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DOE OSTI2022

Performance of the Initial Implementation of the Shift Monte Carlo Code in SCALE 6.3

The Shift Monte Carlo code will be introduced in SCALE 6.3 as an alternative to the KENO V.a, KENO-VI, and Monaco codes. Calculations were performed to establish the performance of Shift for criticality safety analyses within the criticality safety analyses sequence (CSAS) based on models in the Verified, Archived Library of Inputs and Data (VALID). This test suite contains over 600 critical experiment models covering a broad range of fissile materials and neutron energy spectra. The comparisons presented include calculated k eff values and runtime performance for serial calculations and a selection of parallel calculations. Comparisons are presented for multigroup (MG) and continuous-energy (CE) calculations for KENO V.a and KENO-VI models. Results generated with a beta version of SCALE 6.3 indicate excellent agreement in k eff values between KENO and Shift. The largest differences in the average k eff value calculated for the 15 categories of KENO V.a models are 0.00020 ± 0.00011 Δ k for MG calculations and 0.00011 ± 0.00005 Δ k for CE calculations. Similar comparisons in three categories using KENO-VI result in the largest differences for MG calculations: as 0.00004 ± 0.00003 Δ k , and -0.00002 ± 0.00003 Δ k for CE. The preliminary results also indicate that Shift is faster than KENO on a per particle basis, especially for fast spectrum systems. The uncertainty per history is also higher, however, so the Monte Carlo figure of merit is higher for KENO for thermal and intermediate spectrum systems. As expected, Shift generally has better speedup than KENO for parallel calculations, regardless of neutron energy spectrum.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Tissue-mimicking phantoms for performance evaluation of photoacoustic microscopy systems

Phantom-based performance test methods are critically needed to support development and clinical translation of emerging photoacoustic microscopy (PAM) devices. While phantoms have been recently developed for macroscopic photoacoustic imaging systems, there is an unmet need for well-characterized tissue-mimicking materials (TMMs) and phantoms suitable for evaluating PAM systems. Our objective was to develop and characterize a suitable dermis-mimicking TMM based on polyacrylamide hydrogels and demonstrate its utility for constructing image quality phantoms. TMM formulations were optically characterized over 400–1100 nm using integrating sphere spectrophotometry and acoustically characterized using a pulse through-transmission method over 8–24 MHz with highly confident extrapolation throughout the usable band of the PAM system. This TMM was used to construct a spatial resolution phantom containing gold nanoparticle point targets and a penetration depth phantom containing slanted tungsten filaments and blood-filled tubes. These phantoms were used to characterize performance of a custom-built PAM system. The TMM was found to be broadly tunable and specific formulations were identified to mimic human dermis at an optical wavelength of 570 nm and acoustic frequencies of 10–50 MHz. Imaging results showed that tungsten filaments yielded 1.1–4.2 times greater apparent maximum imaging depth than blood-filled tubes, which may overestimate real-world performance for vascular imaging applications. Nanoparticles were detectable only to depths of 120–200 µm, which may be due to the relatively weaker absorption of single nanoparticles vs. larger targets containing high concentration of hemoglobin. The developed TMMs and phantoms are useful tools to support PAM device characterization and optimization, streamline regulatory decision-making, and accelerate clinical translation.

Hsu, Hsun-Chia↗

DOE OSTI2026

Redefining precision interferometry and spectroscopy with high-performance optical interference coatings

High-performance optical interference coatings have transformed precision interferometry and spectroscopy by enabling unparalleled control over light–matter interactions. This review explores recent innovations in ion-beam sputtered amorphous dielectric, as well as substrate-transferred crystalline coatings, and their impact on systems at the forefront of precision metrology. These state-of-the-art coating techniques generate multilayers with ultralow optical losses, yielding mirrors with exceptional reflectivity. Refinements in their noise performance push the ultimate limits of sensitivity, resolution, and stability in demanding laser-based metrology applications. These technologies underpin the most advanced timekeeping and spatial measurement tools, enabling high-finesse reference cavities for the world’s most precise optical atomic clocks and low-noise reflective test masses for km-baseline gravitational-wave detectors. Emerging hybrid designs combining these techniques expand access to the mid-infrared spectral region, enabling the first ultralow-optical-loss coatings in the 3000–5000 nm wavelength range for enhanced spectroscopy and trace-gas detection. We highlight how these technologies redefine coating performance metrics and set new benchmarks in quantum science, fundamental physics, and precision optical sensing.

