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At least 37 records · Page 2

Decoding anomalous grain growth at room temperature during pressure-induced phase transformations

Significant grain growth is observed during the high-pressure phase transformations (PTs) at room temperature in various materials. The main focus here is grain growth from a few hundred nanometers to 10 μm within an hour during α → ω PT in Zr. No existing theory explains this phenomenon since without PT, Zr nanocrystals do not grow at room temperature even for up to 10 years. Here, in this study, a multistep mechanism for the grain growth during α → ω PT in Zr is suggested. Phase interfaces (PI) and grain boundaries (GBs) coincide and move together as a combined PI-GBs under the action of the combined thermodynamic driving force. Such a combined motion changes the diffusional grain growth mechanism to the transformational one and the martensitic mechanism of PT to a reconstructive one via an intermediate disordered phase. The primary condition is that the GB energy of the ω phase is smaller than that of the α phase, which promotes the nucleation of ω-Zr and is consistent with the absence of the reverse PT and reduction in the PT pressure with reducing grain size. Several intermediate steps for such motion are suggested and justified kinetically. Nonhydrostatic stresses due to volume reduction in the growing ω grain promote continuous growth of the existing ω grain instead of a new nucleation at other GBs. In situ synchrotron Laue diffraction experiments confirm the main predictions of the theory. The suggested mechanism provides a new insight into synergistic interaction between PTs and microstructure evolution.

anomalous grain growth during phase transformation

Spaced out: An economic framework to explore the impacts of PV panel spacing on large-scale farming in Colorado

CONTEXT Agrivoltaic systems co-locate solar technologies with agricultural operations on an integrated plot of land and potentially provide benefits to both energy and agricultural systems. To date, large-scale (>5-MW) agrivoltaic projects in the United States have been limited to grazing and ecovoltaic applications, raising questions about the impact and scalability of agrivoltaic crop systems. Many agrivoltaic designs raise the height of the solar panels to accommodate agricultural practices while keeping energy density high. However, raising the panels results in increased photovoltaic (PV) development costs, which often are higher than the economic returns of crop production underneath the panels. This leads to unfavorable project economics and the need for other agrivoltaic solutions than raising panels. OBJECTIVE To explore other solutions, we perform an initial feasibility analysis for an agrivoltaic solution that can integrate with large-scale farming practices by increasing the row spacing in between panels. Increased PV row spacing is a low-cost approach for scaling agrivoltaics to accommodate crop production and this spacing can be tailored to required crop equipment for different regions. Increasing row spacing will reduce the power density (PV installed per acre), but in areas that are not land limited, these agrivoltaic designs could be economically feasible. Our analysis establishes a framework for a feasibility analysis for where and with what crops spaced out panel agrivoltaic solutions might be economical. METHODS Using a case study for large-scale agriculture crops in Colorado, we establish a framework for wide-row agrivoltaic economic feasibility analysis. We utilized the System Advisor Model to calculate technoeconomic metrics to compare different row spacing solutions and capture tradeoffs of these system designs. RESULTS AND CONCLUSIONS We find that, in some circumstances, wider row agrivoltaic solutions that allow for continued mechanized crop production can provide economic benefits over a traditional utility-scale PV system. For most crops examined in this analysis, roughly $\$$200/acre in agricultural profit justified spacing out the panels to at least 31.7 ft. to accommodate agrivoltaic configurations versus PV only configurations. Additionally, opportunities for increased agricultural revenue with agrivoltaic systems allow PV project economics to tolerate a larger range of CAPEX variability while remaining economically viable relative to the PV only configurations. SIGNIFICANCE This framework can be adapted for a wide variety of crops and regions and allows for examination of economically favorable sites for future agrivoltaic systems that utilize different configuration and expand opportunities for agrivoltaics.

14 SOLAR ENERGY

Development of typical solar years and typical wind years for efficient assessment of renewable energy systems across the U.S.

