric measurements. The selected case is the PWR UO2 assembly 0E2, irradiated at the Ringhals-3 reactor and measured at the Clab facility in Sweden. In total, 21 institutes worldwide participated to the exercise, leading to 55 calculated results (named C). It was found that the measured decay heat values (E) can be satisfactorily reproduced with two-dimensional assembly calculations, leading to an average C/E value of 0.99, with an uncertainty (or one standard deviation) of ±0.01.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Scalable Predictive Control and Optimization for Grid Integration of Large-Scale Distributed Energy Resources

Integrating a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problems requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (control-lable DERs), including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperforms other benchmark controllers regarding computation time without compromising operational performance.

DER↗

Qutrit Randomized Benchmarking

Ternary quantum processors offer significant potential computational advantages over conventional qubit technologies, leveraging the encoding and processing of quantum information in qutrits (three-level systems). Therefore, to evaluate and compare the performance of such emerging quantum hardware it is essential to have robust benchmarking methods suitable for a higher-dimensional Hilbert space. We demonstrate extensions of industry standard randomized benchmarking (RB) protocols, developed and used extensively for qubits, suitable for ternary quantum logic. Using a superconducting five-qutrit processor, we find an average single-qutrit process infidelity of 3.8×10 -3 . Through interleaved RB, we characterize a few relevant gates, and employ simultaneous RB to fully characterize crosstalk errors. Finally, we apply cycle benchmarking to a two-qutrit CSUM gate and obtain a two-qutrit process fidelity of 0.85. Our results present and demonstrate RB-based tools to characterize the performance of a qutrit processor, and a general approach to diagnose control errors in future qudit hardware.

97 MATHEMATICS AND COMPUTING↗

MPF: A portable message passing facility for shared memory multiprocessors

The design, implementation, and performance evaluation of a message passing facility (MPF) for shared memory multiprocessors are presented. The MPF is based on a message passing model conceptually similar to conversations. Participants (parallel processors) can enter or leave a conversation at any time. The message passing primitives for this model are implemented as a portable library of C function calls. The MPF is currently operational on a Sequent Balance 21000, and several parallel applications were developed and tested. Several simple benchmark programs are presented to establish interprocess communication performance for common patterns of interprocess communication. Finally, performance figures are presented for two parallel applications, linear systems solution, and iterative solution of partial differential equations.

Malony, Allen D.↗

Performance, Combustion and Emissions Evaluation of Liquid Phase Port-Injected LPG on a Single Cylinder Heavy-Duty Spark Ignited Engine

Liquefied petroleum gas (LPG), like many other alternative fuels, has witnessed increased adoption in the last decade, and its use is projected to rise as stricter emissions regulations continue to be applied. However, much of its use is limited to dual fuel applications, gaseous phase injection, light-duty passenger vehicle applications, or scenarios that require conversion from gasoline engines. Therefore, to address these limitations and discover the most efficient means of harnessing its full potential, more research is required in the development of optimized fuel injection equipment for liquid port and direct injection, along with the implementation of advanced combustion strategies that will improve its thermal efficiency to the levels of conventional fuels. This paper focuses on the development of a liquid phase port-injection system for LPG, the design of a reference piston, and the baseline evaluation of the performance, combustion, and emissions characteristics of a single cylinder research engine to establish a benchmark comparable to existing LPG engines. A sweep of start of injection (SOI) timing is performed by injecting liquid LPG at several closed and open intake valve timings, which demonstrates no significant variation in engine performance, but accounts for a 10% reduction in bsCO with the optimal SOI timing. Spark timing sweep demonstrates the 50% burn crank angle location related to maximum brake torque (MBT) point with a brake thermal efficiency (BTE) of ~34% for the tested load case. The effect of equivalence ratio is also presented with optimal SOI timing at MBT condition. The engine starts exhibiting knocking combustion at 140kPa intake manifold air pressure (IMAP) with a peak torque of 253Nm and a 5% reduction in brake specific fuel consumption compared to the naturally aspirated scenario.

