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At least 235 records · Page 13

Improved Low Temperature Performance of Graphite/Li Cells Using Isoxazole as a Novel Cosolvent in Electrolytes

An investigation of novel electrolyte formulations to improve low temperature performance of Li/graphite half cells has been conducted. A novel electrolyte co-solvent, isoxazole (IZ), has been investigated in electrolyte systems composed of lithium difluoro(oxalato)borate (LiDFOB) in fluoroethylene carbonate (FEC) and LiDFOB in ethylene carbonate (EC). Cells containing 1 M LiDFOB FEC: IZ electrolyte have a significant improvement in capacity retention and reversible capacity at −10 °C. Ex-situ surface analysis of the cycled electrodes suggests that reduction of LiDFOB results in an oxalate rich solid electrolyte interphase (SEI). Addition of FEC, results in improved stability of the anode SEI preventing further decomposition of isoxazole solvent and improving cycling performance.

25 ENERGY STORAGE↗

Earth System Reanalysis in Support of Climate Model Improvements

Recent climate model developments, established through increased model resolution, have led to substantial improvements in model simulations of the time-evolving, coupled Earth system and its subcomponents. However, regardless of resolution, climate models will always produce climate features and variability that differ from the real world and will be prone to biases. This is due to many remaining uncertainties, such as in parametric and structural model uncertainty, in the initial conditions prescribed, and in the prescribed (scenario) forcing which varies on decadal to centennial timescales. Further model improvements are expected to arise specifically from improved representation of physical processes realized through model-data fusion. This will create an unprecedented opportunity to better exploit a large array of Earth observations, from in situ measurements to weather radars and satellite observations, as the resolved scales of the models approach those of the observations. For this, climate DA will be the central tool to bring models and observations into consistency, by improving initial conditions, inferring uncertain model parameters and structure, and quantifying uncertainty. Generally, there will be advantages and complementarities of adjoint-based smoother approaches, ensemble-based filter approaches, or new ML-inspired approaches. Yet, the ever-increasing model resolution will present growing challenges arising from computational cost, calling for new ways of performing data assimilation and model optimization. Using the complementarity in a hybrid approach, blending tools and concepts from variational, ensemble and ML methods might be what is required in the future. In this context ML could be important to handle non-linear responses, and to better approximate non-Gaussian distributions.

54 ENVIRONMENTAL SCIENCES↗

Improved Representation of Horizontal Variability and Turbulence in Mesoscale Simulations of an Extended Cold-Air Pool Event

Abstract Cold-air pools (CAPs), or stable atmospheric boundary layers that form within topographic basins, are associated with poor air quality, hazardous weather, and low wind energy output. Accurate prediction of CAP dynamics presents a challenge for mesoscale forecast models in part because CAPs occur in regions of complex terrain, where traditional turbulence parameterizations may not be appropriate. This study examines the effects of the planetary boundary layer (PBL) scheme and horizontal diffusion treatment on CAP prediction in the Weather Research and Forecasting (WRF) Model. Model runs with a one-dimensional (1D) PBL scheme and Smagorinsky-like horizontal diffusion are compared with runs that use a new three-dimensional (3D) PBL scheme to calculate turbulent fluxes. Simulations are completed in a nested configuration with 3-km/750-m horizontal grid spacing over a 10-day case study in the Columbia River basin, and results are compared with observations from the Second Wind Forecast Improvement Project. Using event-averaged error metrics, potential temperature and wind speed errors are shown to decrease both with increased horizontal grid resolution and with improved treatment of horizontal diffusion over steep terrain. The 3D PBL scheme further reduces errors relative to a standard 1D PBL approach. Error reduction is accentuated during CAP erosion, when turbulent mixing plays a more dominant role in the dynamics. Last, the 3D PBL scheme is shown to reduce near-surface overestimates of turbulence kinetic energy during the CAP event. The sensitivity of turbulence predictions to the master length-scale formulation in the 3D PBL parameterization is also explored. Significance Statement In this article, we demonstrate how a new framework for modeling atmospheric turbulence improves cold pool predictions, using a case study from January 2017 in the Columbia River basin (U.S. Pacific Northwest). Cold pools are regions of cold, stagnant air that form within valleys or basins, and improved forecasts could help to mitigate the risks they pose to air quality, transportation, and wind energy production. For the chosen case study, our tests show a reduction in temperature and wind speed errors by up to a factor of 2–3 relative to standard model options. These results strongly motivate continued development of the framework as well as its application to other complex weather events.