Weather data plays a critical role in renewable energy analysis. Compared to using multiple Actual Meteorological Years, simulations using a single typical year require significantly fewer computational resources. Previous efforts to create typical weather datasets for renewable energy analysis either lack justified or optimized strategies for selecting and weighting different weather parameters or are limited to a few specific locations. Here, in this study, we developed a dataset comprising Typical Solar Years (TSYs) and Typical Wind Years (TWYs) for over 2000 locations across the U.S., based on data from NASA's POWER project. The strategies for creating TSYs and TWYs were optimized based on the simulated outputs of various PV systems and wind turbines in 16 representative cities. This dataset provides an efficient means for the rapid evaluation and optimization of renewable energy systems throughout the entire U.S. Additionally, the optimal strategies identified in this study can be directly applied to create near-optimal TSYs and TWYs for most locations worldwide. However, readers can also employ the optimization approach presented in this work to develop optimal strategies tailored for particular regions.

NASA POWER

Cost impact of hexose-to-pentose sugar ratios for biomanufacturing

Central to the long-term vision for biomanufacturing is the ability to deconstruct plant cell walls to sugars that microbes can convert to products. Aside from glucose, the most abundant sugar in biomass is xylose, a pentose sugar. Industrially relevant microbes have been engineered to co-ferment xylose and glucose. Most nth plant technoeconomic analyses (TEAs) assume similar consumption rates and product yields for both sugars, but in reality, xylose is consumed more slowly. Feedstocks can be selected, or engineered, to alter the glucan-to-xylan ratio (GXR) but no TEAs have quantified the impact of this strategy systematically. This study explores the cost impacts of varying the glucan-to-xylan ratio (GXR) from 1.9 to 6.7 for co-fermenting glucose and xylose to ethanol and bisabolene. The minimum selling prices (MSPs) for both products decrease as the GXR increases, with the largest reductions at shorter residence times. For instance, with an increase in GXR from 1.9 to 6.7, ethanol’s MSP drops by 16 %, 5 %, and 3 % at 24, 72, and 144 h, respectively, while bisabolene’s MSP declines by 23 %, 20 %, and 15 % at 24, 72, and 120 h. Particularly for early-stage commercialization, the results suggest that altering or selecting for feedstocks with higher GXR can minimize capital costs by reducing optimal residence times. Capital-constrained biorefineries operating with shorter residence times can justify paying up to 1.5X to 2X the price for feedstocks with a higher GXR, based on the expected improvements in their product yield and overall process economics.

Delayed xylose utilization

A prototype cooling blanket for mitigating occupant overheating risk in a hot indoor environment: Modeling and assessments

Conventional ways of cooling a room or an entire house for occupant thermal comfort during summer consume a significant amount of energy and are vulnerable to overheating risk during power outages that lead to loss of cooling system operations. This study investigates a low-power cooling blanket, as a Personal Cooling System (PCS), that covers the upper human body for direct cooling during a five-day heat wave in a single-family house. A modeling framework is developed for evaluating the thermal and energy performance of the cooling blanket, which builds upon the co-simulation of three models: a house energy model, a personal thermal comfort model, and a cooling blanket model. Simulation results show that under the power outage scenario, the cooling blanket can greatly reduce the occupant heat stress with a reduction of daily hours of exceedance (discomfort hours defined as TSV>2) by up to 17.2 h (a 95.3 % improvement from the baseline power outage without the blanket). The cooling blanket, equipped with an innovative electrocaloric heat pump (COP as high as 10.1) consumes 6.31 W and can be operated by a portable battery for several days. The cooling blanket consumes only 0.28 % of the electricity of a central air-conditioning system running to provide cooling for the whole house during the five-day heatwave period. The findings justify further research of electrocaloric wearable PCS as low-power effective cooling to ensure thermal survivability of occupants during extreme indoor environments.

