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At least 1,135 records · Page 63

Development Of Nutrient And Water Recycling Capabilities In Algae Biofuels Production Systems. Final Summary Report

The objective of this project was to develop and demonstrate methods of recycling of water and nutrients for algal biofuels production. Recycling was accomplished both internal to the system and, in a broader sense, through import and reuse of municipal wastewater. Such an integrated system with wastewater input had not been demonstrated previously, and the performance was unknown, particularly in terms of influence of recycling on algal productivity and the practical extent of nutrient recovery from biomass residuals. Through long-term laboratory and pilot research, the project resulted in the following: 1. Bench-scale pretreatment of algal biomass did not sufficiently increase methane yield of nutrient solubilization during anaerobic digestion to warrant incorporation of pre-treatment into the pilot plant. The trial pretreatments were high-pressure orifice homogenization, sonication, and two types of heat treatment. 2. Solubilization of biomass particulate nutrients by lab anaerobic digesters ranged from 20% to nearly 60% for N and 40-65% for P. Subsequent aerobic degradation of the anaerobically digested biomass simulated raceways receiving whole digestate and resulted in an additional 20-55% N solubilization and additional 20% P solubilization. 3. Comparisons of laboratory and pilot digesters showed that laboratory units were reasonable proxies for pilot-scale. 4. Pilot-scale anaerobic digesters were designed, installed, and operated to digest algal biomass. Nutrient re-solubilization by the digesters was monitored and whole digestate was successfully used as a fertilizer in pilot algae raceways. 5. Unheated, unmixed digesters achieved greater methane yield and nutrient solubilization than heated, mixed digesters, presumably due to longer the solids residence times in unmixed digesters. The unmixed, unheated pilot digesters yielded 0.16 L CH4 /g volatile solids (VS) introduced with 0.15 g VS/L-d organic loading and 16oC average temperature. A conventional heated mixed lab digester yielded 0.22 L CH4 /g VS with 0.25 g VS/L-d and 30oC. The highest yield (0.30 L CH4 /g VS) was achieved by the unmixed lab digesters operated at a constant 20oC. All digesters were operated with a 40-d hydraulic residence time. 6. In general, 50-75% of initial particulate N and P could be solubilized during anaerobic digestion and available for subsequent rounds of algae cultivation. 7. Bench-scale experiments showed the recovery from hydrothermal liquefaction (HTL) wastewater of carbon via anaerobic digestion and of nutrients to grow algae. To satisfy the nitrogen demand of algae cultivation, HTL wastewater would be diluted 400-fold, which was found to eliminate inhibition of algae growth by HTL wastewater. 8. Anaerobic digestion methane yield was lower for algal biomass containing coagulants such as would be used to aid harvesting or dewatering. Depending on doses, starch-based coagulant decreased yield by 10-14% and aluminum chlorohydrate decreased it by 14-26%. The lowest yield was 0.28 L CH 4 /g volatile solids introduced to the digesters. 9. Algae harvested from raceways operated on recycled water had methane yields 13% higher than algae from raceways operated on both recycled water and nutrients provided by algae digestate. The slightly lower yield was expected due to the presence of previously digested biomass from the digestate fertilizer. 10. Defined media was replenished with nutrients and recycled repeatedly in sequential batch growth of Chlorella sorokiniana (DOE 1412). This laboratory study tested for inhibition and accumulation of inhibiting compounds (allelopathic or auto-inhibitory substances), information that would help estimate the blowdown ratio needed for an integrated system. In laboratory experiments in which water was recycled a total of five times, each successive round of reuse resulted in an average 4±3% reduction in log-phase specific growth rates. However, linear-phase growth inhibition was only observed in the final fifth round of reuse. 11. No decline in productivity was detected after 15 rounds of water recycling with nutrients provided by whole digestate in lab cultivation. Lab tests allowed for steady light and temperature, increasing the ability to detect inhibition. 12. In initial pilot inhibition studies, wastewater growth media was reused once while productivity was monitored. Media reuse was accomplished with triplicate sets of 33-m2 raceways operated in series. First-round gross productivity (based on effluent biomass flow) averaged 23 g/m 2 -day annually while second-round gross productivity averaged 19 g/m 2 -day annually. In terms of net productivity (based on raceway effluent biomass minus influent biomass), the first-round productivity averaged 15 g/m2-d and second round averaged 13 g/m 2 -d during June-September operation. The higher productivity in the first-round ponds was likely due to heterotrophic/mixotrophic growth on the wastewater organic matter. 13. In a culminating pilot experiment, coagulant was used to decrease the carry-over of unsettled algae into subsequent rounds of growth. Over nearly 8 months, 93% of the media (the equivalent of 14 rounds of water reuse) was recycled without significant productivity loss compared to controls. Ponds receiving both recycled water and nutrients had net productivities of 14-24 g/m 2 -d during fall and mid-summer, respectively. 14. Techno-economic analysis of the proposed facility found minimum fuel selling price to range from $7.01/gallon gasoline equivalent without revenue other than fuel to $3.85/GGE with revenue from wastewater treatment fees and LCFS and RIN (Low Carbon Fuel Standard and Renewable Identification Numbers) credits. 15. Life cycle assessment indicated GHG emissions of 40.7 g CO 2 /MJ fuel and a net energy ratio (energy required/energy produced) of 0.37.

