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DOE OSTI2025

An Integral Activity-Based Protein Profiling Method for Higher Throughput Determination of Protein Target Sensitivity to Small Molecules

Activity-based protein profiling (ABPP) is a chemoproteomic technique that uses small molecule probes to label active enzymes selectively and covalently in complex proteomes. Competitive ABPP, which involves treatment of the active proteome with an analyte of interest, is especially powerful for profiling how small molecules impact specific protein activities. Advances in higher throughput workflows have made it possible to generate extensive competitive ABPP data across diverse biological samples, making this approach highly appealing for characterizing shared and unique proteins affected by perturbations such as drug or chemical exposures. To use the competitive ABPP approach effectively to understand potential adverse effects of chemicals of concern (CoC), a wide range of concentrations may be needed, particularly for chemicals that lack potency or toxicity data. In this work, we present an integral competitive ABPP method that enables target sensitivity determination for different organophosphate (OP) pesticides as model toxicants. Using previously developed OP-ABPs, we optimized conditions for tandem mass tag (TMT) multiplexing of ABPP samples and compared conventional competitive ABPP involving samples at discrete paraoxon concentrations to pooled samples across that same concentration range. We then expanded our approach to compare protein target sensitivities toward two additional OP pesticides, chlorpyrifos oxon and malaoxon. The results showed that differences in integral intensities for the pooled competition sample can be used to evaluate the relative sensitivity of specific proteins without increasing the overall number of samples. For 8 CoC concentrations of interest, this strategy reduced the number of TMT plexes and the corresponding number of LC–MS/MS analyses 3-fold. In conclusion, we envision the integral ABPP (IABPP) method will provide a means to screen diverse chemicals more rapidly to identify both high and low sensitivity protein targets.

activity-based probes↗

DOE OSTI2015

Dark matter searches for monoenergetic neutrinos arising from stopped meson decay in the Sun

Dark matter can be gravitationally captured by the Sun after scattering off solar nuclei. Annihilations of the dark matter trapped and accumulated in the centre of the Sun could result in one of the most detectable and recognizable signals for dark matter. Searches for high-energy neutrinos produced in the decay of annihilation products have yielded extremely competitive constraints on the spin-dependent scattering cross sections of dark matter with nuclei. Recently, the low energy neutrino signal arising from dark-matter annihilation to quarks which then hadronize and shower has been suggested as a competitive and complementary search strategy. These high-multiplicity hadronic showers give rise to a large amount of pions which will come to rest in the Sun and decay, leading to a unique sub-GeV neutrino signal. We here improve on previous works by considering the monoenergetic neutrino signal arising from both pion and kaon decay. We consider searches at liquid scintillation, liquid argon, and water Cherenkov detectors and find very competitive sensitivities for few-GeV dark matter masses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Spatially structured bacterial interactions alter algal carbon flow to bacteria

Phytoplankton account for nearly half of global photosynthetic carbon fixation, and the fate of that carbon is regulated in large part by microbial food web processing. We currently lack a mechanistic understanding of how interactions among heterotrophic bacteria impact the fate of photosynthetically fixed carbon. Here, we used a set of bacterial isolates capable of growing on exudates from the diatom Phaeodactylum tricornutum to investigate how bacteria-bacteria interactions affect the balance between exudate remineralization and incorporation into biomass. With exometabolomics and genome-scale metabolic modeling, we estimated the degree of resource competition between bacterial pairs. In a sequential spent media experiment, we found that pairwise interactions were more beneficial than predicted based on resource competition alone, and 30% exhibited facilitative interactions. To link this to carbon fate, we used single-cell isotope tracing in a custom cultivation system to compare the impact of different "primary" bacterial strains in close proximity to live P. tricornutum on a distal "secondary" strain. We found that a primary strain with a high degree of competition decreased secondary strain carbon drawdown by 51% at the single-cell level, providing a quantitative metric for the "cost" of competition on algal carbon fate. Additionally, a primary strain classified as facilitative based on sequential interactions increased total algal-derived carbon assimilation by 7.6 times, integrated over all members, compared to the competitive primary strain. Our findings suggest that the degree of interaction between bacteria along a spectrum from competitive to facilitative is directly linked to algal carbon drawdown.