Electrocaloric heat pump

Influence of alloy solidification path on melt pool behavior in additive manufacturing

Numerical models used to study transport phenomena in laser-powder bed fusion processes often rely on assumptions and simplifications to reduce their computational expense. One common simplification is in the description of latent heat evolution during the solid-liquid phase change (i.e., the solidification pathway), justified by the fact that the mushy zone thickness is similar to the numerical grid spacing used for continuum transport models. The lack of resolution of transport phenomena in the mushy zone motivates the use of computationally convenient solidification paths such as linear or sigmoidal relationships over pathways derived from fundamental solidification theory such as equilibrium or Scheil models. In the present work, an uncertainty quantification (UQ) framework is used to analyze the influence of solidification pathway selection on the solidification dynamics and melt pool geometries in laser based additive manufacturing (AM) of IN625. Results show the solidification pathway has a quantifiable influence on the cooling rate at the liquidus isotherm, mushy zone thickness, and solidification time. Due to similarities in the latent heat evolution at the beginning of solidification, the equilibrium and Scheil models predict similar cooling rates near the liquidus isotherm, however the wider freezing range of Scheil leads to a wider mushy zone compared to equilibrium. The non-physical latent heat release profiles of sigmoidal and linear paths lead to significant overpredictions of cooling rates at the liquidus isotherm compared to equilibrium and Scheil. Finally, these results indicate that careful consideration should be given to the choice of solidification pathway to ensure reliable model predictions.

36 MATERIALS SCIENCE

Experimental observation of nonlinear relation between pressure and water flux is consistent with the solution-diffusion model

In several recent studies, it has been proposed that the fundamental understanding of penetrant transport in dense polymer membranes occurring via the solution-diffusion model, which has been the generally accepted theoretical framework for describing penetrant transport in such materials for the past several decades, is flawed. An alternate mechanistic framework based on the idea of two-phase flow in a porous medium (i.e., pore-flow) has been broadly advanced instead, with proponents of this approach claiming that the pore-flow theoretical framework provides the necessary mechanistic insight to design novel polymeric membrane materials for emerging applications. In this study, we show experimental results for hydraulic permeation of water that are entirely consistent with the solution-diffusion theory, without modification, for three dense polymeric membranes: crosslinked poly(ethylene glycol diacrylate) (XLPEGDA), Nafion 117 ionomer in the sodium counterion form (Nafion 117-Na), and cellulose acetate (CA). By measuring water flux at transmembrane pressures up to 240 bar, we observe a nonlinear relationship between the transmembrane pressure (TMP) and water flux, J w , for XLPEGDA and Nafion 117-Na, while this relationship is linear for CA. We demonstrate that the behavior of these three materials is described via the solution-diffusion model. According to the solution-diffusion model, flux is, to a good approximation, proportional to the transmembrane concentration difference induced by the pressure difference across the membrane, rather than to TMP itself. Water sorption isotherms are reported for all three materials. They further justify the nonlinear relationship between TMP and J w observed in XLPEGDA and Nafion 117-Na, emphasizing that the nonlinearity in the flux/TMP relationship stems from nonlinearities in the sorption isotherm with pressure. Additionally, the relationship between water flux and TMP can be predicted, a priori, with no adjustable parameters when a predictive model for the diffusion coefficient of water is employed in conjunction with the experimental water sorption isotherms in the solution-diffusion model. Furthermore, our results demonstrate the validity of the solution-diffusion model to describe transport of penetrants in dense polymer membranes, while highlighting the sensitivity of the solution-diffusion model to the many physical and mathematical simplifications commonly applied to the theory in literature.

materials

Hydrogen embrittlement and mechanical response of 304L steel with ZrC additions

While stainless steels are widely used for hydrogen storage infrastructure, they can still be vulnerable to hydrogen embrittlement justifying the need to further improve their hydrogen resiliency. Here, we investigate the potential for transition metal carbide additions to improve the hydrogen compatibility of austenitic stainless steels. ZrC nanoparticles were dispersed in contents of 0.01–10 wt% in 304 L stainless steel powder, mixed via high energy ball milling, and subsequently consolidated using direct current sintering. To assess hydrogen compatibility, the tensile properties of similarly processed 304 L without ZrC nanoparticles were compared to 304 L with the ZrC additions; both materials were evaluated prior to and after hydrogen exposure (non-charged and H-precharged, respectively). Depending upon the ZrC phase fraction, the yield strengths varied from ∼325 to 560 MPa in the non-charged condition and from ∼375 to 550 MPa in the H-precharged condition. Strain at failure varied from ∼5 to 90 % and from ∼5 to 35 % in the non-charged and hydrogen-precharged conditions, respectively. Results from stress-strain profiles demonstrate limited efficacy of ZrC as a method to mitigate hydrogen embrittlement entirely but does demonstrate the potency of ZrC inclusions as strengthening addition to 304 L alloys without a loss of ductility.