09 BIOMASS FUELS↗

Methodology to Calculate the ACE and HPQ Metrics Used in the Wave Energy Prize

The U.S. Department of Energy's Wave Energy Prize Competition encouraged the development of innovative deep-water wave energy conversion technologies that at least doubled device performance above the 2014 state of the art. Because levelized cost of energy (LCOE) metrics are challenging to apply equitably to new technologies where significant uncertainty exists in design and operation, the prize technical team developed a reduced metric as proxy for LCOE, which provides an equitable comparison of low technology readiness level wave energy converter (WEC) concepts. The metric is called 'ACE' which is short for the ratio of the average climate capture width to the characteristic capital expenditure. The methodology and application of the ACE metric used to evaluate the performance of the technologies that competed in the Wave Energy Prize are explained in this report.

17 WIND ENERGY↗

A Scaling Study of Microbially-Enhanced Methane Production From Coal (Mecbm): Optimizing Nutrient Delivery For Maximized Methane Production

Microbially-enhanced coalbed methane (MECBM) recovery is a novel method to stimulate gas production in CBM reservoirs. We first develop suitable nutrient recipes for native coals from sites each in the Illinois Basin and in the San Juan Basin. The optimal concentrations for statistically significant parameters are identified and the methane yields at laboratory scale are obtained (Part I & II). We then demonstrate the importance of replicating truly in-situ conditions for bio- gasification studies by investigating methane productivity in a core holder simulating in-situ conditions. Based on the experimental results, the resulting gas production correlates positively with the permeability of the samples. We examine the deliverability of engineered microbial solutions to promote coal bioconversion in coals and demonstrate that greater than milli-darcy permeability is required under in-situ stress conditions (Part III). This constraint is supplemented by imaging and a fractal-based characterization approach to evaluate changes in the physical properties of coal due to bio-gasification. High resolution SEM imaging is used to observe swelling of the coal matrix with sub-micron wide continuous pores observed to persist even after microbial treatment (IV). We explore the potential of generating, propping-open and sustaining the functionality of hydraulic fractures in coal using different fracturing fluids (Part V). The alteration of the nano-pore structure due to MECBM treatment is examined by using small angle X-ray scattering (SAXS) to define the in-situ porosity evolution as a proxy to infer permeability evolution (Part VI). Coupled hydro-mechanical and bio-gasification modeling is applied to determine the effectiveness of nutrient delivery by hydraulic fracturing and its field implementation. Compared with both the unstimulated and hydro-shear-dilated cases of the natural fracture network, hydraulic fracturing demonstrates a significant improvement to enhance nutrient delivery. A preliminary analysis of field-scale methane yield is completed with consideration of the combined influence of permeability evolution, solute transport and microbial growth (Part VII). Developing nutrient solutions for Illinois Basin and San Juan Basin (Task 2): To enhance methane release from coal through bio-gasification, suitable nutrient solutions are needed to stimulate microbial activities toward coal depolymerization and conversion to biogas. Specific for bituminous coal in the Illinois basin, a nutrient recipe that can be used to enhance coal bio- gasification in situ is developed. Based on our previous experience working with Illinois coal and the characteristics of the formation water and the indigenous microbial community, four parameters, Fe powder, methanol, ethanol, and trace minerals are optimized through using a Box-Behnken design. The optimal condition predicted by the models is: Fe-powder at 74 mM, methanol at 97.91 mM, ethanol at 100 mM, and trace minerals at 100%. Under these conditions, the predicted methane yield and content is 1,417.35 ft 3 /ton and 80.7%, respectively. These results are then validated by experimental studies. In addition, each added component is evaluated in terms of its contribution to methane generated. Specifically, the role of coal in the bio-gasification process is studied against two other solid materials. Experimental data from different solid matrices prove that coal is indeed degraded by the studied microbial community.