genome-scale metabolic model↗

DOE OSTI2016

Solar Decathlon 2015 - Indigo Pine

The Solar Decathlon competition challenges students across the country to design and build a net-zero, market ready solar powered home. The bi-annual competition consists of ten contests that seek to balance the home on a scale of innovation. The ten contests were selected by to organizers to address all aspects of housing, including architecture, market appeal, engineering, communication, affordability, comfort, appliances, home life, commuting, and energy balance. Along with the criteria associated with the contests, the competition includes several design constraints that mirror those found in practical housing applications: including (but certainly not limited to) lot lines, building height, and ADA accessibility. The Solar Decathlon 2015 was held at the Orange Country Great Park in Irvine, CA. The 2015 competition was Clemson University’s first entry into the Solar Decathlon and was a notable milestone in the continued development of a home, called Indigo Pine. From the beginning, the team reconsidered the notion of sustainability as related to both the design of a home and the competition itself. The designing and building process for the home reflects a process which seamlessly moves between thinking and making to develop a comprehensive design with a method and innovations that challenge the conventions of residential construction. This report is a summary of the activities of the Clemson University team during the two-year duration of the project leading to the participation in the 2015 Solar Decathlon competition in Irvine California.

14 SOLAR ENERGY↗

DOE OSTI2016

Team Massachusetts & Central America Solar Decathlon 2015 Final Technical Report

Our team was Team MASSCA (Massachusetts and Central America), which was a partnership of Western New England University (WNE) located in Massachusetts USA, The Technological University of Panama (UTP), and Central American Technological University (UNITEC) of Honduras. Together we had a group of 6 faculty members and approximately 30 undergraduate students. Our house is ‘The EASI’ House, which stands for Efficient, Affordable, Solar Innovation. The EASI house is rectangular with two bedrooms and one bath, and offers a total square footage of 680. Based on competition estimates, The EASI house costs roughly $121,000. The EASI house has a 5kW solar system. Faculty and students from all three institutions were represented at the competition in Irvine California. Team MASSCA did well considering this was our first entry in the Solar Decathlon competition. Team MASSCA won the following awards: First Place – Affordability Contest Second Place – Energy Balance Contest. The competition provided a great experience for our students (and faculty as well). This competition provided leadership, endurance, and technical knowledge/skills for our students, and was the single most important hands-on experience during their undergraduate years. We are extremely pleased with the awards we received. At the same time we have learned from our efforts and would do better if we were to compete in the future. Furthermore, as a result of our team’s Inter-Americas collaborative effort, UTP and WNE have partnered to form Team PANAMASS (PANAma and MASSachusetts) and have developed The 3 SMART House for the inaugural Solar Decathlon Latin America & Caribbean competition held in Colombia.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Supporting ARPA-E Power Grid Optimization (Final Report)

