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At least 55 records · Page 3

Scaling Equitable Finance

Driven by dramatic declines in up-front cost, the U.S. solar photovoltaics (PV) industry has taken off over the past decade, growing from 1 gigawatt of installed capacity in 2009 to 89 gigawatts in 2020—or enough capacity to power roughly 19 million homes. The industry is expected to double in size over just the next 5 years.1 Much of the growth has been driven by large, utility-scale projects that can produce 5 mega- watts or more of power—enough to power at least 1,000 homes. The cost of electricity produced by these projects has decreased by more than 70 percent since 2010. As of Q3 2020, development costs of large, util- ity-scale solar PV power plants were under $1 per watt, down by more than 70 percent from 2010.2 A robust array of investors has come forward to efficiently deliver capital to these kinds of utility-scale projects including large banks, insurance companies, pension funds, and others. But low- and moderate-income communities, including communities of color, are at risk of being left behind in the transition to clean energy. Mission- driven solar project developers and financial institu- tions have been working alongside energy justice advocates to open up solar access for these communi- ties, using strategies ranging from community solar, to solar installations on affordable multifamily housing, to distributed solar and storage programs, and more. Their goals go beyond simply generating more green energy to advancing social equity by: • empowering communities to control their energy future • stabilizing energy prices, saving money, and build- ing wealth for low-income families • creating quality jobs • improving health by reducing pollution • providing energy resilience for vulnerable communities Mission-driven actors are successfully deploying a wide variety of strategies to meet these goals, from helping low-income homeowners get solar—and some- times battery storage, to developing solar projects serv- ing affordable rental housing and community facilities, to building larger “shared solar” projects to which households from across the community can subscribe. However, the financing ecosystem does not work nearly as well for these “mission driven” solar proj- ects as it does for utility-scale projects. For home rooftop solar, even if low-income consumers have a home and suitable roof, they may fail to qualify for federal tax incentives, lack adequate credit to qualify for a loan—or the mission-driven lenders seeking to serve them may not be adequately capitalized to make long-term loans. For mission-driven commercial or community-scale projects, assembling nearly every component of the project capital stack—whether bridging early-stage costs, attracting tax credit equity investors, securing long-term debt, or coming up with sponsor equity and filling gaps—can present challenges. A variety of obstacles contribute to the scarcity of financing for low-income solar, including small project sizes, lack of developer balance sheet capacity, both real and perceived issues with credit risk, elevated technical assistance needs, and greater subsidy requirements to pursue goals such as deep energy affordability, climate resilience, or job creation. Still other obstacles are regulatory: for example, not all states allow community solar projects or Power Purchase Agreements, common strategies used for providing low-income solar—and the potential for regulations to shift over time creates risks that mission-driven projects can ill afford. This report synthesizes information garnered from 47 key informant interviews, four focus group discus- sions involving 60 stakeholders, and a review of the substantial existing literature on low-income solar finance to assess the current landscape of mission- driven solar development in the United States, examine the roles that community-based financial institutions could play, and recommend public invest- ments and policy changes that could help to scale the provision of equitable solar finance. Key recommen- dations for policymakers and funders in the renew- able energy and community development fields that emerge from this process include the following: • Help to capitalize and support community-based lenders to provide flexible, low-cost, and long- term financing to mission-driven solar projects— including providing guarantees or other forms of credit enhancement. • Provide federal support for equitable solar, including a grant-in-lieu-of-credits option for the Investment Tax Credit to improve access to this critical government subsidy. • Develop pools of government and philanthropic support that can complement financing from community-based lenders to complete the capi- tal stack for mission-driven projects, as well as to support education and technical assistance to both consumers and potential project sponsors. • Create a national Renewable Energy Credits pro- gram that includes social equity targets to provide a baseline of support for clean energy generation. • Change utility regulations to remove barriers to low-income solar projects; lower permitting costs; provide greater certainty for developers, consumers and owners; and measure progress toward equity in renewable energy policy implementation.