17 WIND ENERGY↗

Improving Tropical Cyclogenesis Forecasts of Hurricane Irma (2017) through the Assimilation of All-Sky Infrared Brightness Temperatures

The assimilation of satellite all-sky infrared (IR) brightness temperatures (BTs) has been shown in previous studies to improve intensity forecasts of tropical cyclones. Here, in this study, we examine whether assimilating all-sky IR BTs can also potentially improve tropical cyclogenesis forecasts by improving the pregenesis cloud and moisture fields. By using an ensemble-based data assimilation system, we show that the assimilation of upper-tropospheric water vapor channel BTs observed by the Meteosat-10 SEVIRI instrument two days before the formation of a tropical depression improves the genesis forecast of Hurricane Irma (2017), a classic Cape Verde storm, by up to 24 h while also capturing its later rapid intensification in deterministic forecasts. In an experiment that withholds the assimilation of all-sky IR BTs, the assimilation of conventional observations from the Global Telecommunications System (GTS) leads to the premature genesis of Hurricane Irma by at least 24 h. This premature genesis is shown to result from an overestimation of the spatial coverage of deep convection within the African easterly wave (AEW) from which Irma eventually forms. The gross overestimation of deep convection without all-sky IR BTs is accompanied by higher column saturation fraction, stronger low-level convergence, and the earlier spinup of a low-level meso- β -scale vortex within the AEW that ultimately becomes Hurricane Irma. Through its adjustment to the initial moisture and cloud conditions, the assimilation of all-sky IR BTs leads to a more realistic convective evolution in forecasts and ultimately a more realistic timing of genesis.

54 ENVIRONMENTAL SCIENCES↗

An improved Method for Determining Transient Fuel Dilution of Oil in an Internal-Combustion Engine Using Laser-Induced Florescence and Multivariate Least Square Calibration

An optical diagnostic, based on laser-induced fluorescence (LIF), has been developed for on-engine measurements of real-time fuel dilution of engine oil or fuel in oil (FIO). Fuel dilution of oil is broadly relevant to advancing engine technology including durability, calibration, and catalyst-system management, and believed to promote destructive stochastic pre-ignition (SPI) during high-load engine operations. While standard (e.g., ASTM D3524-90) methods are not capable of real-time transient measurements, the LIF technique resolves transient dilution on the minutes time scale. We have expanded on our original FIO instrument development by introducing an improved analysis based on multivariate least square chemometrics analysis. The measurement uses a fuel dye (180–1300 parts per million, by mass) and monitors for its presence in the oil using 532 nm excitation and LIF. While the original FIO instrument utilized a two-color ratio method for analysis, the improved chemometric analysis uses the fully resolved LIF dye spectra to provide better predictive FIO accuracy (>92%) over a wide FIO range (1.5–14%) typical of engine application. We also investigate the effect of oil temperature on the LIF signal. Limited engine applications for demonstrating and validating the improved FIO instrument are shown, and the related data used to quantify practical detection limit and sensitivity. The improved analysis is insensitive to laser power fluctuation and change in detector integration time, providing an excellent FIO sensitivity (1–2%) and detection limit (0.01 %FIO) over a wide range of loads and injection timings, illustrating this updated approach to be a promising tool for advancing engine technology.

42 ENGINEERING↗

Metabolic engineering of Rhodotorula toruloides IFO0880 improves C16 and C18 fatty alcohol production from synthetic media