Pacific Northwest National Laboratory (PNNL), Arizona State University (ASU), Georgia Institute of Technology (Georgia Tech), Los Alamos National Laboratory (LANL), National Renewable Energy Laboratory (NREL), Texas A&M University (TAMU), The University of Texas at Austin (UT), and the University of Wisconsin-Madison (UW-M) supported the ARPA-E Grid Optimization (GO) Competition by providing a common problem formulation, data format, datasets, evaluation mechanism, scoring, rules, and results that resulted in the awarding of $\$9.24$ million dollars to teams from academia, industry, and national labs for solving three sets of increasingly difficult non-linear, security- constrained AC Optimal Powerflow (AC-OPF) optimization problems in order to increase the efficiency of the US Electric Grid. It is estimated that a 1% increase in efficiency can save $\$1$ billion. Current industry practices typically use a linear DC model (DC-OPF) in order solve the OPF problem within the time constraints of the operation schedule. The GO Competition challenges the best power engineers, mathematicians, and computer scientists to make possible operational decisions based on accurate physical models. To accomplish this, the GO Competition created a series of Challenges and funded teams to produce the best solver. Challenge 1 was to solve the security constrained Alternating Current Optimal Power Flow (ACOPF) problem. Challenge 2 extended that to by adding adjustable transformer tap ratios, phase shifting transformers, switchable shunts, price-responsive demand, ramp rate constrained generators and loads, and fast-start unit commitment (UC). Furthermore, Challenge 2 was a maximization problem while Challenge 1 was a minimization problem. While Challenge 3 was being developed, the entrants were invited to find better solutions to the Challenge 2 synthetic datasets with no restrictions on time, hardware, or algorithms. The Challenge 2 solutions turned out to be very good. Challenge 3 expanded the Challenge 2 problem further by using multiperiod dynamic markets, including advisory models for extreme weather events, day-ahead markets, and the real-time markets with an extended look-ahead. These problems included active bid-in demand and topology optimization. Together the Challenges used nearly 30 million CPU hours. Since each team was working on the same problem, using the same data, and running on the same hardware, fair comparisons could be drawn as to the best solver. The datasets were varied enough, however, that the best solver for one dataset was not necessarily the best at another, so cumulative scores were used. The process was managed by the PNNL maintained website https://GOCompetition.energy.gov, where Entrants could find information about the problem, the data, the rules, submit their solver for evaluation, and see the scores of all the competing teams on a Leaderboard. Interest was world-wide but only American teams were eligible for prizes. The Competition has produced 34 journal articles 115 papers and been cited over 500 times in the literature, including 12 dissertations (4 from foreign countries; Columbia (2), Germany, and Italy) and 3 from the DOE ExaScale project. Software developed by Pearl Street Technologies for Challenges 1 and 2 is now deployed by Southwest Power Pool (SPP) and Midcontinent Independent Service Operator (MISO). Other teams have received inquiries from venture capitalists. Google DeepMind has thanked the Competition for making the datasets developed for the Competition public. They are using it to train machine learning models. The larger datasets have billions of unknowns to be solved for, but only a small percent matter in the final solution. Knowing what unknowns are important can dramatically speedup the solution.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

High-Fidelity, Large-Scale, Realistic Dataset Development

The final report summarizes the work performed for supporting the ARPA-E Grid Optimization Competition (Challenge 2 and Challenge 3) within the stated period. Challenge 2 For the challenge period, the main responsibility of the team is to investigate, gen- erate, and deliver parts of the data sets for the competition, based on the competition model for Challenge 2, existing data sets from Challenge 1, and data source supplied by other data set teams. Challenge 3 For the challenge period, the main responsibility of the team is to propose, create, deliver, and maintain the data format during the competition period. The data format will specify how the benchmark data will be represented and communicated to competitors. It will also specify how competitors should report back the solutions. The data format will be closely aligned with the problem formulation (maintained by the formulation team) and the solution validation process (maintained by the validation team). Our team is also responsible in investigating, generating, and delivering parts of the data sets for the competition. The data sets will be created based on the competition model for Challenge 3, existing data sets from Challenge 1 and Challenge 2, and data source supplied by other data set teams.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1998

Development of a teaching tool to encourage high school students to study aerospace technical subjects

This report details the efforts to develop a design competition aimed at high school students which will encourage them to study aerospace technical subjects. It has been shown that such competitions - based on an industry simulation game - are valuable ways to energize high school students to study in this area. Under the grant, a new competition scenario was developed, in keeping with NASA-Dryden's mission to develop aircraft and foster knowledge about aeronautics. Included are preliminary background materials and information which, if the grant is continued, would form the basis of a national competition for high school students, wherein they would design an Aerospaceport in a future year, taking into consideration the requirements of aircraft, spacecraft- ground transportation systems, passengers who use the facility, and employees who operate it. Many of the Competition methods were studied and tested during two existing local competitions in the disadvantaged communities of Lancaster and Victorville, California.