Cole, Garrett D. [University of Arizona, Tucson, A↗

DOE OSTI2021

Using Models to Predict the Hygrothermal Performance of Equipment and Piping Insulation

The development of hygrothermal models began in earnest in the 1990s, with the initial emphasis on the performance of building envelope systems. Numerous large-scale building envelope failures associated with water intrusion drove this development. The physical principles of moisture transfer that apply to building envelopes are equally valid for equipment and piping insulation systems. The main advantage of modeling is that carefully characterized models can predict the long-term hygrothermal performance of any system under different climatic and interior conditions. Thermal insulations are commonly used on outdoor equipment and piping for different applications, such as thermal energy conservation and freeze protection. The insulated equipment usually experiences moisture intrusion due to many factors, such as the duration and frequency of moisture exposure, equipment operating temperature, insulation type, exposure temperature, weather conditions, equipment thermal cycling, and weatherproofing condition. Hygrothermal models have been employed to estimate the moisture pickup of insulated equipment and piping systems, as well as the moisture redistribution and subsequent change in thermal performance as these systems become contaminated with moisture. The hygrothermal model provides insights on the parameters influencing the time of wetness, the lateral redistribution of moisture along the pipe away from the leak, and the ease by which water escapes the insulation/jacketing systems. It has been shown that the moisture leak effect decreases rapidly with distance from the leak and that one- and two-dimensional hygrothermal simulations help to identify solutions to reduce conditions that support corrosion under insulation (CUI).

Shrestha, Som↗

DOE OSTI2019

First Ever Polymer Flood Field Pilot to Enhance the Recovery of Heavy Oils on Alaska’s North Slope – Polymer Injection Performance

Alaska North Slope (ANS) holds an estimated 20-30+ billion barrel heavy oil resources, yet the development pace has been very slow due to high development costs and low oil recovery using conventional waterflood and EOR methods. The objective of this pilot is to perform a field experiment to validate the use of an advanced polymer flooding technology to unlock the vast heavy oil resources on ANS. The advanced polymer flooding technology combines polymer flooding, low salinity water flooding, horizontal wells, and if necessary, injection conformance control treatments into one integrated process to significantly improve oil recovery from heavy oil reservoirs. Two pairs of horizontal injection and production wells have been deployed in an isolated fault block of the Schrader Bluff heavy oil reservoir at the Milne Point Field to conduct a polymer flood pilot. The pilot will acquire scientific knowledge and field performance data to optimize polymer flood design in the Schrader Bluff heavy oil reservoirs on ANS. Polymer injection started on August 28, 2018 using a custom made polymer blending and pumping unit. This paper focuses on the facility setup and polymer injection performance into the horizontal injectors drilled and completed in the Schrader Bluff heavy oil reservoir. Partially hydrolyzed polyacrylamide (HPAM) polymer was selected and the initial target viscosity was set at 45 centipoise. Polymer injection rate was set at 2200 bbl/day for one injector (J-23A) and 1200 bbl/day for the other (J-24A) based on production voidage. Injection pressure was controlled at below fracture pressure to prevent fracturing the reservoir and causing fast breakthroughs. Step rate and pressure falloff tests indicate that short term polymer injectivity is similar to water injectivity, which means that injectivity is mostly controlled by fluid mobility deep in the reservoir rather than that in the vicinity of the injection wellbore. Long term injection data indicate that polymer injectivity has been decreasing in both injectors as the reservoir is filled by polymer. No polymer has been observed in the production stream 7 months after the start of polymer injection compared with a 3-month breakthrough time with waterflood. This indicates that polymer significantly delays breakthrough time which will lead to increased sweep efficiency.

Ning, Samson↗

DOE OSTI2022

Evaluating the Effects of Nitrogen Doping and Oxygen Doping on SRF Cavity Performance

Superconducting radiofrequency (SRF) cavities are resonators with extremely low surface resistance that enable accelerating cavities to have extremely high quality factors (Q₀). High Q₀ decreases the capital required to keep the accelerators cold by reducing power loss. The performance of SRF cavities is largely governed by the surface composition of the first §I{100}{nm} of the cavity surface. Impurities such as oxygen and nitrogen have been observed to yield high Q₀, but their precise roles are still being studied. Here, we compare the performance of cavities doped with nitrogen and oxygen in terms of surface composition and heating behavior with field. A simulation of the diffusion of oxygen into the bulk of the cavity was built using COMSOL Multiphysics software. Simulated results were compared to the actual surface composition of the cavities as determined from secondary ion mass spectrometry analysis. Understanding how these impurities affects performance allows us to have further insight into the underlying mechanisms that enable these surface treatments to yield high Q₀.