Fosudo, Toluwalase↗

Uncertainty Quantification of a Light Water Pulsed-Neutron Die-Away Experiment to Thermal Neutron Scattering Laws

Thermal neutron scattering laws are important nuclear data for many nuclear science and engineering applications. Validation helps to ensure that a thermal neutron scattering law has a high quality and often employs critical benchmarks as integral experiments. Recently, pulsed-neutron die-away benchmarks have been used as an experiment to validate thermal neutron scattering laws. Herein, we evidence how this alternative integral experiment has a high sensitivity to these nuclear data by performing an uncertainty quantification analysis. The analysis randomly sampled the nuclear model parameters associated with hydrogen bound in light water thermal neutron scattering law and sampled other nuclear data that influenced the experiment’s integral parameter (e.g., elastic scattering, absorption in hydrogen and oxygen) from their respective covariance matrices. The thermal neutron scattering law caused an uncertainty in the integral parameter that reached 2.67%, which exceeds by an order of magnitude the uncertainties induced in commonly used thermal solution critical benchmarks. The validation performed here, although limited due to a poor description of the historical experiment, indicated that the ENDF/B-VIII.0 thermal neutron scattering law well predicted the integral parameter. These results motivate further benchmark and validation efforts using pulsed-neutron die-away experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Advancements in Accelerator Physics and System Developments for the EIC

The development and enhancement of the Electron-Ion Collider (EIC) are founded on extensive research and development efforts aimed at achieving rigorous performance goals. This document outlines the crucial research and development (R&D) efforts that underpin the various systems and components of the EIC, including the polarized electron source and linear accelerator (linac) systems. Achieving the collider’s operational benchmarks relies on meticulously enhancing these components to optimize performance.

43 PARTICLE ACCELERATORS↗

ARC Software Validation Work for the FFTF Reactor

Extensive efforts have been carried out at ANL for the verification and validation of the Argonne Reactor Codes (ARC) software package currently used for the design of Versatile Test Reactor (VTR). The ARC software package consists of steady state neutronics and thermal hydraulics modeling capabilities which are being used by the VTR program to develop most of the VTR reactor design details which will be part of the licensing application. It is anticipated that this software will continue to be used for the design work and for initial operations although additional software may be introduced at a later time. The validation work was focused primarily on obtaining validation data consistent with VTR and usable for the ARC software. Because no critical facilities or operating fast spectrum reactors are available to do experiments for the VTR, the next best option is to identify historical experimental data that can be used as validation data. Early on in VTR, the ZPPR-15 set of experiments was identified as good validation data because of 1) the availability and quality of the data, 2) existing staff that are already familiar with the experimental machine and measurements, 3) most of the ZPPR-15 loadings of interest have already been processed into ARC models, and 4) a full uncertainty quantification has already been done for several loadings of ZPPR-15. The FFTF startup and operations data was identified as the most consistent reactor type that has validation data usable for VTR. Finally, the EBR-II fuel depletion measurements were identified as the best available validation data for VTR. It is important to note that both the FFTF and EBR-II reactors typically come with higher uncertainties than the ZPPR. In the frame of the discussed verification and validation efforts, the present document discusses the analysis of selected FFTF measurements included in the benchmark specifications of the International Reactor Physics Experiment (IRPhE) handbook. The FFTF reactor core configurations from the benchmark specification are presented in Section 2. The analysis is performed with the use of the ARC code suite available at ANL for fast reactor studies and is discussed in Section 3. The reactor parameters from the benchmark include criticality, neutron spectra, effective delayed neutron spectra, control rod worth, isothermal temperature coefficient and low energy gamma-ray spectra. The calculated values and the comparison with the experimental data is discussed in Sections 4 to 9 for each considered reactor parameter. Finally, conclusions are presented in Section 10.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Platinum group metal-free (PGM-free) integrated tandem junction photoelectrochemical (PEC) water splitting devices (Final Technical Report)