Gale, Anita↗

NASA NTRS2012

Modular Flooring System

The modular flooring system (MFS) was developed to provide a portable, modular, durable carpeting solution for NASA fs Robotics Alliance Project fs (RAP) outreach efforts. It was also designed to improve and replace a modular flooring system that was too heavy for safe use and transportation. The MFS was developed for use as the flooring for various robotics competitions that RAP utilizes to meet its mission goals. One of these competitions, the FIRST Robotics Competition (FRC), currently uses two massive rolls of broadloom carpet for the foundation of the arena in which the robots are contained during the competition. The area of the arena is approximately 30 by 72 ft (approximately 9 by 22 m). This carpet is very cumbersome and requires large-capacity vehicles, and handling equipment and personnel to transport and deploy. The broadloom carpet sustains severe abuse from the robots during a regular three-day competition, and as a result, the carpet is not used again for competition. Similarly, broadloom carpets used for trade shows at convention centers around the world are typically discarded after only one use. This innovation provides a green solution to this wasteful practice. Each of the flooring modules in the previous system weighed 44 lb (.20 kg). The improvements in the overall design of the system reduce the weight of each module by approximately 22 lb (.10 kg) (50 %), and utilize an improved "module-to-module" connection method that is superior to the previous system. The MFS comprises 4-by-4-ft (.1.2-by- 1.2-m) carpet module assemblies that utilize commercially available carpet tiles that are bonded to a lightweight substrate. The substrate surface opposite from the carpeted surface has a module-to-module connecting interface that allows for the modules to be connected, one to the other, as the modules are constructed. This connection is hidden underneath the modules, creating a smooth, co-planar flooring surface. The modules are stacked and strapped onto durable, commercially available drywall carts for storage and/or transportation. This method of storage and transportation makes it very convenient and safe when handling large quantities of modules.

Thate, Robert↗

DOE OSTI2015

Elevated carbon dioxide is predicted to promote coexistence among competing species in a trait‐based model

Abstract Differential species responses to atmospheric CO 2 concentration (C a ) could lead to quantitative changes in competition among species and community composition, with flow‐on effects for ecosystem function. However, there has been little theoretical analysis of how elevated C a ( eC a ) will affect plant competition, or how composition of plant communities might change. Such theoretical analysis is needed for developing testable hypotheses to frame experimental research. Here, we investigated theoretically how plant competition might change under eC a by implementing two alternative competition theories, resource use theory and resource capture theory, in a plant carbon and nitrogen cycling model. The model makes several novel predictions for the impact of eC a on plant community composition. Using resource use theory, the model predicts that eC a is unlikely to change species dominance in competition, but is likely to increase coexistence among species. Using resource capture theory, the model predicts that eC a may increase community evenness. Collectively, both theories suggest that eC a will favor coexistence and hence that species diversity should increase with eC a . Our theoretical analysis leads to a novel hypothesis for the impact of eC a on plant community composition. This hypothesis has potential to help guide the design and interpretation of eC a experiments.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

National Energy Education Development Project (NEED Project) (CRADA Final Report)

The U.S. Department of Energy Building Technologies Office (BTO) funds student competitions that introduce students to careers in the building sciences and increase public awareness around high-performance buildings to support the goal of developing, demonstrating, and accelerating the adoption of cost-effective technologies, techniques, tools, and services that enable high-performing, energy-efficient and demand-flexible residential and commercial buildings in both the new and existing buildings markets. The U.S. Department of Energy Solar Decathlon® (DOE/SD) is a flagship, high-visibility international competition started in 2002 that advances the goals of BTO by introducing students to building science careers; educating students and the public about the latest technologies and materials in high-performance buildings; encouraging student-led projects and research centered around building science; and demonstrating to the public the comfort and savings of homes that combine energy-efficient construction, home systems, appliances and innovative design with onsite renewable energy production. SD is a collegiate competition, comprising 10 contests, that challenges student teams to design and build highly efficient and innovative buildings powered by renewable energy. The winners will be those teams that best blend architectural and engineering excellence with innovation, market potential, building efficiency, and smart energy production. Solar Decathlon is comprised of two Challenges – Design Challenge (annual) and Build Challenge (biennial). The National Renewable Energy Laboratory (NREL) provides competition management for Solar Decathlon. NREL and Participant establish this CRADA to enable the success of the overall Solar Decathlon program by managing sponsorship funds and creating a K12 education program. Participant is to act as an Education Partner to Solar Decathlon, which includes: 1) accepting and dispersing sponsorship funds for DOE/SD; and 2) providing K12 education program to support Solar Decathlon Competition Events in April each year.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