Abstract Background The oleaginous, carotenogenic yeast Rhodotorula toruloides has been increasingly explored as a platform organism for the production of terpenoids and fatty acid derivatives. Fatty alcohols, a fatty acid derivative widely used in the production of detergents and surfactants, can be produced microbially with the expression of a heterologous fatty acyl-CoA reductase. Due to its high lipid production, R. toruloides has high potential for fatty alcohol production, and in this study several metabolic engineering approaches were investigated to improve the titer of this product. Results Fatty acyl-CoA reductase from Marinobacter aqueolei was co-expressed with SpCas9 in R. toruloides IFO0880 and a panel of gene overexpressions and Cas9-mediated gene deletions were explored to increase the fatty alcohol production. Two overexpression targets ( ACL1 and ACC1 , improving cytosolic acetyl-CoA and malonyl-CoA production, respectively) and two deletion targets (the acyltransferases DGA1 and LRO1 ) resulted in significant (1.8 to 4.4-fold) increases to the fatty alcohol titer in culture tubes. Combinatorial exploration of these modifications in bioreactor fermentation culminated in a 3.7 g/L fatty alcohol titer in the LRO1 Δ mutant. As LRO1 deletion was not found to be beneficial for fatty alcohol production in other yeasts, a lipidomic comparison of the DGA1 and LRO1 knockout mutants was performed, finding that DGA1 is the primary acyltransferase responsible for triacylglyceride production in R. toruloides , while LRO1 disruption simultaneously improved fatty alcohol production, increased diacylglyceride and triacylglyceride production, and increased glucose consumption. Conclusions The fatty alcohol titer of fatty acyl-CoA reductase-expressing R. toruloides was significantly improved through the deletion of LRO1 , or the deletion of DGA1 combined with overexpression of ACC1 and ACL1 . Disruption of LRO1 surprisingly increased both lipid and fatty alcohol production, creating a possible avenue for future study of the lipid metabolism of this yeast.

59 BASIC BIOLOGICAL SCIENCES↗

Iron incorporation both intra- and extra-cellularly improves the yield and saccharification of switchgrass (Panicum virgatum L.) biomass

Abstract Background Pretreatments are commonly used to facilitate the deconstruction of lignocellulosic biomass to its component sugars and aromatics. Previously, we showed that iron ions can be used as co-catalysts to reduce the severity of dilute acid pretreatment of biomass. Transgenic iron-accumulating Arabidopsis and rice plants exhibited higher iron content in grains, increased biomass yield, and importantly, enhanced sugar release from the biomass. Results In this study, we used intracellular ferritin (FerIN) alone and in combination with an improved version of cell wall-bound carbohydrate-binding module fused iron-binding peptide (IBPex) specifically targeting switchgrass, a bioenergy crop species. The FerIN switchgrass improved by 15% in height and 65% in yield, whereas the FerIN/IBPex transgenics showed enhancement up to 30% in height and 115% in yield. The FerIN and FerIN/IBPex switchgrass had 27% and 51% higher in planta iron accumulation than the empty vector (EV) control, respectively, under normal growth conditions. Improved pretreatability was observed in FerIN switchgrass (~ 14% more glucose release than the EV), and the FerIN/IBPex plants showed further enhancement in glucose release up to 24%. Conclusions We conclude that this iron-accumulating strategy can be transferred from model plants and applied to bioenergy crops, such as switchgrass. The intra- and extra-cellular iron incorporation approach improves biomass pretreatability and digestibility, providing upgraded feedstocks for the production of biofuels and bioproducts.

09 BIOMASS FUELS↗

Data for Metabolic Engineering of Rhodotorula toruloides IFO0880 Improves C16 and C18 Fatty Alcohol Production from Synthetic Media

The oleaginous, carotenogenic yeast Rhodotorula toruloides has been increasingly explored as a platform organism for the production of terpenoids and fatty acid derivatives. Fatty alcohols, a fatty acid derivative widely used in the production of detergents and surfactants, can be produced microbially with the expression of a heterologous fatty acyl-CoA reductase. Due to its high lipid production, R. toruloides has high potential for fatty alcohol production, and in this study several metabolic engineering approaches were investigated to improve the titer of this product. Fatty acyl-CoA reductase from Marinobacter aqueolei was co-expressed with SpCas9 in R. toruloides IFO0880 and a panel of gene overexpressions and Cas9-mediated gene deletions were explored to increase the fatty alcohol production. Two overexpression targets (ACL1 and ACC1, improving cytosolic acetyl-CoA and malonyl-CoA production, respectively) and two deletion targets (the acyltransferases DGA1 and LRO1) resulted in significant (1.8 to 4.4-fold) increases to the fatty alcohol titer in culture tubes. Combinatorial exploration of these modifications in bioreactor fermentation culminated in a 3.7 g/L fatty alcohol titer in the LRO1Δ mutant. As LRO1 deletion was not found to be beneficial for fatty alcohol production in other yeasts, a lipidomic comparison of the DGA1 and LRO1 knockout mutants was performed, finding that DGA1 is the primary acyltransferase responsible for triacylglyceride production in R. toruloides , while LRO1 disruption simultaneously improved fatty alcohol production, increased diacylglyceride and triacylglyceride production, and increased glucose consumption. The fatty alcohol titer of fatty acyl-CoA reductase-expressing R. toruloides was significantly improved through the deletion of LRO1, or the deletion of DGA1 combined with overexpression of ACC1 and ACL1. Disruption of LRO1 surprisingly increased both lipid and fatty alcohol production, creating a possible avenue for future study of the lipid metabolism of this yeast.