43 PARTICLE ACCELERATORS↗

DOE OSTI2026

CHARACTERIZING AND CONTROLLING RECOVERY AND RECRYSTALLIZATION IN NIOBIUM FOR IMPROVED SRF CAVITY PERFORMANCE

Crystal defects, such as dislocations and low-angle boundaries, provide sources of magnetic flux trapping in the Nb materials used for superconducting radio frequency (SRF) resonating cavities. Improving the performance of SRF cavities, as measured through the quality factor, requires reducing these defects. SRF cavity production involves deformation processing, such as rolling and forming, and strategic annealing heat treatments. The resulting microstructures can be recovered, recrystallized, or both. Because recovery leaves many defects that can trap flux, recrystallization should improve cavity performance. Thus, processing schedules that produce complete recrystallization without excessive grain growth need to be designed. Solutions to this problem require understanding physical metallurgy and differentiating between recovered and recrystallized regions of microstructure. Backscattered electron microscopy techniques are applied to this end. We demonstrate that the conditions required to produce fully recrystallized microstructures depend on Nb impurity content, suggesting that processing schedules may need to be adjusted by material heat or lot. We also demonstrate that processing can be used to control growth of recrystallized grains to maintain mechanical strength in fully recrystallized materials. Forming cavities from cold-rolled Nb sheet material may provide strategic new routes to obtain microstructures that improve SRF cavity performance.

Taleff, E. [The University of Texas at Austin]↗

DOE OSTI2020

BASS: An R Package for Fitting and Performing Sensitivity Analysis of Bayesian Adaptive Spline Surfaces

In this work, we present the R package BASS as a tool for nonparametric regression. The primary focus of the package is fitting fully Bayesian adaptive spline surface (BASS) models and performing global sensitivity analyses of these models. The BASS framework is similar to that of Bayesian multivariate adaptive regression splines (BMARS) from Denison, Mallick, and Smith (1998), but with many added features. The software is built to efficiently handle significant amounts of data with many continuous or categorical predictors and with functional response. Under our Bayesian framework, most priors are automatic but these can be modified by the user to focus on parsimony and the avoidance of overfitting. If directed to do so, the software uses parallel tempering to improve the reversible jump Markov chain Monte Carlo (RJMCMC) methods used to perform inference. We discuss the implementation of these features and present the performance of BASS in a number of analyses of simulated and real data.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

PyPVRPM: Photovoltaic Reliability and Performance Model in Python

The ability to perform accurate techno-economic analysis of solar photovoltaic (PV) systems is essential for bankability and investment purposes. Most energy yield models assume an almost flawless operation (i.e., no failures); however, realistically, components fail and get repaired stochastically. This package, PyPVRPM, is a Python translation and improvement of the Language Kit (LK) based PhotoVoltaic Reliability Performance Model (PVRPM), which was first developed at Sandia National Laboratories in Goldsim software (Granata et al., 2011) (Miller et al., 2012). PyPVRPM allows the user to define a PV system at a specific location and incorporate failure, repair, and detection rates and distributions to calculate energy yield and other financial metrics such as the levelized cost of energy and net present value (Klise, Lavrova, et al., 2017). Our package is a simulation tool that uses NREL’s Python interface for System Advisor Model (SAM) (National Renewable Energy Laboratory, 2020b) (National Renewable Energy Laboratory, 2020a) to evaluate the performance of a PV plant throughout its lifetime by considering component reliability metrics. Besides the numerous benefits from migrating to Python (e.g., speed, libraries, batch analyses), it also expands on the failure and repair processes from the LK version by including the ability to vary monitoring strategies. These failures, repairs, and monitoring processes are based on user-defined distributions and values, enabling a more accurate and realistic representation of cost and availability throughout a PV system’s lifetime.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