08 HYDROGEN

Uncertainty quantification and sensitivity analysis for SPERT III E-core reactivity measurement benchmarking

The Special Power Excursion Reactor Test (SPERT) III E-core experiment is important because it provides critical data on reactor behavior under significant reactivity insertions, which is essential for validating computer simulations and ensuring the safety of modern light water reactors. Its design similarities to contemporary reactors make it a valuable resource for understanding and mitigating extreme hazards in nuclear operations. The current study details the application of formal parametric uncertainty quantification and sensitivity analysis to a model of the SPERT-III E-core model for zero power reactivity benchmarking. Additionally, the reactivity impact from various modeling assumptions is quantified. Overall, an conservative estimate for an uncertainty in k$_{\text{eff}}$ of $\pm$1257 was observed. A less conservative, more realistic, uncertainty estimate of $\pm$1096 pcm can be justified by the potential for various parametric uncertainties to become negligible when sampled independently across the ~1400 pins in the core. The experimental results fall within both of these uncertainty bounds. Standardized regression coefficient as well as Sobol indices are used to identify the guide tube thicknesses as the primary contributors to the uncertainty in k$_{\text{eff}}$. Overall, this study provides information on how the uncertainties in input parameters and modeling methods impact simulated k$_{\text{eff}}$ values and can be used to aid model building efforts for future code validation with the SPERT-III E-core experiment.

22 - GENERAL STUDIES OF NUCLEAR REACTORS

Probing gluon saturation with forward di-hadron correlations in proton-nucleus collisions

We present a detailed numerical investigation of semi-inclusive forward di-hadron production in proton–nucleus collisions employing the Color Glass Condensate effective theory. We focus on the regime where di-hadrons are produced nearly back-to-back in the transverse plane, thereby justifying a transverse-momentum-dependent factorization approach in terms of small-x gluon distributions. Our computation integrates several key elements: i) non-linear rapidity evolution via the Balitsky–Kovchegov equation with running coupling, ii) both perturbative and non-perturbative Sudakov resummation, and iii) a phenomenologically constrained model for the initial conditions for small-x gluon distributions. We compare this phenomenological framework to experimental data from the STAR Collaboration on azimuthal correlations in forward di-pion production in both proton–proton and proton–gold collisions. We analyze the systematic theoretical uncertainties associated with the saturation scales of nuclei at the initial scale for rapidity evolution and with those associated with the hadronization process. Finally, we make predictions for the kinematics anticipated to be covered by the ALICE Forward Calorimeter (FoCal) upgrade at the Large Hadron Collider.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS

Quantifying the economic costs of power outages owing to extreme events: A systematic review

Quantifying the economic cost of long-duration power outages is crucial to justifying investments in resiliency and reliability improvements. However, extensive study on the subject complicates the identification of power outage costs and determining the most suitable approach to quantify them for an individual, specific facility, particularly in the context of extreme events. Here, this research provides a systematic review of economic studies estimating the impact of environmental disasters at the microeconomic and macroeconomic levels. Of 326 articles, evaluating the costs of power outages in extreme events, this work identified 22 studies that attempted to quantify the economic costs. These findings indicate that quantifying power outage costs lacks standardization, posing challenges for comparing different studies. Most analyses aiming to quantify these costs for utilities, sectors, and the overall economy rely on outdated survey data, which offer generalized rather than specific cost estimations. The costs of power outages exhibit a significant dependence on factors such as the sector involved, the type of customer affected, and the outage duration. To quantify industry costs, the research in this study suggests that using the National Renewable Energy Laboratory's online, open-access Customer Damage Function Calculator is the best option for individual-level assessments of industries, hospitals, offices, education centers, and similar facilities. However, the Interruption Cost Estimate Calculator can estimate outage costs across industrial, commercial, and residential sectors for macroeconomic outcomes. Finally, this article discusses the relative strengths of these methods and tools and the potential directions for future research.