Conversion↗

Adjoint Waveform Tomography for Crustal and Upper Mantle Structure of the Middle East and Southwest Asia for Improved Waveform Simulations Using Openly Available Broadband Data

Here we present a new model of radially anisotropic seismic wavespeeds for the crust and upper mantle of a broad region of the Middle East and Southwest Asia (MESWA) derived from adjoint waveform tomography. The new model enables fully 3D simulations of complete three-component waveforms and provides improved fits that were not possible with previous models. We inverted over 32,000 waveforms from 192 earthquakes recorded by over 1000 openly available broadband seismic stations from permanent and temporary networks in the region with highly uneven coverage. Inversion iterations proceeded from the period band 50–100 s in six stages and 54 total iterations reducing the minimum period to 30 s. Our final model, MESWA, improves waveform fits compared to the starting and other models for both the data used in the inversion and an independent validation set of 66 events. Restitution tests indicate that the model resolves features in the central part of the model to depths of about 150 km. The new model reveals tectonic features imaged by other studies and methods but in a new holistic model of anisotropic shear and compressional wavespeeds (V S and V P , respectively) covering a larger domain with smaller scale length and amplified features. Examples include low crustal V S in the Tethyan belt and low mantle VS following divergent (Gulf of Aden, Red Sea) and transform (Dead Sea fault) margins of the Arabian plate. Low V S is imaged below Cenozoic volcanic centers of the Mecca–Madina–Nafud Line, Arabian Peninsula, and the Türkiye–Iran border region. Elevated V S tracks Makran subduction under southeast Iran with near vertical dip. MESWA could be used as a starting model for further improvements, say, using waveforms from in-country seismic networks that are not currently openly available and/or smaller-scale studies targeting a shorter period. The model could be used to improve earthquake hazard studies and nuclear explosion monitoring.

58 GEOSCIENCES↗

Improved measurements of nonlinear integrable optics at IOTA

Nonlinear integrable optics (NIO) are a promising novel approach at improving the stability of high intensity beams. Implementations of NIO based on specialized magnetic elements are being tested at the Integrable Optics Test Accelerator (IOTA) at Fermilab. One method of verifying proper implementation of these solutions is by measuring the analytic invariants predicted by theory. The initial measurements of nonlinear invariants were performed during IOTA run in 2019/20, however the covid-19 pandemic prevented the full-scale experimental program from being completed. Several important improvements were implemented in IOTA for the 2022/23 run, including the operation at higher beam energy of 150 MeV, improved optics control, and chromaticity correction. This report presents on the improved calibrations of the NIO for nonlinear invariant measurements.

43 PARTICLE ACCELERATORS↗

A low-cost centralized HVAC control system solution for energy savings, load shedding, and improved maintenance

University campuses rely on centralized controls for managing and optimizing complex HVAC systems in larger buildings. However, most campuses also have many smaller buildings with packaged HVAC systems controlled by a stand-alone thermostat. Even when these distributed and often overlooked systems have modern programmable thermostats, they cannot be centrally monitored or controlled, and they are typically not programmed adequately. This paper describes the implementation of a low-cost centralized control solution for these systems serving smaller campus buildings, mostly under 5,000 sf and representative of light commercial spaces. Thanks to advances in technology spurred by residential and commercial IoT developments, simple networked thermostat solutions exist that can easily replace original thermostats, and, connect these systems to a web-based portal for monitoring and control. We show that, with small customizations, these platforms can be integrated into facility management workflows. Beyond the energy savings potential from improved scheduling and closer management of these systems, there are significant advantages for maintenance crews since these systems can now be monitored on smart phones or tablets. A grid-responsive load-shedding program has also been implemented for additional cost savings. The networked thermostats can also be connected to additional systems such as economizer controls for improved ventilation management and energy savings. With data from these systems integrated centrally, it can also be used for improved analytics and fault detection. A toolkit has been developed to share the program with other campuses, whether for energy savings, improved management of ventilation, or a more proactive maintenance approach.