The Institute for Sustained Performance, Energy, and Resilience

The Green Queue framework is a framework designed to automate the development and deployment of customized architecture- and application-aware power savings recipes for large-scale HPC applications achieving up to 21% and 32% energy savings on HPC production applications run at scale. Additional work focused on the memory sub-system involved our methodology that uses application and machine characterization information to build predictive machine learning models that can accurately quantify phase-level sensitivity to the reduced per core memory bandwidth resulting from changes in the memory bus frequency to reduce the power. We evaluated the predictive capability of the model on real applications and validated them at a fine grain level by looking at 43 individual computational phases or application hotspots as well as the whole application. For more than 91% of the application hotspots, the prediction error is less than 10% (15) . Building from these validated performance and power models collaborations among SUPER team members developed an automated end-to-end system to reduce the complexity of developing and deploying machine learning models for performance, power, and energy. The new framework Automatic Multi-objective Modeling with Machine Learning (AutoMOMML) enabled multi-objective optimizations (power and performance) for HPC workloads.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

DNB performance with modified FY19-GEN1 tests [Slides]

GEN1 boiling model is developed to assess the DNB prediction performance for ”high pressure” flow test, showing “consistent under-prediction”. Based on lessons learned from previous DNB test, a modified boiling model is proposed and tested for high pressure application. For selected tests, modified GEN1 boiling model shows improved DNB performance. Interestingly, DNB performance become poor when the subcooled level is high. More-like PWR condition (High pressure, low subcooled condition), the CASL GEN1 boiling modeling predict the DNB with reasonable accuracy.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2019

Performance Evaluation of the ThermoLift Natural Gas Fired Air Conditioner and Cold-Climate Heat Pump

ThermoLift is currently developing its Thermal Compression Heat Pump (TCHP™), a natural-gas driven air conditioner and cold-climate heat pump, which can provide space heating, water heating, and air conditioning simultaneously in a single device. The system has broad application as a combined heating, ventilation, and air-conditioning (HVAC) solution with the benefit of substantial energy, cost, and greenhouse gas (GHG) reductions. Unlike traditional vapor compression heat-pumps, the TCHP™ uses helium as a working fluid in place of high global warming potential (GWP) refrigerants. The development effort has produced three iterations or generations of prototypes with advancement of the technology readiness level (TRL) from TRL-1 (TCHP™ Gen 1.0) to TRL-5 (TCHP™ Gen 3.0). In August of 2013, the US DOE solicited the submission of proposals through funding opportunity announcement DE-FOA-0000823, Building Technologies Innovations Program. The Office of Energy Efficiency and Renewable Energy (EERE) subsequently accepted ThermoLift’s proposal to develop a heat pump system based on the Hofbauer cycle, a new cycle that supplants the Vuilleumier cycle and provided funding for prototype evaluation at Oak Ridge National Laboratory (ORNL). ORNL is a widely known research center for developing and evaluating building technologies. Through its Building Technologies Research and Integration Center, ORNL has unique capabilities which allows them to collaborate with industry and academia to advance building component technologies. The TCHP™ Gen 3.0 prototype was shipped to ORNL on July 23, 2018. After installation and integration of the heat pump into ORNL’s test facility and performing instrumentation validation and calibration, extended operation of the heat pump was achieved during continuous operation on August 6, 2018, and includes various heating and cooling temperature ranges and performance analysis. The Gen 3.0 prototype was evaluated at four “ambient” temperatures: −25°C, −8.33°C, 8.33°C, and 20°C, (−13°F, 17°F, 47°F, and 68°F) denoted as test points 1-4, respectively. For heating, cycle coefficients of performance (COP) at the four “ambient” temperatures were found to be 1.30, 1.46, 1.52, and 1.61, respectively. Furthermore, there is no capacity reduction as the inlet temperature to the cold heat exchanger (HX) decreases. The heating capacity delivered by the TCHP was found to be 12 kW at -25°C. Finally, this final report identifies measures for obtaining further efficiency improvements.

42 ENGINEERING↗

DOE OSTI2019

BOM: The Next Generation of High Performance Explosives

The EPA has declared phase-out of Trinitrotoluene (TNT) a priority due to toxicity concerns. LANL and the Army Research Laboratory created a melt-castable next generation high performance explosive to replace TNT. They invented bis(1,2,4-oxadiazole)bis(methylene) dinitrate, or BOM, a higher-performing, safer replacement, which is 50% more energetic than TNT. BOM is less toxic to produce and use than TNT. Unlike competitors, BOM requires no performance-enhancing additives. BOM could replace TNT in a variety of civilian and military applications. BOM has been synthesized at the multi-kilogram scale.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2019