This project involves using solar light, a photoabsorber, and a catalyst to split water and produce hydrogen. The Department of Energy (DOE) targets for integrated photoelectrochemical (PEC) cells emphasize cost (electrode cost < $200/m 2 ), performance (> 15% solar to hydrogen (STH) efficiency), and stability (> 6 months electrode lifetime), but most approaches skew toward one specific metric. This project exploited interfacial integration of platinum group metal-free (PGM-free) catalysts on the high performance and high value tandem solar cells to attain or exceed the DOE benchmark STH energy conversion efficiency and durability. This was investigated in two thrusts by developing two PEC devices for direct comparison: the first is a high-performance monolithic device based on state-of-the-art GaInP 2 /GaAs tandem solar cells developed at National Renewable Energy Laboratory (NREL), and the second is a high-value device based on earth-abundant wide band gap photoabsorber materials including oxynitride and hybrid organic-inorganic perovskite (HOIP) coupled with commercial narrow band gap silicon (Si). Both these devices were paired with electrocatalysts developed for this purpose at Rutgers University by adapting them to thin films on the photoabsorbers. These catalysts are based on the hydrogen evolution reaction (HER) catalysts (Ni 5 P 4 ), oxygen evolution reaction (OER) catalysts (LiCo 2 O 4 ) previously developed at Rutgers for high-efficiency electrolyzers. For using the high-performance tandem solar cell and Ni 5 P 4 catalysts, we achieved a durability of > 200 h at a STH efficiency of > 10%. For using the high-value wide band gap single junction solar cells on n + Si, we achieved 0.73 mA/cm 2 at 1.23V vs reversible hydrogen electrode (RHE) and -15.9 mA/cm 2 at 0V vs RHE using the oxynitride- and HOIP-based photoelectrodes, respectively. After comparing their photocurrent densities, we down selected the HOIP photoabsorber to couple Si for fabrication of a tandem photocathode. However, due to the COVID-19 pandemic, both the laboratories at Rutgers and NREL were locked down for three months and reopened only partially in 2020. The HOIP/Si tandem photocathode using robust nickel phosphide thin film catalysts cannot be developed within the project period, which is expected to achieve a STH efficiency of > 20%. Also, the low-cost LiCo 2 O 4 OER catalysts need to replace the benchmark IrO 2 for evaluation. Finally, techonomic analysis of full high-performance and high-value integrated PEC devices needs to be carried out for comparison in terms of cost.

08 HYDROGEN↗

Aerosol-Assisted Deposition for TiO 2 Immobilization on Photocatalytic Fibrous Filters for VOC Degradation

Atomization and spraying are well-established methods for the production of submicrometer- and micrometer- sized powders. In addition, they could be of interest to the immobilization of photocatalytic nanoparticles onto supports because they enable the formation of microporous films with photocatalytic activity. Here, we provide a comparison of aerosol-assisted immobilization methods, such as spray-drying (SD), spray atomization (SA), and spray gun (SG), which were used for the deposition of TiO 2 dispersions onto fibrous filter media. The morphology, microstructure, and electronic properties of the structures with deposited TiO 2 were characterized by SEM and TEM, BET and USAXS, and UV-Vis spectrometry, respectively. The photocatalytic performances of the functionalized filters were evaluated and compared to the benchmark dip-coating method. Our results showed that the SG and SA immobilization methods led to the best photocatalytic and operational performance for the degradation of toluene, whereas the SD method showed the lowest degradation efficiency and poor stability of coating. We demonstrated that TiO2 sprays using the SG and SA methods with direct deposition onto filter media involving dispersed colloidal droplets revealed to be promising alternatives to the dip-coating method owing to the ability to uniformly cover the filter fibers. In addition, the SA method allowed for fast and simple control of the coating thickness as the dispersed particles were continuously directed onto the filter media without the need for repetitive coatings, which is common for the SG and dip-coating methods. Our study highlighted the importance of the proper immobilization method for the efficient photocatalytic degradation of VOCs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Validation of Oregon State University High Temperature Test Facility Experiments Using Pronghorn

The OSU High Temperature Test Facility is a quarter-scale diameter, 1/64 scale volume test facility meant to replicate thermophysical phenomena in the prototypical General Atomics Modular High Temperature Gas Reactor. Tests pertaining to conduction cooldown events were performed from 2016-2019, providing a large database by which computational methods that are applicable to different length scales can be validated. One of these codes is Pronghorn, which is a coarse-meshed, porous-based subchannel thermal hydraulics code based on the MOOSE application, with the intention of better capturing the physics of both conduction and convection heat transfer within the OSU HTTF core. The goal of this summer project is to develop the framework by which Pronghorn can perform validation exercises of the HTTF core for benchmarking, by generating a mesh appropriate to the geometry of the HTTF core, developing input decks that accurately capture the initial and boundary conditions, materials, and relevant equations to the physics seen in the HTTF core, and using a postprocessor to compare simulation results to various experimental data. While validation of codes is a multi-year project, a mesh has been generated and tested in Pronghorn that meets mass conservation and basic heat transfer principles. The next step is to accurate depict the fluid inlet and outlet boundary conditions, which will be performed using computational fluid dynamics software.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