01 COAL, LIGNITE, AND PEAT↗

Kokkos R&D: Remote Memory Spaces WBS STPR 04 Milestone 7

This report documents the completion of milestone STPRO4-7 Kokkos R&D: Remote Memory Spaces for One-Sided Halo-Exchange. The goal of this milestone was to develop and deploy an initial capability to support PGAS like communication models integrated into Kokkos via Remote Memory Spaces. The team developed semantic requirements for Remote Memory Spaces and implemented a prototype library leveraging four different communication libraries: libQUO, SHMEM, MPI-OneSided and NVSHMEM. In conjunction with ADCD02-COPA the Remote Memory Space capability was used in ExaMiniMD — a Molecular Dynamics Proxy Application — to explore the current state of the technology and its usability. The obtained results demonstrate that usability is very good, allowing a significant simplification communication routines, but performance is still lacking.

97 MATHEMATICS AND COMPUTING↗

ECP STPR04 Milestone 5 Report

This report documents the completion of milestone STPRO4-5 Kokkos interoperability with general SIMD types to force vectorization on ATS-1. The Kokkos team worked with application developers to enable the utilization of SIMD intrinsics, which allowed up to 3.7x improvement of the affected kernels on ATS-1 in a proxy application. SIMD types are now deployed in the production code base.

97 MATHEMATICS AND COMPUTING↗

Neural Networks as Surrogates of Nonlinear High-Dimensional Parameter-to-Prediction Maps.

We present a preliminary investigation of the use of Multi-Layer Perceptrons (MLP) and Recurrent Neural Networks (RNNs) as surrogates of parameter-to-prediction maps of com- putational expensive dynamical models. In particular, we target the approximation of Quan- tities of Interest (QoIs) derived from the solution of a Partial Differential Equations (PDEs) at different time instants. In order to limit the scope of our study while targeting a rele- vant application, we focus on the problem of computing variations in the ice sheets mass (our QoI), which is a proxy for global mean sea-level changes. We present a number of neural network formulations and compare their performance with that of Polynomial Chaos Expansions (PCE) constructed on the same data.

97 MATHEMATICS AND COMPUTING↗

Examining Efficacy of Strategic Stability in South Asia: An Analysis

This paper highlights how, in the backdrop of prevalent tensions between India and Pakistan, deterrence stability is endangered even when overall strategic stability prevails. Unresolved legacy issues including an outstanding boundary dispute, conflict over Kashmir, and terrorism mar India-Pakistan relations. Variables undermining the prospects for long term peace, among others, include growing mutual mistrust, the proxy war that India believes is state perpetrated, increasing conventional asymmetry, rapid advancement in weapon technologies, growing size of nuclear arsenals, doctrinal mismatch and above all, bilateral gridlock in confidence building measures and arms control measures.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