NEAMS Workbench and Bison Fuel Performance Remote Application Configuration

The mission of the US Department of Energy (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program is to develop, apply, deploy, and support state-of-the-art predictive modeling and simulation tools for the design and analysis of current and future nuclear energy systems. This is accomplished using computing architectures that range from laptops to leadership class facilities. The NEAMS Workbench [1,2,3] initiative will facilitate the transition from conventional computer codes to high-fidelity ones by providing a common analysis environment and interface for model creation, review, execution, output review, and visualization for integrated codes. The BISON fuel performance code [4] is a finite element method (FEM)-based software being developed by multiple organizations led by the Idaho National Laboratory for the US Department of Energy Office of Nuclear Energy. BISON can simulate a variety of fuel and cladding compositions and geometries in varying dimensionalities, depending upon the problem type and complexity, including one-dimensional (1D), 1.5D, 2D axially symmetric (2D-rz), 2D radial-azimuthal (2D-rθ), or 3D models. The NEAMS Workbench allows execution of the BISON fuel performance code on local and remote compute resources. In this report, the detailed instructions of configuring the NEAMS Workbench for remote execution of the BISON fuel performance code on a portable batch system (PBS)-scheduled compute resource, as well the transfer of associated Bison files, is illustrated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2019

Fundamental Surface Science of PFCs for Improved Plasma Performance in NSTX-U

This research applies to improving the plasma performance in the National Spherical Torus Experiment-Upgrade (NSTX-U). NSTX-U will extend the high performance plasmas produced and controlled in NSTX by doubling the heating power and extending the pulse duration by a factor of five. Both of these will substantially raise the thermal stress on plasma facing components (PFCs). Liquid metal-based PFCs, in particular lithium, have been used to improve the plasma performance of many tokamaks, but the predictive understanding needed for confident application of liquid metals and coatings in NSTX-U and future machines is in its infancy. Our work is aimed at applying surface analysis techniques to relevant materials and coatings in a controlled laboratory environment to understand the fundamental surface science and measure key properties that will guide the operations and optimize plasma facing materials at the higher temperatures expected in NSTX-U. Current plans for NSTX-U are to begin operations with carbon PFCs and gradually transition to refractory metal PFCs and liquid metal PFCs toward the end of the first 5 years. Accordingly, our research emphasizes the surface science of lithium on PFC substrates comprised of carbon, molybdenum, and stainless steel. Conditioning of these substrates with boron and the influence of impurities, such as water vapor, present in the tokamak environment will be investigated. These studies make quantitative measurements with low energy ion scattering (LEIS) and high-resolution X-ray photoelectron spectroscopy (HR-XPS) to characterize lithium and complex mixed-material deposits on metal single crystals, e.g. molybdenum, and practical alloys. We utilize ultrathin films of these deposits to be able to follow the surface chemistry and determine stoichiometry. The temperature dependence of surface properties and reactivity is a key parameter. Temperature programmed desorption (TPD) mass spectrometry is utilized to measure deuterium uptake and retention by these materials, and vibrational spectroscopy provides crucial information needed on surface species and chemical compounds. Additional measurements probe diffusion of oxygen into bulk lithium and explore lithium diffusion and wetting on molybdenum and stainless steel. The outcomes of these studies contributes to an improved understanding of plasma surface interactions and specific information needed for NSTX-U operations and the future development of lithium-conditioned plasma-facing components in high-heat flux long-pulse scenarios.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2019