29 ENERGY PLANNING, POLICY, AND ECONOMY

A mathematical design framework for membrane pre-concentration in energy-efficient recovery of fermentation products

Due to the dilute nature of products manufactured via fermentation and cell-free bioprocessing, dewatering is a common unit operation in downstream processing (DSP) for bioproduct recovery, but it is typically energy intensive. To improve DSP energy efficiency for bio-based small molecules, integrating high-pressure membrane pre-concentration is a promising process option. However, this approach is typically constrained by a tradeoff between concentration factor (CF) and product recovery (PR), namely increasing the CF typically results in greater product loss, and vice versa. Here we developed a model that enables process design guidelines to: (i) identify scenarios in which the additional energy consumption and product loss from membrane pre-concentration are justified for use in DSP, and (ii) determine the optimal CF that minimizes process specific energy consumption. We compared the energy consumption of high-pressure membrane-integrated processes to evaporation-only processes and applied the model to an experimental case study for the separation and purification of butyric acid from Clostridium tyrobutyricum fermentation using an in situ product recovery (ISPR) process. The model estimated that integrating a tangential-flow reverse osmosis (RO) pre-concentration unit could reduce process energy consumption up to 45%. The use of advanced membrane pre-concentration technologies, such as negative rejection membranes and organic solvent reverse osmosis (OSRO), have the potential to further reduce the overall process specific energy consumption up to 96%, projected based on modeling. Overall, membrane pre-concentration, especially when strategically integrated prior to an evaporation step with optimized process conditions, holds significant potential for improving DSP energy efficiency, particularly in applications requiring substantial solvent removal for product recovery from dilute mixtures.

09 BIOMASS FUELS

Discovery and Development of a Small-Molecule Inhibitor Targeting the GAS41 YEATS Domain in Nonsmall Cell Lung Cancer

Abstract GAS41 is frequently overexpressed in Non-Small Cell Lung Cancer (NSCLC). GAS41 contains a YEATS domain, which recognizes acetylated lysine residues on histones to recruit protein complexes and facilitate transcription. Suppression of GAS41 in NSCLC models inhibits cellular proliferation and markedly reduces tumor growth in mouse xenografts, justifying the development of small-molecule inhibitors. We have employed structure-based design and medicinal chemistry optimization to discover DLG-41, a submicromolar inhibitor binding to the GAS41 YEATS domain. DLG-41 potently disrupts the association of GAS41 YEATS with chromatin in mammalian cells and inhibits the proliferation of NSCLC cell lines with submicromolar potency without significantly affecting normal lung fibroblasts. DLG-41 induces more effective growth inhibition in A549 versus GAS41-knockout cells, demonstrating on-target activity. DLG-41 treatment upregulates the CDKN1A gene and downregulates pathways associated with lung cancer cell identity, tumor migration, and invasion. DLG-41 is a promising chemical probe for targeting GAS41 protein in NSCLC models and has potential for future development.

Listunov, Dymytrii [University of Michigan , , , ,

The Photochemistry of Amino Acids Produced on the Polar Cryovolcanic Regions of Titan

The cryovolcanic regions of Titan offer transient opportunities for prebiotic molecules to exist in water–ammonia solutions on the surface of the Saturnian moon. The upcoming NASA’s Dragonfly mission will search for high nitrogen concentrations and amino acids on Titan’s equatorial terrains. Cryovolcanic features, however, are most common on the polar regions. To mitigate the distance, bubble bursting may encapsulate the prebiotic molecules into aerosols, which Titan’s Hadley circulation would subsequently transport to the equator. Here we investigate whether alanine and glycine survive this meridional journey. Despite the unconstrained meridional wind velocities, our results suggest that the amino acids can survive the transport through the mesosphere. Dragonfly may find cryo-volcanogenic amino acids on Titan’s equator. Further, the interaction between the two amino acids increased 10-fold the photodegradation rate of glycine. We justify it based on changes in the environment polarity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

A Comprehensive Framework for Assessing Terrestrial Analogue Field Sites for Ocean Worlds