The Russian Model of Internet Control and Its Significance

Russia has emerged as an exemplar of an innovative and experimental – though not always completely consistent or successful – alternative approach to information manipulation and control that differs significantly from the more-often discussed Chinese “Great Firewall” system and other approaches with an emphasis on systemic technical censorship. The Russian model relies on a mix of less overt, more plausibly deniable, legalistic, and often non-technical mechanisms to manipulate online information flows, narratives, and framings, to affect and shape public opinion without resort to universal censorship. The government uses surveillance, a panoply of vague laws, the prosecution or censorship of exemplars, proxy actors and hard to track extra-legal pressures, hacking and leaks, and a heavy emphasis on content production and manipulation to influence narratives and shape public opinion. This model for the domestic control of information not only fits with Russia’s own political system, but is likely to prove more resonant and easier to emulate across many other countries in which a systematic-censorship approach is not technologically or politically feasible. The learning and experimentation involved in this type of domestic information manipulation also has direct applicability to the use of information operations in international political and military competition. The future of this model will likely depend on continuing innovation, not least on the leveraging of advances in artificial intelligence and big data analysis. If successful, however, this might look very different from the future of information control in China – and have significantly different repercussions for democracies and the international system.

97 MATHEMATICS AND COMPUTING↗

Model-Data Fusion Approaches for Retrospective and Predictive Assessment of the Pan-Arctic Scale Permafrost Carbon Feedback to Global Climate

Policy decisions regarding climate change mitigation and adaptation rely on having reliable projections of future climate change. Coupled climate-carbon models predict that the northern high latitudes will serve as a substantial land carbon sink during the 21stcentury, but these models lack many of the key processes governing high-latitude ecosystem processes. Arctic tundra and boreal forests are unique from other biomes particularly because of the presence of snow, ice and frozen ground, and it is important to understand the mechanisms that drive interconnected processes in these landscapes. Increasing our confidence in climate projections requires an integrated approach where existing, on-going and planned observational and experimental studies of high-latitude ecosystem processes are organized and analyzed in a framework designed to target improvements in understanding key ecosystem-climate feedbacks. For this project we designed an approach to improve our scientific understanding of the permafrost carbon feedback through broad-scale assessment of the drivers and responses of the Arctic system carbon cycle using data-driven models of simple-to-intermediate complexity. The made a valuable contribution to the first of its kind, data-driven quantitative assessment of the impact of permafrost thaw on pan-Arctic scale carbon cycle feedbacks to the global climate system. The approach drew on a conceptual framework for integrating the key system components and their underlying data within a “book-keeping” framework for assessment of the key processes driving the permafrost carbon feedback. The results provided quantitative model-data benchmarking to constrain future projections of carbon cycle responses to a warming Arctic. The framework used environmental proxy data sets examining recent-era geomorphologic land-form transitions and vegetation dynamics, through remotely-sensed data, to guide the extrapolation of site-based data on the key system components to larger regions. These products contribute to the development of finer-scale, more complex representation of permafrost carbon processes in terrestrial biogeochemistry models, to operate within coupled Earth system modeling frameworks.

54 ENVIRONMENTAL SCIENCES↗

Final Technical Report

This proposal work was meant to investigate the role of the coupling between the biosphere and the atmosphere using a combination of theoretical modeling, high-resolution cloud resolving models and remote sensing observations (in particular of solar-induced fluorescence - a proxy for photosynthesis).