Fauchier-Magnan, Nicolas↗

Evaluation of Steam Cycle Upgrades to Improve the Competitiveness of U.S. Coal Power Plants (Final Scientific / Technical Report)

Increasing the competitiveness of the existing pulverized-coal utility fleet in the United States may be achieved by decreasing heat rate, via increases in steam cycle efficiency through upgraded steam temperatures and use of latest technology available in steam turbine and blading design. The average net plant efficiency of the US coal-fired fleet is approximately 33% (HHV). Plant efficiency increases to approximately 41.4% (HHV) at 1,350°F (732°C) steam temperature. However, achieving these Advanced Ultra-Super Critical (AUSC) steam conditions requires the use of advanced high-temperature materials. While there has been a significant amount of DOE-funded materials R&D, most of the related design work has focused on new (greenfield) units, rather than on opportunities to retrofit this advanced technology to the existing utility fleet. If technology, based upon the advanced materials required for AUSC steam conditions, may be applied to the existing fleet, using an economically viable retrofit, a higher capacity factor can be expected as a result of the increased plant competitiveness. The Electric Power Research Institute (EPRI) was awarded a project by the US Department of Energy to examine the technical and economic feasibility of a series of steam cycle upgrades to the two most prevalent types of U.S. coal power plants: 2,400 psig (16.6 MPa) subcritical and 3,500 psig (24.1 MPa) supercritical pulverized coal units. The nine upgrade options that were originally being considered included increasing the main and reheat steam temperatures from 1,000°F (538°C) to 1,100°, 1,200°, and 1,350°F (593°C, 649°C, and 732°C) while holding the steam pressures constant at their original design values, and cases where just the main steam or reheat steam temperatures were increased. The objective was to minimize the modifications required to the existing power plant while still providing a significant improvement in heat rate. The upgrade options assumed that the boiler enclosure envelope remained unchanged from each base case, and that all applicable OEM design guidelines for normal commercial units were imposed. For the highest temperature supercritical case, an option of using a low-pressure molten salt loop to transfer heat from the furnace to the steam was examined. The first major task of the work scope was designed to examine the technical feasibility of various upgrade options, while the subsequent work determined economic viability of the technically feasible upgrade options. Prior to evaluating the effect of these increased temperatures, a “base case” model of a subcritical and supercritical PC boiler was created, which was used for comparative purposes. Upgrade options were evaluated at full-load, part-load and dynamic transient conditions. Once the technical feasibility of each upgrade option was evaluated, the economic value of the heat rate improvement of each feasible option was determined by detailed modeling of unit dispatch in several regional power markets. The dispatch model was used to estimate the amount of revenue from power sales the upgraded unit would receive in comparison to a non-upgraded version of the same power plant. As a parallel task to the dispatch analysis, the capital cost of implementing the upgrades was estimated. The capital cost estimates were then compared to the increased revenue estimated by the dispatch modeling to determine the economic attractiveness of each upgrade option. Several upgrade options were determined to be technically feasible. The net present value (NPV) of the costs for steam cycle upgrades considered in this study ranged from approximately $\$$111 to $\$$130 million. The economic modeling results show that the unit dispatch changes resulting from steam cycle upgrades are relatively small, due largely to heat rate (and operating cost) changes being relatively small. Additionally, the cost of each upgrade exceeds the net revenue increases associated with the upgrade case. Note that the breakeven values are higher for subcritical retrofits, but the capital costs for the subcritical upgrades are also slightly higher. In typical new pulverized coal plants, fuel accounts for approximately 25% of the cost of electricity (COE), while capital costs represent around 50% of the COE. Therefore, in order to improve the heat rate by 4% one can only afford to increase the capital cost by 2%, at the same cost of electricity. The conclusion of this study is that without a cost for emitting CO 2 , it will be difficult to pay for significant efficiency improvements on plants firing low cost coals.