14 SOLAR ENERGY↗

GrayQb: A Radiological Contamination Locating and Mapping Tool

Benefits Technology Overview  Easy to operate • Self-contained unit for imaging – no special power, cooling or handling requirements • Standard color camera, easy to use gamma camera and reader • Software automatically processes images, sliders to adjust intensity display • Lightweight – less than 5 lbs. without additional background shielding

Timmons, Daren↗

Evaluating the Hybrid Modelling Competition: A Step Towards Developing Good Modelling Practice

Hybrid modelling, a combination of mechanistic and data-driven modelling, is a promis¬ing approach to advance current mathematical models towards improved deci¬sion support tools for today's water-related challenges. Researchers have been develop¬ing guidelines or references for good modelling practices in the water field for mecha¬nistic (Rieger et al., 2012) and data-driven (Zhu et al., 2023) modelling, respectively. However, good modelling practices for hybrid modelling are currently missing (Schneider et al., 2022). Therefore, the International Water Association’s (IWA) hybrid modelling working group initiated the first competition on a data science competition platform (i.e. Kaggle) for water resource recovery modelling at the Watermatex con¬ference in September 2023 in Quebec. The main objective of this competition was to gain insights and experience to create good modelling practices. Further goals were to motivate students, researchers, and practitioners model, foster a vibrant and engaged community, and evaluate the efficacy of com¬petitions in solving modelling challenges within the water domain. Our next goal is that facilities will measure and gather relevant data for future competitions to solve their challenges from a modeller’s perspective.

Schneider, Mariane↗

Reflections on the role of MOOSE in Unleashing a Golden Era of American Energy Innovation

As the use of artificial intelligence spreads across most professions, projections for the expected energy consumption of these virtual assistants/workers dictate a large increase in energy production. Recent published estimates refer to up to a necessary tripling of nuclear energy production~\cite{iaea}. % TODO add citations This is supported by the new administration, calling on February 5th to "unleash Commercial Nuclear Power in the United States" and to launch the "long-awaited American nuclear renaissance"~\cite{doe-order}. The Department of Energy (DOE) is tasked with "enabl[ing] the rapid deployment and export of next generation nuclear technology". In terms of research of development, we must seek to "unleash American Energy Innovation", by "focus[ing] our time and resources on technologies that will advance basic science, grow America’s scientific leadership, reduce costs for American families [...]". To that end, the Department will "prioritize affordable, reliable, and secure energy technologies, including fossil fuels, advanced nuclear, geothermal, and hydropower." Following this call to action, we elect to examine the role of the open-source Multiphysics Object Oriented Simulation Environment (MOOSE)~\cite{moose3} in meeting the stated goals.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Vapor–Fed Electrolyzers for Carbon Dioxide Reduction Using Tandem Electrocatalysts: Cuprous Oxide Coupled with Nickel–Coordinated Nitrogen–Doped Carbon

We report ethylene is particularly attractive due to its major importance as a feedstock for various applications including the polymer industry. As such, catalyst and electrolyzer developments are crucial to achieve industrially relevant ethylene production and efficiency levels. In this work, a tandem electrocatalyst composed of copper nanocubes and nickel-coordinated nitrogen-doped carbon (NiNC) is presented, which is integrated into gas diffusion electrodes (GDEs) for direct conversion of vapor-fed CO 2 into ethylene. Evaluation of tandem GDEs in the vapor-fed flow electrolyzer shows significantly increased ethylene selectivity in terms of faradaic efficiency and C 2 H 4 /CO ratio compared to a non-tandem copper GDE. The enhancements are attributed to the increased local CO availability near the copper surface via effective CO 2 to CO conversion on neighboring NiNC. The experimental results are validated by 3D resolved continuum simulations, which show increased flux of higher-order prod-ucts with the added CO flux from NiNC. The practical viability of Cu/NiNC catalyst is further evaluated in a membrane electrode assembly electrolyzer, achieving 40% FE toward ethylene at 150 mA cm -2 and 3.2 V. These find-ings highlight the high selectivity and formation rate of ethylene achieved by successful device integration of the Cu/NiNC catalyst, demonstrating the potential for implementation in large-scale sustainable CO 2 electrolyzers.