On the numerical sensitivity of cellular automata grain structure predictions to large thermal gradients and cooling rates

Cellular automata (CA) models of as-solidified grain structure, originally developed and applied to casting, have become a common means of predicting grain structure resulting from Additive Manufacturing (AM) processes. The majority of these models are based on the decentered octahedron approach, which attempts to correct for the effect of grid anisotropy on the prediction of competitive solidification of dendritic grains. However, AM solidification occurs under cooling rates ($\dot{T}$) and thermal gradients (G) that are orders of magnitude larger than those encountered in casting, and no systematic investigation on the effect of the CA model cell size (Δx) and time step (Δt) on AM microstructure predictions has been performed. Here, in this study, such an investigation is first performed via simulation of individual grains of various crystallographic orientations with a fixed, unidirectional G, showing that CA prediction of the steady-state undercooling matched the expected values based on the interfacial response function at small G and deviated from the expected values at large G. Simulation of competitive growth of multiple grains showed a weakening of the predicted texture as G and Δx became large. Simulation of solidification under AM conditions, where G and $\dot{T}$ vary spatially across the melt pools, showed that not only does grain selection weaken and deviate from expectations at large Δx, but grains with crystallographic $\langle$100$\rangle$ aligned with the grid directions are more adversely affected by the temperature field discontinuities than grains with other crystallographic orientations. Despite the fact that the exact grain competition results depended on Δt, the overall texture development was notably less sensitive to Δt than Δx, provided that a reasonable value of Δt is selected based on the ratio of Δx to the maximum local solidification velocity in the simulation domain. Finally, from the directional solidification and AM simulation results, an analysis of computational cost compared to simulation resolution is performed based on an equation derived to quantify the relatively inaccuracy in grain selection based on the model and temperature field inputs. From this analysis, it is concluded that there is a need for algorithmic improvements to improve CA grain competition accuracy for large G processing conditions as sufficiently small Δx to resolve the necessary competition is intractable for many AM processing conditions.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Ectomycorrhizal effects on decomposition are highly dependent on fungal traits, climate, and litter properties: A model-based assessment

It has been proposed that competition between ectomycorrhizal (ECM) fungi and free-living saprotrophs for resources like nitrogen (N) slows decomposition and increases the soil carbon storage in ECM ecosystems compared to arbuscular (AM) ecosystems. However, empirical evidence for the generality of such ECM effects is equivocal, and confounding mechanisms have been proposed that affect the magnitude and direction of ECM effects on soil carbon. Here, for this work, we conduct a theoretical modeling experiment, where we explicitly incorporate mycorrhizal processes into the Carbon, Organisms, Rhizosphere, and Protection in the Soil Environment (CORPSE) model. We use the model to explore the conditions under which ECM N acquisition processes can induce stronger saprotrophic N limitation and result in slower decomposition rates and greater soil organic carbon accumulation compared to AM processes. We found that the ECM fungi more strongly inhibited decomposition when litter inputs were N-depleted and relatively recalcitrant and when ECM fungi possessed a strong capacity to mine N from both recalcitrant soil organic matter and microbial necromass. Climate and seasonality also played a role as the ECM competition effect was strongest at low mean annual temperatures and when litterfall peaked seasonally. Priming effects driven by high root exudation rates in ECM-dominated systems could overwhelm the competition effect and reduce soil carbon under some circumstances. The ECM effect on decomposition in our simulations was highly context dependent. Based on our model results, we expect to see a strong ECM competition effect in temperate deciduous and boreal forests with relatively recalcitrant litter inputs, and with ECM fungi that produce oxidases and necromass-degrading enzymes. However, even a relatively strong ECM competition effect on decomposition only increased soil organic carbon accumulation by ~10%.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

Novel covariance-based neutrality test of time-series data reveals asymmetries in ecological and economic systems