01 COAL, LIGNITE, AND PEAT↗

Development of Algal Biomass Yield Improvements in an Integrated Process (Final Report)

This project built on the success of Global Algae Innovations Algae Biomass Yield Phase 1 project to accelerate the commercialization of algal biofuels through development of an integrated, economical, photosynthetic, open raceway system to produce algal oil. Two parallel pathways to a biofuel were investigated. In the algal crude oil pathway, highlighted in blue, the dewatered algal biomass slurry is used as a feed to hydrothermal liquefaction to produce an algae crude oil and recycle aqueous stream. In the algal lipid oil pathway, highlighted in green, the algal biomass slurry is dried, and the oil is extracted to produce an algal lipid oil biofuel intermediate and a high protein algae meal co-product. Upgrading to drop-in fuels has been demonstrated for the biofuel intermediates in both pathways. Since the algal lipid oil pathway requires lipid accumulation, the productivity is generally lower than the algal crude oil pathway, but the required productivity for economical algal biofuel production is also lower because the coproduct value is greater. The outdoor cultivation was performed at the Kauai Algae Farm. The project team has expertise across the full breadth strain development, advanced algal cultivation, open raceway contamination control, CO 2 supply, harvesting, dewatering, extraction, hydrothermal liquefaction, technoeconomic analysis and life cycle analysis: Hildebrand laboratory at Scripps Institution of Oceanography – diatom strain development. Mayfield laboratory at UCSD - green algae strain development. TSD Management Associates- CO 2 supply, algal harvesting and dewatering, and algal drying and extraction. Qualitas - large-scale test site for algal harvesting technology. Texas A&M University - algal drying and extraction technology. Pacific Northwest National Laboratory - hydrothermal liquefaction technology. GE Water and Power - membrane technology. National Renewable Energy Laboratory - algal techno-economic analysis. Phase 1 of the project resulted in tremendous productivity and pre-processing improvements in an integrated, large-scale, low-cost cultivation and pre-processing process that moved algal technology closer to economic viability for biofuels than ever before. Phase 2 accomplishments further facilitate development of a commercial algal biofuel industry by adding: several top performing strains and strain development tools including breeding; open-pond cultivation innovations that achieved a 30% improvement in overall productivity, an 83% reduction in cost, and a 95% reduction in energy use relative to conventional technology; further improvements in harvesting that led to the Zobi harvester ® as a universal, economical, low energy, commercially available microalgae harvesting solution; breakthroughs in drying and extraction including a new low energy drying process and several new low energy extraction unit operations that together with the Zobi harvester ® achieve a 90% reduction in cost and 97% reduction in energy use relative to conventional technology. These improvements are sufficient to enable economical production of algae biofuel and protein meal co-product if the process were scaled up to a commercial-scale 5,000-acre algae farm.