36 MATERIALS SCIENCE↗

Enhancing and Extinguishing the Different Emission Features of 2D (EA(1-)(x)FA(x))(4)Pb3Br10 Perovskite Films

2D hybrid perovskites are attractive for optoelectronic devices. In thin films, the color of optical emission and the texture of crystalline domains are often difficult to control. Here, a method for extinguishing or enhancing different emission features is demonstrated for the family of 2D Ruddlesden-Popper perovskites (EA(1-)(x)FA(x))(4)Pb3Br10 (EA = ethylammonium, FA = formamidinium). When grown from aqueous hydrobromic acid, crystals of (EA(1-)(x)FA(x))(4)Pb3Br10 retain all the emission features of their parent compound, (EA)(4)Pb3Br10. Surprisingly, when grown from dimethylformamide (DMF), an emission feature, likely self-trapped exciton (STE), near 2.7 eV is missing. Extinction of this feature is correlated with DMF being incorporated between the 2D Pb-Br sheets, forming (EA(1-)(x)FA(x))(4)Pb3Br10 center dot(DMF)(y). Without FA, films grown from DMF form (EA)(4)Pb3Br10, retain little solvent, and have strong emission near 2.7 eV. Slowing the kinetics of film growth strengthens a different emission feature, likely a different type of STE, which is much broader and present in all compositions. Films of (EA(1-)(x)FA(x))(4)Pb3Br10 center dot(DMF)(y) have large, micron-sized domains and homogeneous orientation of the semiconducting sheets, resulting in low electronic disorder near the absorption edge. The ability to selectively strengthen or extinguish different emission features in films of (EA(1-)(x)FA(x))(4)Pb3Br10 center dot(DMF)(y) reveals a pathway to tune the emission color in these compounds.

2D halide perovskites↗

Glucose assimilation rate determines the partition of flux at pyruvate between lactic acid and ethanol in Saccharomyces cerevisiae

Engineered Saccharomyces cerevisiae expressing a lactic acid dehydrogenase can metab- olize pyruvate into lactic acid. However, three pyruvate decarboxylase (PDC) isozymes drive most carbon flux toward ethanol rather than lactic acid. Deletion of endoge- nous PDCs will eliminate ethanol production, but the resulting strain suffers from C 2 auxotrophy and struggles to complete a fermentation. Engineered yeast assimilating xylose or cellobiose produce lactic acid rather than ethanol as a major product with- out the deletion of any PDC genes. We report here that sugar flux, but not sensing, contributes to the partition of flux at the pyruvate branch point in S. cerevisiae express- ing the Rhizopus oryzae lactic acid dehydrogenase (LdhA). While the membrane glucose sensors Snf3 and Rgt2 did not play any direct role in the option of predominant product, the sugar assimilation rate was strongly correlated to the partition of flux at pyruvate: fast sugar assimilation favors ethanol production while slow sugar assimilation favors lactic acid. Applying this knowledge, we created an engineered yeast capable of simultaneously converting glucose and xylose into lactic acid, increasing lactic acid production to approximately 17 g L –1 from the 12 g L –1 observed during sequential consumption of sugars. This work elucidates the carbon source-dependent effects on product selection in engineered yeast.

59 BASIC BIOLOGICAL SCIENCES↗

Dynamic instructions for Lock-out Tag-out

Lock-out tag-out (LOTO) instructions protect personnel from un-expected re-energization or start-up of equipment that is under maintenance. Even though there is rigorous training associated with LOTO activities, inci-dents still occur. Idaho National Laboratory is researching and developing dynamic LOTO instructions, which supports automatic place keeping, per-sonnel working on multiple instructions, and multiple work groups complet-ing the same instructions. Researchers identified user needs through subject matter expert interviews, observations, and classroom training. Failing to identify potential hazards during LOTO can cause injury or death to person-nel. Dynamic instructions can provide planning, incorporate supplemental documentation into the instruction, and improve instruction compliance. Combining these functions may lead to clearer, more applicable instructions which addresses the reason for compliance issues with current paper-based procedures.