Integrated Solutions for Optimized Performance (ISOP) Final Technical Report

The goal of this project was to demonstrate technical feasibility of an integrated approach for deep energy retrofits by packaging innovative technologies with smart communicating controls that represent the next generation of energy efficiency. The integrated solutions for optimized performance (ISOP) package integrates (i) advanced lighting and plug load controls; (ii) intelligent daylight harvesting through automated self-powered shades and window films; (iii) advanced HVAC controls sequences (ASHRAE Guideline (GDL) 36); and (iv) fault detection and diagnosis (FDD) and continuous commissioning (CCx) using advanced analytics. These technologies address energy use across multiple building end uses that represent more than 60% of the energy consumption in all commercial buildings. The project was structured to be implemented over three budget periods: Budget Period 1 scope included site selection, project design, site-specific customization of technology packages, procurement of technologies, initiation of installation of technologies, the development of a measurement and verification plan and collection of pre-retrofit data collection. The first year go/no-go decision was based on securing host sites representing 250,000 sq. ft. of occupied operational spaces, savings analysis, technology procurement and initiation of installation. Budget Period 2 planned to complete technology installations and initiate data collection of post-retrofit performance data. The second year go/no-go was to be the completion of technology installations and commissioning, metering and data collecting to support the requirements laid out in site specific M&V plans. Budget Period 3 planned to collect and analyze post-retrofit performance data and provide data and reporting to support energy efficiency rebate programs. After the team completed activities planned for Budget Period 1, the team reached a Go/No-Go Decision Point. At that point, TRC recommended that DOE discontinue the project without prejudice due to challenges with securing demonstration sites to meet the full 250,000 sf of occupied operational spaces and DOE concurred. In Budget Period 1, the TRC team developed criteria to recruit and evaluate potential demonstration host sites. TRC worked with Princeton University, the project demonstration partner, to identify buildings on their campus as potential candidates for the demonstration. Following the selection of demonstration sites, the TRC team customized energy technology packages according to the needs and characteristics of each site. TRC defined technology specifications, identified vendors, and conducted analysis to estimate energy and cost savings potential. The project team then developed schedules for technology procurement processes and scheduled for installation at all selected demonstration sites. The project team worked with Princeton University and DOE to develop an approach to verify energy savings achieved through measurement and verification (M&V) 2.0 methods. Princeton University initiated open bids to procure the necessary materials and installation contractors. Bid results came back higher than estimates due to a couple of factors – lack of familiarity of the bidders with the proposed technologies and lack of local trained installers to execute the installation of these new measures. Due to the higher bids, projects no longer met the internal cost-effectiveness criteria used by Princeton to proceed with procurement of the full suite of technologies as proposed in ISOP. Princeton had already procured parts of the ISOP package as part of a campus-wide initiative for FDD and lighting retrofits, but with the higher costs for other ISOP components, Princeton could no longer commit to the full ISOP package on the selected sites. Based on this, the team reached the Go/No-Go decision point, where they decided not to proceed with the project. Princeton is separately installing portions of the ISOP package where they individually meet Princeton’s payback criteria but on a different schedule than would have been needed for the DOE ISOP project. The team has learned several lessons from project progress in the first budget period. The team will utilize these lessons in future projects, as should any team which proceeds with a project around the ISOP technology. The first lesson is that more information about the proposed sites is required earlier in the process (perhaps even at the proposal stage) in order to have a successful demonstration. Technical details not evident earlier in the process (such as the TLED limitations for ALCS) can derail project execution. The second lesson is that pricing of emerging technologies is highly variable due to lack of familiarity of local installers and distributor with the proposed technologies as well as alternate bids using products they were more familiar with, but that cost more than the ones proposed by TRC. Finally, the last major lesson is that the host site’s internal project criteria is of critical importance. Based on these higher installed costs and lack of an informed installer base for the products proposed for this project, the project does not meet Princeton’s simple payback goals of five years.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Momentary Cessation: Improving Dynamic Performance and Modeling of Utility-Scale Inverter Based Resources During Grid Disturbances

Sandia National Laboratories worked with NERC staff to provide stakeholder guidance in responding to a May 2018 NERC alert regarding dynamic performance and modeling issues for utility-scale inverter-based resources. The NERC alert resulted from event analyses for grid disturbances that occurred in southern California in August 2016 and October 2017. Those disturbances revealed the use of momentary cessation of transmission connected inverter-based generation- a short time period when they ceased to inject current into the grid, counter to desired transmission operation. The event analyses concluded that, in many cases, the Western Interconnection system models used to determine planning and operating criteria do not reflect the actual behavior of solar plants, resulting in overly optimistic planning assessments and substandard operational responses. This technical report summarizes the gaps between the models and actual performance that were observed at those times, and the guidance that Sandia and NERC provided to owners of solar PV power plants, transmission planners, transmission operators and planning/reliability coordinators to modify existing models to reflect that actual performance

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Evaluation of short-term initial performance of a “Molekule Air” portable air cleaner

The aim of this project was to evaluate and characterize the performance of a MOLEKULE AIR air cleaner unit. The testing protocol comprised the evaluation of an unused Molekule Air unit operating at maximum (“boost” setting) fan speed setting. The device was tested over initial short-term periods of 70-80 h of continuous operation. The tested air cleaner was challenged in separate experiments with a well-characterized mixture of volatile organic compounds (VOCs), and with ozone. All tests were performed at realistic pollutant levels in a 20-m 3 environmental stainless-steel chamber. Variables controlled and measured in this study included the chamber temperature, relative humidity, the composition and concentration of the challenge VOCs, and the concentrations of ozone. Potential formation of byproducts was also investigated to assess the overall performance.

47 OTHER INSTRUMENTATION↗