09 BIOMASS FUELS↗

Improving energy yield in photovoltaic modules with photonic structures

When installed outdoors, Si solar cells typically operate 20 – 30 K above ambient conditions. These elevated operating temperatures lead to diminished performance, reducing efficiency by ~0.4%/K for crystalline Si cells and decreasing module lifetime. Since much of the elevated temperature of the modules derives from parasitic absorption of sub-bandgap sunlight by the contacts, encapsulants, or other materials, reflectors that remove the sub-bandgap radiation from the module before it is absorbed promise to reduce the operating temperature. However, there are many competing strategies to reject this light: selective reflectors could be integrated into the outer module glass, at the textured Si-encapsulant interface, or on the rear. Furthermore, many of these approaches are complex and expensive to fabricate. The issue of heating can be even more critical in bifacial modules: high fractions of rear irradiance can lead to higher operating temperatures. Prior to this project, relatively little was known about the optical strategies for temperature reduction in bifacial modules. The goal of this project was to quantitatively assess optical strategies for improving the energy yield via a combination of improved anti-reflection and sub-bandgap light rejection. We studied two complementary concepts: the performance of ideal structures to determine the upper limits to performance, and low-complexity structures made from standard materials as cost-effective implementations. We also studied the performance of these reflectors in different types of modules, including Al BSF, PERC, and bifacial. Here we build from our prior accomplishments in developing mirror optimization techniques, and make use of simulation methods that accurately capture the optical properties of the modules throughout the visible and near-infrared spectrum. We connect these optical properties to energy yield under realistic, outdoor conditions. We also experimentally fabricated mirrors, incorporated them into mini-modules, and performed outdoor testing of performance at NREL. We found definitively that spectrally-selective mirrors on the outside of the module cover glass offer the best performance, both under ideal conditions and for realistic, low- complexity mirrors. Mirrors at the Si cell/encapsulant interface are limited by the multiple reflections needed to remove sub-bandgap light. Mirrors at the cell surface and mirrors on the rear also cannot remove all the sub-bandgap light, since parasitic absorption also occurs in the cover glass, encapsulant, and front contacts, depending on the module configuration. Also, cell texturing places higher demands on any cell-surface mirror because multiple interactions with the mirror are required to reject sub bandgap light which compounds losses. For bifacial modules, mirrors on the back do provide additional cooling and energy yield improvements, and the mirrors can have the same structure. In the monofacial case up to 3.3K of cooling is possible for mirrors on the front, compared to 2.2K at the cell surface and 1.2K at the rear. For bifacial modules, up to 2.4K of cooling is possible when mirrors are included at both the front and back. Our realistic designs utilize 4 – 6 layers of common photovoltaic materials such as SiO 2 , TiO 2 , and SiN x , making them more cost effective. Finally, we used our models to study thermal management in bifacial modules with different back lamination materials, finding that glass-glass laminated modules operated hotter than equivalent glass-polymer backsheet modules, due solely to the increased absorption of light incident from the rear of the module. Improving the energy yield by 2%, which is achievable with these realistic designs, would lead to LCOE reductions of $0.03/kWh by 2030. These benefits make photovoltaic panels more accessible to the public and may reduce associated maintenance costs.

14 SOLAR ENERGY↗

Improving solar panel durability through novel panel designs and advanced manufacturing equipment

Work in the project was spread across 4 main themes:1) Improved Understanding of Why Cracks Form and Cause Degradation in Solar Cells: We developed a finite element model which correlated well with experimental determined deflection vs load profiles and which predicted stress profiles vs load level and temperature. These profiles helped to guide brace designs and showed the high stress levels seen in the silicon near the interconnect wire locations as the temperature is cooled below -30C, likely forming "invisible" microcracks. Experiments showed how for polymer backsheet modules, a brief exposure to such low temperatures made modules extremely sensitive to propagation of these microcracks at relatively low load levels, and how thicker and softer encapsulant helped to reduce this crack sensitivity. We showed for some modules that most cracks that are seen under loading had their origin at short, hard to see, V-cracks from soldering damage, and how the shunting from cells with high densities of cracks reduces energy delivery more than Pmax. 2) Improved Durability Testing Methods With Respect to Cracked Cells: We lobbied the PV community throughout the project that IEC 61215 was insufficient to probe the sensitivity of module Pmax degradation due to cracks in that in did not have a test leg that included a crack creation step (static loading) followed by a crack opening step (cyclic loading and/or thermal cycling). We published extensively on how pre- existing cracks opened up with cyclic loading. The new IEC TS 63209-1 ED1 test sequence now include our recommendations, and this should lead to improved module designs and reduced risk for investors. We also published recommendations for a new "Cold Climate Test" sequence to probe the sensitivity of modules to degradation from short microcracks formed when modules see temperatures below -30C followed by front side loading. We participated in several USTAG meetings related to cracked cells, EL testing, and mechanical load testing and provided input to the group to improve new standards under consideration. We also showed how the act of performing an EL test can affect the test results due to heating from the injected current. 3) New Module Designs and Related Manufacturing Methods & Equipment: We demonstrated reduced crack sensitivity on encapsulated cell coupons the benefits of building protective compressive stress into the cells by laminating them in a bent state and then allowing the coupon to flatten out after lamination. Our attempts to scale this to the module level with a more manufacturable sequence did not demonstrate the same positive effects, but we hope that others will follow up with other variations on this bent lamination or bent cooling concept to make more durable modules. 4) New Module Mounting Designs: We explored a range of bracing concepts which pressed on the backsheet to slightly bow the glass outward and place cells in a state of protective compressive stress and to reduce the deflection under front side loads. These successfully reduced cell cracking and crack opening, but high static loads permanently deformed cost-effective braces, after which they provided little benefit. We settled on an elegant & effective solution – the RailPad, where lightweight bracing elements are placed between the mounting rail(s) and the backsheet, and the existing strength of the rails is used to prevent module deflection under load. New construction and retrofit designs were made, and test sites were implemented in FL and MA. We applied for RailPad patent protection.