99 GENERAL AND MISCELLANEOUS↗

Gravitational self force from scattering amplitudes in curved space

Abstract We employ scattering amplitudes in curved space to model the dynamics of a light probe particle with massmorbiting in the background spacetime induced by a heavy gravitational source with massM. Observables are organized as an expansion inm/Mto all orders inG— the gravitational self-force expansion. An essential component of our analysis is the backreaction of the heavy source which we capture by including the associated light degrees of freedom. As illustration we consider a Schwarzschild background and verify geodesic motion as well as the first-order self-force correction to two-body scattering through$$\mathcal{O}$$(G 3 ). Amplitudes in curved space offer several advantages, and further developments along these lines may advance the computation of gravitational-wave signals for extreme-mass-ratio inspirals.

Physics↗

Estimating and Evaluating Roughness Length and Displacement Height in Heterogeneous Urban Environments

The roughness length (z 0 ) and displacement height (z d ) are essential surface-layer parameters in numerical models (e.g., weather, climate, wall-modeled LES, etc.). This work evaluates the consistency of z 0 and z d estimates from morphometric and anemometric methods using data from two eddy-covariance flux towers (AmeriFlux US-INg and US-INc) in Indianapolis, IN. Results show inconsistencies in estimated z 0 and z d values depending on the chosen method. The two evaluated anemometric methods estimate non-physical values of z d when compared to roughness elements surrounding both towers. Additionally, predictions of mean wind speed using surface-layer similarity theory with morphometric estimates exhibit a bias during near-neutral and stable conditions relative to observations. The overestimation of mean wind speed by surface layer similarity theory is consistent with previous observational and modeling studies in urban areas, suggesting that the application of similarity theories to urban environments may have limitations. Differentiation of vegetation from built structures appears to impact morphometric z 0 and z d estimates, particularly where vegetation is abundant; however, it has little impact on correcting biases in the similarity theory. Specifically, we find that existing similarity theories using morphometric estimates underestimate integral velocity and length scales, and the degree of underestimation depends on the stability conditions. Accounting for the degree of anisotropy in surface-layer turbulence helps reduce the biases between similarity theories and observations during unstable conditions, but not in near-neutral cases. Future work is needed to identify the cause of such biases for near-neutral conditions.

Aerodynamic roughness length↗

Multiscale Modeling Meets Machine Learning: What Can We Learn?

Machine learning is increasingly recognized as a promising technology in the biological, biomedical, and behavioral sciences. There can be no argument that this technique is incredibly successful in image recognition with immediate applications in diagnostics including electrophysiology, radiology, or pathology, where we have access to massive amounts of annotated data. However, machine learning often performs poorly in prognosis, especially when dealing with sparse data. This is a field where classical physics-based simulation seems to remain irreplaceable. In this review, we identify areas in the biomedical sciences where machine learning and multiscale modeling can mutually benefit from one another: Machine learning can integrate physics-based knowledge in the form of governing equations, boundary conditions, or constraints to manage ill-posted problems and robustly handle sparse and noisy data; multiscale modeling can integrate machine learn- ing to create surrogate models, identify system dynamics and parameters, analyze sensitivities, and quantify uncertainty to bridge the scales and understand the emergence of function. With a view towards applications in the life sciences, we discuss the state of the art of combining machine learning and multiscale modeling, identify applications and opportunities, raise open questions, and address potential challenges and limitations. We anticipate that it will stimulate discussion within the community of computational mechanics and reach out to other disciplines including mathematics, statistics, computer science, artificial intelligence, biomedicine, systems biology, and precision medicine to join forces towards creating robust and efficient models for biological systems.

machine learning, multiscale modeling, physics-bas↗

Evaluating the Feasibility of Transactive Approach for Voltage Management Using Inverters of a PV Plant