54 ENVIRONMENTAL SCIENCES↗

Rapid Development of Hybrid Perovskites and Novel Tandem Architectures

Multijunction solar cells based on epitaxially grown III-V materials hold the record for solar energy power conversion efficiency (PCE). However, due to the high cost of fabricating these devices, they are typically only used for concentrator cells and space applications. The overarching goal of this project was to develop low-cost printable hybrid perovskite (HP) materials appropriate and optimized for tandem solar cells with high power conversion efficiency under “1 Sun” illumination. Key results and findings over the course of the project we: Developed higher-performance high-bandgap (1.75 eV) perovskite materials and devices. In particular, we explored tens-of-thousands of compositions for high bandgap perovskites, achieving quasi-Fermi level splitting of 1.35 eV for a 1.75 eV bandgap material. We achieved World-record open circuit voltages from single junction p-i-n devices, 1.24 V from 1.75 eV bandgap material, which is what is preferable for tandems with a PCE of 14.3% using a guanidinium/formanadinium/ cesium alloyed lead iodobromide. We also developed a series of World-record efficiency devices at higher band-gaps based on 2D/3D perovskites using PEA. Developed higher-performance low-bandgap (1.35 eV) perovskite materials and devices. In particular, we developed a 1.35 eV bandgap perovskite of composition MAPb0.5Sn0.5(I0.8Br0.2)3 and showed its superiority to MAPb0.75Sn0.25I3. High efficiency solar cells were fabricated using PEDOT:PSS and doped-ICBA as HTL and ETL, respectively. Short circuit currents of 25.7 mA/cm2 and PCEs of 17.1% were obtained. Developed mechanically stacked 4-terminal CIGS-Perovskite tandems with PCE of 18.8% and monolithic 2-terminal CIGS-Perovskite tandems with PCE of 8.5%. The low efficiency of the monolithic device is a result of the high surface roughness of the solution processed CIGS bottom cells. This is not an intrinsic problem for CIGS-perovskite tandems, but does mean that smooth evaporated or sputtered CIGS films likely need to be used, unless a polishing step is employed. Developed monolithic 2-terminal Perovskite-Perovskite tandems with a stabilized PCE of 18.5%. This was the World-record perovskite-perovskite monolithic tandems for over a year in 2017-2018. Revealed that light is not an essential component of the so-called “light-induced” phase segregation. By using charge injection in the dark and electroluminescence, we showed that the presence of electrons in the conduction band and hole in the valence band is sufficient to drive the nearly ubiquitously observed phase segregation in high bandgap perovskites. Developed a new method to simultaneously measure absolute intensity photoluminescence and photoconductivity and use them to obtain simultaneous in-situ measurement of quasi-Fermi level splitting and diffusion length. This is important since it provides a proxy for device Voc and device Jsc. In addition, 67 papers were published with support from this award that detail many more advances in the field, including numerous publications in high impact journals such as Nature Photonics, Advanced Materials, ACS Energy Letters, and Energy and Environmental Science.

14 SOLAR ENERGY↗

Neural Networks as Surrogates of Nonlinear High-Dimensional Parameter-to-Prediction Maps

We present a preliminary investigation of the use of Multi-Layer Perceptrons (MLP) and Recurrent Neural Networks (RNNs) as surrogates of parameter-to-prediction maps of computational expensive dynamical models. In particular, we target the approximation of Quantities of Interest (QoIs) derived from the solution of a Partial Differential Equations (PDEs) at different time instants. In order to limit the scope of our study while targeting a relevant application, we focus on the problem of computing variations in the ice sheets mass (our QoI), which is a proxy for global mean sea-level changes. We present a number of neural network formulations and compare their performance with that of Polynomial Chaos Expansions (PCE) constructed on the same data.

97 MATHEMATICS AND COMPUTING↗

XVis: Visualization for the Extreme-Scale Scientific Computation Ecosystem (Final Report)

Scientific computing is no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. The XVis project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressing four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis. This report reviews the accomplishments of the XVis project to prepare scientific visualization for Exascale computing.

97 MATHEMATICS AND COMPUTING↗

Compare linear-system solver and preconditioner stacks with emphasis on GPU performance and propose phase-2 NGP solver development pathway