14 SOLAR ENERGY↗

United States Department of Energy Sandia Natinoal Laboratories, California Arroyo Seco Improvement Program (Annual Report for 2021)

The Arroyo Seco Improvement Program (ASIP) is intended to provide active channel improvements and stream zone management activities that will reduce current flood and erosion risk while providing additional and improved habitat for critical species that may use the Arroyo Seco at the United States Department of Energy (DOE), Sandia National Laboratories, California (SNL/CA) location. The objectives of the ASIP are: correct existing channel stability problems associated with existing arroyo structures (i.e. bridges, security grates, utility crossings, and drain structures), correct bank erosion and provide protection against future erosion, reduce the risk of future flooding, and provide habitat improvement and creation of a mitigation credit for site development and management activities.

54 ENVIRONMENTAL SCIENCES↗

Solutions for Enhanced Legacy Probabilistic Risk Assessment Tools and Methodologies: Improving Efficiency of Model Development and Processing via Innovative Human Reliability Dependency Analysis

Probabilistic risk assessments (PRAs) are integral to nuclear power plant (NPP) operations, having tremendously benefitted the safety of the U.S. reactor fleet for decades. Insights obtained from the models have provided perspectives on a variety of applications, both at the plant and for the regulator. While these models are very useful, they are now being asked to represent and analyze aspects of the plant that were never envisioned by the initial PRA practitioners. Furthermore, heightened demands on the PRA models have led to increased computing power requirements. Additionally, as the complexity of the PRA models increased, the difficulty experienced by non-PRA experts in trying to understand these models, grasp the insights they provide, and effectively use that information has become problematic. The need for research to address key issues regarding PRA tools and methods has never been greater. Although the nuclear power industry has largely been well-served by these tools and methods, the underlying science is dated, remaining mostly unchanged for over two decades. Three areas were identified as most beneficial to address to maintain and improve the usefulness of the current practice legacy PRA tools: improved quantification speed, increased ability to efficiently model multi-hazard models, and improved modeling human action dependency in PRA. This report is focused on the third critical area, improvements in dependency analysis of human actions conducted as part of a typical human reliability assessment.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Understanding and Improving Energy Efficiency of Regional Mobility Systems Leveraging System-Level Data

Increased congestion required urban Americans to travel 6.8 billion hours more and purchase 3.1 billion gallons of fuel for a congestion cost of $\$$153 billion, according to the 2019 Urban Mobility Report. How to effectively manage the regional mobility system and improve the energy efficiency presents a big challenge to public agencies. Recent years have witnessed massive multi-jurisdictional multi-modal system-level data from various sources, which provides an unprecedented opportunity to improve the mobility system and its energy efficiency. However, implications of system-level data for mobility and energy efficiency are unclear. Those system-level data sets are siloed, spatially and temporally sparse, biased, not unified, and lacking of insights for system management. Consequently, there is a real need to acquire, fuse, mine and learn from multi-source system-level data to prepare public agencies to deal more effectively with large-scale energy efficiency modeling, management and planning. This project proposes to intensively review inexpensive, replicable and openly-accessible data from multi-modal systems, develop a data-driven system-level modeling framework enabled and validated by data, identify the energy inefficiencies of mobility systems from infrastructure, vehicles, passenger systems, and quantify the benefits of system-level strategies to improve mobility/energy efficiency. In addition, this research develops models to effectively estimate energy consumption and emissions from various types of vehicles on the roadway networks, with high granularity and high fidelity. Traditional models often heavily rely on aggregated infrastructure or vehicle/passenger data, for example, the census survey, land-use, and traffic counts of one or several classes, which may lead to research gaps considering the emerging vehicle technologies. Those models do not contain individual vehicular information. We propose an integrated data-driven method that combines multiple network modeling components, featuring the utilization of state-wide vehicle registration data. The additional vehicle registration data improve the model performance, and produce high-resolution vehicle-specific estimates of emissions and network performance metrics. Two case studies on the Pittsburgh and Philadelphia regional network show that the proposed method can efficiently and effectively estimate the emissions of a large-scale network, and provide valuable information for evaluating common management strategies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