This article evaluates the feasibility of a double-auction-based Transactive Energy System (TES) for engaging the reactive power (Var) capability of inverters in a utility-scale pho¬tovoltaic (PV) plant for voltage management in distribution feed¬ers. In this approach, a PV plant owner (seller) provides Var supply curves in terms of price-quantity pairs consider¬ing the inverters’ P-Q capability, efficiency, opportunity cost for real power curtail¬ment, losses, etc. At the same time, the utility (buyer) proposes Var demand curves in price-quantity pairs exhibiting the marginal price of Var. Then, market clearing points are obtained from the intersection points of supply and demand curves which are then used to create Var dispatch sig-nals from the PV plant. To conduct a fea¬sibility study of this approach, an Australian distribution network with a utility-scale PV plant (capacity 3.275 MWP) is modeled in RSCAD and simu¬lated in real-time on MATLAB, RSCAD-RTDS co-simulation platform using real historical data. Consid¬ering a use case, namely, conservation voltage reduction (CVR), the operational feasibility along with cost-benefit analysis is demonstrated in software-in-the-loop (SIL) and hardware-in-the-loop (HIL) platform. Another use case, exploring the benefit from tap-change reduction of step-voltage-regulator, is investigated. These studies explore further use cases, e.g., PV hosting capacity, network reconfiguration, etc., to be incorporated in TES for experiencing substantial economic benefits.

Alam, Mollah Rezaul↗

Estimating geographic origins of corn and soybean biomass for biofuel production: A detailed dataset

Sustainable fuel initiatives in the United States such as the Environmental Protection Agency’s Renewable Fuel Stan- dard and the Department of Energy’s Sustainable Aviation Fuel Grand Challenge have increased the production of corn ethanol and soybean biodiesel. However, the lack of precise information regarding biomass sourcing at a localized level has hindered accurate understanding of both biofuel costs and environmental impact of these production pathways. By harnessing the power of geospatial analysis and leveraging United States Department of Agriculture (USDA) crop cen- sus data, this dataset fills this critical knowledge gap. This dataset offers a novel estimation of geospatial biomass sourc- ing for biofuel production in the United States by synthe- sizing 2017 USDA crop census data, biorefinery data from the United States Energy Information Administration, and publicly available information about biomass sourcing for biofuel production. This dataset provides a detailed under- standing of biomass use for first generation biofuel pro- duction, enabling stakeholders to make informed decisions about resource allocation, investment strategies, and infras- tructure development. Furthermore, the county-level gran- ularity of the dataset allows for increased fidelity in the techno-economic assessments and life-cycle analyses of first- generation biofuels in the United States.

09 BIOMASS FUELS↗

The path to 2060: Saudi Arabia's long-term pathway for GHG emission reduction

Saudi Arabia, as part of its Saudi Green Initiative, has announced its goal to achieve net zero green-house gas emissions by 2060. This ambitious target underscores the nation's dedication to address-ing climate change. However, there is a significant gap in comprehensive analysis regarding the long-term effects of Saudi Arabia's climate policies and their collective contribution towards the net-zero objective. This study endeavors to bridge this gap through a detailed examination using the GCAM-KSA, a specialized version of the Global Change Analysis Model tailored for Saudi Arabia, employing a multi-sectoral methodology that integrates economic, energy, and land use systems within a coherent framework to assess the impact of climate policies on GHG emissions. Our anal-ysis reveals that reaching net-zero GHG emissions by 2060 is a complex challenge requiring con-certed efforts across all sectors of the economy. While transitioning to low-carbon electricity and improving energy efficiency offer considerable emission reductions, fully decarbonizing the indus-trial and transportation sectors poses a significant hurdle. Our findings suggest that Saudi Arabia must triple its emission reduction commitments in its next Nationally Determined Contributions (NDCs) update to align with its 2060 net-zero goal. Early action and increased ambition could avoid the chances of getting locked into the high emission assets and give enough time to transform the energy system. Furthermore, the adoption and integration of Carbon Dioxide Removal (CDR) tech-nologies are identified as crucial for offsetting residual emissions, especially in sectors that might continue to rely on fossil fuels.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Logical approach to tritium vacuum pump selection for fusion applications

Vacuum pumps have been used for tritium processing since the 1940s following the isolation of pure tritium. The largest problem facing tritium vacuum pumps is the tritium radioactive decay. The beta particles, recoil energy, and subsequent radical formations are detrimental to most carbon-based materials. Carbon materials, such as plastics, elastomers, carbon fiber, activated carbon, etc., react with tritium to form methane and in the process strip material from the carbonbased material. Other reactions can be self-catalyzing, as is the case with nitrogen and tritium forming tritiated ammonia at room temperature and pressure. Tritium also readily isotopically exchanges with surface -OH groups, increasing the amount of protium in the gas stream while creating a tritium holdup on the surface. Metals are the preferred material when working with tritium, but tritium will permeate into and through almost all metals at some point. The entrapped tritium can decay inside the metal, creating local helium distortions that can impact the structural properties above and beyond the hydrogen embrittlement issue tritium can cause.