The goal of the ExaWind project is to enable predictive simulations of wind farms comprised of many megawatt-scale turbines situated in complex terrain. Predictive simulations will require computational fluid dynamics (CFD) simulations for which the mesh resolves the geometry of the turbines and captures the rotation and large deflections of blades. Whereas such simulations for a single turbine are arguably petascale class, multi-turbine wind farm simulations will require exascale-class resources. The primary physics codes in the ExaWind project are Nalu-Wind, which is an unstructured-grid solver for the acoustically incompressible Navier-Stokes equations, and OpenFAST, which is a whole-turbine simulation code. The Nalu-Wind model consists of the mass-continuity Poisson-type equation for pressure and a momentum equation for the velocity. For such modeling approaches, simulation times are dominated by linear-system setup and solution for the continuity and momentum systems. For the ExaWind challenge problem, the moving meshes greatly affect overall solver costs as reinitialization of matrices and recomputation of preconditioners is required at every time step. In this report we evaluated GPU-performance baselines for the linear solvers in the Trilinos and hypre solver stacks using two representative Nalu-Wind simulations: an atmospheric boundary layer precursor simulation on a structured mesh, and a fixed-wing simulation using unstructured overset meshes. Both strong-scaling and weak-scaling experiments were conducted on the OLCF supercomputer Summit and similar proxy clusters. We focused on the performance of multi-threaded Gauss-Seidel and two-stage Gauss-Seidel that are extensions of classical Gauss-Seidel; of one-reduce GMRES, a communication-reducing variant of the Krylov GMRES; and algebraic multigrid methods that incorporate the afore-mentioned methods. The team has established that AMG methods are capable of solving linear systems arising from the fixed-wing overset meshes on CPU, a critical intermediate result for ExaWind FY20 Q3 and Q4 milestones. For the fixed-wing strong-scaling study (model with 3M grid-points), the team identified that Nalu-Wind simulations with the new Trilinos and hypre solvers scale to modest GPU counts, maintaining above 70% efficiency up to 6 GPUs. However, there still remain significant bottlenecks to performance: matrix assembly (hypre), AMG setup (hypre and Trilinos) In the weak-scaling experiments (going from 0.4M to 211M gridpoints), it's shown that the solver apply phases are faster on GPUs, but that Nalu-Wind simulation times grow, primarily due to the multigrid-setup process. Finally, based on the report outcomes, we propose a linear solver path-forward for the remainder of the ExaWind project. Near term, the NREL team will continue their work on GPU-based linear-system assembly. They will also investigate how the use of alternatives to the NVIDIA UVM (unified virtual memory) paradigm affects performance. Longer term, the NREL team will evaluate algorithmic performance on other types of accelerators and merge their improvements back to the main hypre repository branch. Near term, the Trilinos team will address performance bottlenecks identified in this milestone, such as implementing a GPU-based segregated momentum solve and reusing matrix graphs across linear-system assembly phases. Longer term, the Trilinos team will do detailed analysis and optimization of multigrid setup.

17 WIND ENERGY↗

Evaluation and improvement of the parameterization of aerosol hygroscopicity in global climate models using in-situ surface measurements (Final Report)

Aerosols are tiny particles suspended on the atmosphere that can interact with incoming solar radiation and affect the Earth radiative budget. They do so by scattering and absorbing solar radiation, and these properties vary depending on the aerosol size and chemical composition. Moreover, by taking up water from the surrounding air, hygroscopic aerosol particles will grow in size and change their chemical composition, thus modifying their optical properties (scattering and absorption) and their final impact on radiative forcing calculations. An accurate knowledge of aerosol hygroscopicity is crucial for estimating the net radiative impact of aerosols. We took a three-pronged approach to improve our understanding of aerosol hygroscopicity and how it is implemented in Earth system models. In the first part of our project, we developed a benchmark dataset from existing aerosol hygroscopic growth measurements made by tandem nephelometer humidogram systems. We analyzed, using a standardized methodology, observations from 26 in-situ stations around the globe. Measurement data was collected from multiple data providers, reviewed and harmonized to create a consistent dataset of the scattering enhancement factor due to aerosol water uptake. This dataset is archived in several publicly available databases for use by interested researchers. In the second part of the project, we used the benchmark hygroscopicity dataset to perform a global study on aerosol hygroscopicity and aerosol optical properties. Measurements show a global picture of scattering enhancement with larger values for Arctic and marine sites and lower for urban and desert sites. We assessed the RH dependence of aerosol radiative forcing and showed that the overall effect of aerosol hygroscopicity on DARF is an increase in the absolute forcing effect (negative sign) by a factor of up to 4 compared to dry conditions (RH<40%). Finally, we explored using aerosol single scattering albedo (SSA) and scattering Angstrom exponent (SAE) as possible proxies for aerosol hygroscopicity. SSA showed more promise as a surrogate for the scattering enhancement factor than SAE, but neither was ideal. In the third part of the project we evaluated the output of ten Earth system models (ESMs) against the benchmark hygroscopicity dataset. ESMs utilize various schemes for aerosol hygroscopicity which had not been previously tested against observations on a global scale. We found that ESMs currently overestimate scattering enhancement due to hygroscopic growth. Model parameterizations of hygroscopicity and model chemistry are two main factors driving the observed diversity in hygroscopicity simulations among the models. In addition, our study makes several suggestions for modelers, including improving the parameterizations of organic and sea salt aerosol hygroscopicity. Future hygroscopicity model evaluation experiments should include the model data related to particles size which was not available for our study.