Systems as diverse as the interacting species in a community, alleles at a genetic locus, and companies in a market are characterized by competition (over resources, space, capital, etc) and adaptation. Neutral theory, built around the hypothesis that individual performance is independent of group membership, has found utility across the disciplines of ecology, population genetics, and economics, both because of the success of the neutral hypothesis in predicting system properties and because deviations from these predictions provide information about the underlying dynamics. However, most tests of neutrality are weak, based on static system properties such as species-abundance distributions or the number of singletons in a sample. Time-series data provide a window onto a system’s dynamics, and should furnish tests of the neutral hypothesis that are more powerful to detect deviations from neutrality and more informative about to the type of competitive asymmetry that drives the deviation. Here, we present a neutrality test for time-series data. We apply this test to several microbial time-series and financial time-series and find that most of these systems are not neutral. Our test isolates the covariance structure of neutral competition, thus facilitating further exploration of the nature of asymmetry in the covariance structure of competitive systems. Much like neutrality tests from population genetics that use relative abundance distributions have enabled researchers to scan entire genomes for genes under selection, we anticipate our time-series test will be useful for quick significance tests of neutrality across a range of ecological, economic, and sociological systems for which time-series data are available. Here, future work can use our test to categorize and compare the dynamic fingerprints of particular competitive asymmetries (frequency dependence, volatility smiles, etc) to improve forecasting and management of complex adaptive systems.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2015

Improved Method for the Production of Tetrahydrofuran From Biomass

Statement of the Problem: Tetrahydrofuran (THF) is a large volume, commodity chemical used as a basic building block for polyurethane stretch fibers (Spandex), other elastomers, solvents for PVC cements, pharmaceuticals, and coatings. Current THF production requires petroleum-based raw materials and significant energy inputs, representing inefficient use of petroleum resources and placing the U.S. at a manufacturing disadvantage compared to chemical manufacturers in other world areas. Pulp and paper manufacture is one of the largest industries in the U.S., representing about 6% of the manufacturing sector of the U.S. GDP. In recent decades, the pulp and paper industry has struggled with a declining market, poor profitability, and competition from other world areas, leading to the shutdown of many U.S. pulp and paper mills, and loss of U.S. employment. The production of chemicals, such as THF from pulp and paper waste hydrolysate, can provide new technologies and products from pulp and paper manufacture which can enhance industry profitability. The iCARD technology will produce and sell THF from selected pulp and paper byproduct hydrolysates without deleterious effect on ongoing pulp production of the mill. Overall Objective: The overall goal of this Small Business Innovation Research Phase II Project was to complete the research, development, and design tasks required to commercialize an innovative technology using catalytic reactive distillation to achieve process intensification for the manufacture of “green” THF from pulp mill waste hydrolysate. The new technology will benefit the U.S. pulp and paper industry by providing new technologies and products from pulp and paper manufacture, which can enhance industry profitability, and increase industry employment. Development of commercially competitive biomass based technologies will reduce consumption of scarce hydrocarbon resources, and improve long term U.S. competitiveness in global markets. Conclusions: The novel catalytic reactive distillation technology successfully demonstrated the technical and economic feasibility of the manufacture of THF production from dilute aqueous biomass solutions. New catalyst compositions were developed with catalytic activity for conversion of furfural to THF which exceed the activity of conventional catalysts by 2 to 3 orders of magnitude. The feasibility of achieving selectivity to the desired THF product approaching 100% was demonstrated. The novel catalysts also demonstrated catalyst stability far superior to conventional furfural decarbonylation catalysts. The novel technology also demonstrated the ability to produce other valuable commercial products such as tetrahydrofurfuryl alcohol, 1,5-pentanediol, 2-methyl furan, and 2-tetrahydromethylfuran as co-products with THF. Based on the use of waste pulp mill hydrolysate as the biomass raw material source, the new technology will produce THF for a total manufacturing cost less than the raw material cost for the hydrocarbon-based feed stocks for conventional THF production. Commercial Applications: Selective catalytic reactive distillation of pulp mill waste hydrolysate will allow commercial production of “green” THF from biomass feedstocks for the production of “green” elastomer fibers, and industrial solvents. The new technology will benefit the U.S. pulp and paper industry by providing new technologies and products from pulp and paper manufacture, which can enhance industry profitability, and increase industry employment. Development of commercially competitive biomass based technologies will reduce consumption of scarce hydrocarbon resources, and improve long term U.S. competitiveness in global markets.