Angelette, Lucas M. [Savannah River National Labor↗

Micro-tensile testing of the bond line in hot isostatic pressed aluminum

Considerable effort is being devoted to development and regulatory qualification of low enriched fuels for research and test reactors by many agencies worldwide. One promising fuel configuration being examined for United States higher power research and test reactors (USHPRRs) are plate-type fuels composed of a metallic uranium-molybdenum foil clad in an aluminum alloy. The two pieces of aluminum alloy cladding are bonded using a hot isostatic pressing method. The mechanical properties of the resulting bond line in the aluminum alloy cladding will vary by the HIP'ing parameters, requiring a need to characterize the bond line. Small scale mechanical testing can provide a path for evaluating the mechanical properties and deformation behavior of the bond line both prior to and following irradiation. Here, in this research, room temperature micro-tensile specimens of non-irradiated and irradiated samples containing an Al alloy (AA 6061) bond line were tested to evaluate its strength and deformation behavior. Observations indicated that the strain rate did not affect the deformation behavior or strength and most of the micro-tensile specimens failed in a ductile mode in grains around the bond line. There was no indication that the microstructural features from the bond line affected the mechanical properties of the micro-tensile specimens. An initial examination was performed on irradiated material but further systematic studies of the effects of irradiation can be performed in the future.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Optimal checkpointing for adjoint multistage time-stepping schemes

Here, we consider checkpointing strategies that minimize the number of recomputations needed when performing discrete adjoint computations using multistage time-stepping schemes that require computing several substeps within one complete time step. Specifically, we propose two algorithms that can generate optimal checkpoint-ing schedules under weak assumptions. The first is an extension of the seminal Revolve algorithm adapted to multistage schemes. The second algorithm, named CAMS, is developed based on dynamic programming, and it requires the least number of recomputations when compared with other algorithms. The CAMS algorithm is made publicly available in a library with bindings to C and Python. Numerical results show that the proposed algorithms can deliver up to two times the speedup compared with that of classical Revolve. Moreover, we discuss the utilization of the CAMS library in mature scientific computing libraries and demonstrate the ease of using it in an adjoint workflow. The proposed algorithms have been adopted by the PETSc TSAdjoint library. Their performance has been demonstrated with a large-scale PDE-constrained optimization problem on a leadership-class supercomputer. This work is a significant extension of the authors' conference paper.

97 MATHEMATICS AND COMPUTING↗

Physical origins of the varying performance and unusual transport behaviors among thermoelectric A Mg 2 Sb 2 materials ( A = Ca, Sr, Sm, Yb, and Mg)

Contrary to the similar thermoelectric performance among both AZn 2 Sb 2 and AMg 2 Bi 2 compounds, their isostructural counterparts, AMg 2 Sb 2 , can exhibit thermoelectric figure of merit values that vary by orders of magnitude with different A elements. Here, we reveal physical origins accounting for the significantly differing performance among AMg 2 Sb 2 -based compounds (A = Ca, Sr, Sm, Yb, and Mg) through comprehensive analyses, where it is shown that the dispar- ities in performance at the macroscale essentially originate from the widely varying activation energies that equal amounts of dopant can induce. Meanwhile, a few unusual transport behaviors regarding electrical conductivity, carrier concentration, or lattice thermal con- ductivity among these compounds have been identified, and we also present their rationales in depth. Furthermore, this mechanism-focused study can not only promote further understanding of the complex transport behaviors in condensed matter but be instrumental in rationally tun- ing the physical properties of materials as well.

36 MATERIALS SCIENCE↗