54 ENVIRONMENTAL SCIENCES↗

Fleet-wide Electrification Impacts Assessment for the Valley Transportation Authority

This report explores the long-term electrification opportunities for the Valley Transit Authority’s (VTA) transit bus fleet. The potential for transit bus electrification at VTA as well as the economic impacts of partial and complete electrification are explored. We use the Revenue Operation and Device Optimization model to determine the optimal charging, operation and lowest capital and operating cost solution to achieve different levels of electrification to meet their existing routes. This study finds that, relying on only depot charging, around 70% of the daily trips by VTA’s transit bus fleet can be replaced with battery electric buses (BEBs) today. The benefits and drawbacks of five methods for improving the electrification potential beyond that achievable with only depot charging are discussed including (1) increase charger power, (2) purchase of larger vehicle batteries, (3) en-route charging, (4) purchasing additional buses and swapping them to enable the existing routes/blocks1 to be met, and (5) route/block redesign. A strategy is developed to enable full fleet electrification by increasing charger power or allowing intraday charging as a proxy for the options mentioned above. This method allows us to develop an understanding of the impacts and trade-offs of full fleet electrification. Two charging strategies are examined. Immediate charging, when the bus is charged as soon as it arrives at a depot or en-route charging station, and smart charging, which uses a controller to determine the best times to charge to achieve the lowest charging cost, while maintaining the same trip schedules. Smart charging is effective at reducing the peak power consumption, which can be reduced by between 31% and 65% compared to immediate charging. This translates directly to lower electricity demand charges and lower costs for possible distribution system upgrades. The total lifetime net present value (NPV) costs for different scenarios are presented in Figure ES-1. Scenarios are separated into three sections. The first stacked bar on the left is the base case (business-as-usual) where all buses are diesel hybrids, the next four bars include partial and full fleet electrification utilizing only immediate charging, and the last four bars include partial and full fleet electrification utilizing smart charging. The results show that smart charging scenarios are within ±4% of the lifetime NPV cost of the diesel-hybrid only (business-as-usual) scenario. The scenarios with full fleet electrification (i.e., including intraday charging) are 4% lower cost and those with partial fleet electrification (i.e., without intraday charging) are 2%–3% higher. However, it is important to note that the intraday charging scenarios do not include any additional costs for the equipment necessary to achieve intraday charging (e.g., additional chargers, larger batteries, new route design). Additionally, it is worth noting that the Low Carbon Fuel Standard (LCFS) credit received for implementing electric buses is essential to achieving these results.

33 ADVANCED PROPULSION SYSTEMS↗

Background Data and Statistics on Low-Income Energy Use and Burden for the Weatherization Assistance Program: Update for Fiscal Year 2020

This report provides updated estimates of the energy consumptions, energy expenditures, and energy burdens of the population eligible to be served through the US Department of Energy (DOE) Weatherization Assistance Program (WAP) and by proxy, those clients actually served by the program. WAP continues to serve a population with an energy burden that is much greater than the rest of the county. The mean energy burden for the WAP-eligible population across the United States for FY 2020 is estimated to be 13.9% compared to 3.0% for households living above the 200% poverty threshold. The mean energy burden for households living below the 100% federal poverty line was estimated to be 30.9%. These energy burdens for the WAP-eligible population have remained steady at this high level over the last decade.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

XVis: Visualization for the Extreme-Scale Scientific Computation Ecosystem. Final Report

Scientific computing is no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/0 limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. The XVis project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressing four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis. This report reviews the accomplishments of the XVis project to prepare scientific visualization for Exascale computing.

97 MATHEMATICS AND COMPUTING↗