09 BIOMASS FUELS↗

DOE OSTI2020

Phase 1 NuScale SMR FOAK Nuclear Demonstration Readiness Project (Final Scientific/Technical Report)

The overarching objective of the Phase 1 NuScale SMR First-of-a-Kind (FOAK) Nuclear Demonstration Readiness Project was to enhance competitiveness of the U.S. nuclear industry by enabling timely deployment of the NuScale small modular reactor (SMR). The scope of this Phase 1 project continued to advance the licensing and design maturity, particularly in those areas related to supporting customer readiness, supply chain integration, cost competitiveness, and cost confidence. This investment provided by the Government has accelerated development of these designs and technologies so that the existing domestic fleet of nuclear power plants remains viable and the most mature in the nuclear industry. The intent is to have the new, advanced U.S. designs be deployed as early 2026, and be globally competitive. As a part of the First-of-a-Kind Nuclear Demonstration Readiness Project, NuScale has been developing an advanced reactor design, leading the path for other development projects or complex technology advancements for existing plants that have significant technical and licensing risk. The NuScale Power team (NuScale) is advancing licensing, engineering, supply chain development, testing, and other required activities to enhance the innovation and competitiveness of the U.S. nuclear industry by enabling timely deployment of the NuScale SMR. Specifically, NuScale is performing the following activities in Phase 1. Fully supporting the NRC review of the NuScale DCA to ensure approval of a final safety evaluation report by the end of 2020. Improving plant cost confidence and cost competitiveness through design and supply chain advancement, incorporation of constructability best practices, and margin recovery to increase plant power output. Accelerating design maturity, technology development, and operational program readiness to support a customer commitment for plant deployment. The Department of Energy (DOE) Office of Scientific and Technical Information (OSTI), a unit of the Office of Science, fulfills agency-wide responsibilities to collect, preserve, and disseminate both unclassified and classified scientific and technical information (STI) emanating from DOE-funded research and development (R&D) activities at DOE national laboratories and facilities and at universities and other institutions nationwide. This scientific and technical report provides summaries of the analyses and research that was performed by NuScale under this project that achieves the objective of disseminating information to the nuclear industry to ensure the innovations realized are shared for the benefit of the industry at large.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

A Spatially Explicit Individual-Based Modeling Approach to Evaluate the Cumulative Effects of Wind Energy Development on the Greater Sage-Grouse: Sensitivity Analysis and Validation of Key Parameters

To address the need for an approach to evaluate cumulative ecological impacts of wind energy development, particularly those on critical wildlife habitats and species, the authors developed a proof-of-concept, landscape-based, spatially explicit individual-based modeling (IBM) framework for populations of the greater sage-grouse (Centrocercus urophasianus) in Albany County, Wyoming, based on published and other available information on the life history of the species. This sage-grouse IBM estimates the spatial and temporal movements of sage-grouse based on modeled effects of habitat characteristics and developments on sage-grouse condition, survivorship, and reproduction. After completing the initial version of the model, we conducted a series of sensitivity analyses of key model parameters and validation of lek occurrences and spatial distributions to better understand performance of the model relative to observed values of important life history characteristics. The parameter sensitivity analysis was conducted as a series of one-factor-at-a-time tests in which the values of selected parameters were individually varied to evaluate the corresponding effects on model output. We examined the model’s response to changes in parameter values to gain insight into the overall robustness of the model, identify key driver parameters, and initiate qualitative validation. Five functions selected for sensitivity analyses were (1) the rate of change in body condition in relationship to habitat suitability index (HSI) of occupied habitat (condition change rate), (2) the effect of competition between individuals with overlapping home ranges expressed as a percentage reduction in HSI (competition factor), (3) value of condition at which survivorship probability is equal to zero (zero survivorship condition), (4) the relationship between female body condition and clutch size, and (5) the relationship between female body condition and nest success. We varied the parameter values to be tested for the sensitivity analysis around the original value used in the model (i.e., tested values were higher and lower than the model’s original value) to examine the effect of this variation on the predicted output of the model. Model outputs evaluated in the sensitivity analysis included (1) predicted age-class distribution (as measured by the percentage of immature individuals within the population); (2) predicted sex ratio; (3) predicted age-sex class distribution (percent of population in each of six age-sex classes, i.e., male and female juveniles, yearlings, and adults); (4) lifespan; (5) population size; and (6) spatial distribution. Of the five parameters analyzed, condition change rate, survivorship, clutch size, and nest success did not substantially affect any of the evaluated model outputs. For the predicted age-class distribution, the percentage of immature individuals predicted by the model for these four parameters ranged from 61.9% to 65.0%, which was reasonable with respect to the reference values of 51.4 to 57.8% in published studies. The ratio of females to males ranged from 1.09 to 1.14, which was comparable to the reference values of 1.2 to 3.0 presented in an existing study. The predicted mean lifespan ranged from 1.62 to 1.74 years, which appears to be reasonable with respect to the reference values of 0.9 to 1.1 years for sharp-tail grouse and greater prairie chickens presented by published studies. The predicted population size ranged from 1,877 to 3,140. This prediction would be reasonable with respect to our estimate of 5,000 yearlings and adults, which was based on the USFWS estimate for the state of Wyoming scaled to the number of leks in the county. The predicted spatial distribution was not substantially affected by the parameter values examined. In our sensitivity analyses, the only tested parameter that had a noticeable effect on model output was competition factor. Over the range of values tested for this parameter, predicted population size exhibited the largest range (from 1,833 to 4,737) of all parameters tested. As the competition factor increased, the predicted population size decreased. This reflects the effect competition had on the number of individuals that could co occur in high-quality habitat patches. Despite this apparently significant effect, the range of values appears to be reasonable with respect to our estimate of 5,000 yearlings and adults, which was based on the USFWS estimate for the state of Wyoming scaled to the number of leks in the county.

17 WIND ENERGY↗

DOE OSTI2020

Benchmarking and parameter sensitivity of physiological and vegetation dynamics using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) at Barro Colorado Island, Panama

Plant functional traits determine vegetation responses to environmental variation, but variation in trait values is large, even within a single site. Likewise, uncertainty in how these traits map to Earth system feedbacks is large. We use a vegetation demographic model (VDM), the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), to explore parameter sensitivity of model predictions, and comparison to observations, at a tropical forest site: Barro Colorado Island in Panama. We define a single 12-dimensional distribution of plant trait variation, derived primarily from observations in Panama, and define plant functional types (PFTs) as random draws from this distribution. We compare several model ensembles, where individual ensemble members vary only in the plant traits that define PFTs, and separate ensembles differ from each other based on either model structural assumptions or non-trait, ecosystem-level parameters, which include (a) the number of competing PFTs present in any simulation and (b) parameters that govern disturbance and height-based light competition. While single-PFT simulations are roughly consistent with observations of productivity at Barro Colorado Island, increasing the number of competing PFTs strongly shifts model predictions towards higher productivity and biomass forests. Different ecosystem variables show greater sensitivity than others to the number of competing PFTs, with the predictions that are most dominated by large trees, such as biomass, being the most sensitive. Changing disturbance and height-sorting parameters, i.e., the rules of competitive trait filtering, shifts regimes of dominance or coexistence between early- and late-successional PFTs in the model. Increases to the extent or severity of disturbance, or to the degree of determinism in height-based light competition, all act to shift the community towards early-successional PFTs. In turn, these shifts in competitive outcomes alter predictions of ecosystem states and fluxes, with more early-successional-dominated forests having lower biomass. It is thus crucial to differentiate between plant traits, which are under competitive pressure in VDMs, from those model parameters that are not and to better understand the relationships between these two types of model parameters to quantify sources of uncertainty in VDMs.

54 ENVIRONMENTAL SCIENCES↗