Field studies at terrestrial analogue sites represent an important contribution to the science of ocean worlds. The value of the science and technology investigations conducted at field analogue sites depends on the relevance of the analogue environment to the target ocean world. We accept that there are no perfect analogues for many of the unique environments represented by ocean worlds but suggest that a one‐to‐one matching of environmental characteristics and conditions is not crucial to the success or impact of the work. Instead, we must determine which processes and parameters are required to map directly to the target ocean world environment with high fidelity to address the science question. In this review paper, we discuss the outcomes of a workshop aimed at developing a new framework for evaluating the suitability of analogue field locations for ocean worlds research. Here we present a two‐step approach to (a) identify the most crucial processes and parameters associated with a given science question and (b) assess the fidelity of these processes and parameters at a proposed field site to those expected for the target ocean world. We demonstrate this approach in a test case evaluating three types of ocean world analogue environments with respect to a science question. The consensus document presented here equips veteran and new investigators with valuable tools to better assess and justify their analogue site selections.

58 GEOSCIENCES

Energy Equity: From Sociological Concept to Engineering Perspective of Electric Power Systems

The implementation of energy equity has emerged as a pivotal goal of the global energy transition, driven by widespread recognition of energy inequities worldwide. Because energy equity is broadly regarded as a sociological concept rather than an engineering one, the current absence of technical engineering methods necessitates the development of a justified and sound approach to making energy equity an actionable practice in the broader realms of energy, environment, and sustainability. This Perspective discusses different terms related to energy equity and proposes a generalized definition of energy equity from the engineering perspective of electric power systems. To address these challenges related to energy equity, policies in Europe and the U.S. are introduced, although their effectiveness is limited. Further, current energy equity research is classified into four categories: quantifying energy equity, improving equity in the accessibility of electricity, improving equity in the affordability of electricity, and improving equity in the resilience of power systems. Then, we classify the ongoing research challenges in energy equity into two categories, technical challenges and application challenges, and provide corresponding insights. Finally, we discuss equity of resilience or reliability, income disparity, and environmental equity, followed by a summary of this Perspective.

29 ENERGY PLANNING, POLICY, AND ECONOMY

Applying the FAIR Principles to computational workflows

Recent trends within computational and data sciences show an increasing recognition and adoption of computational workflows as tools for productivity and reproducibility that also democratize access to platforms and processing know-how. As digital objects to be shared, discovered, and reused, computational workflows benefit from the FAIR principles, which stand for Findable, Accessible, Interoperable, and Reusable. The Workflows Community Initiative’s FAIR Workflows Working Group (WCI-FW), a global and open community of researchers and developers working with computational workflows across disciplines and domains, has systematically addressed the application of both FAIR data and software principles to computational workflows. We present recommendations with commentary that reflects our discussions and justifies our choices and adaptations. These are offered to workflow users and authors, workflow management system developers, and providers of workflow services as guidelines for adoption and fodder for discussion. The FAIR recommendations for workflows that we propose in this paper will maximize their value as research assets and facilitate their adoption by the wider community.

97 MATHEMATICS AND COMPUTING

Neural network representations of multiphase Equations of State

Abstract Equations of State model relations between thermodynamic variables and are ubiquitous in scientific modelling, appearing in modern day applications ranging from Astrophysics to Climate Science. The three desired properties of a general Equation of State model are adherence to the Laws of Thermodynamics, incorporation of phase transitions, and multiscale accuracy. Analytic models that adhere to all three are hard to develop and cumbersome to work with, often resulting in sacrificing one of these elements for the sake of efficiency. In this work, two deep-learning methods are proposed that provably satisfy the first and second conditions on a large-enough region of thermodynamic variable space. The first is based on learning the generating function (thermodynamic potential) while the second is based on structure-preserving, symplectic neural networks, respectively allowing modifications near or on phase transition regions. They can be used either “from scratch” to learn a full Equation of State, or in conjunction with a pre-existing consistent model, functioning as a modification that better adheres to experimental data. We formulate the theory and provide several computational examples to justify both approaches, highlighting their advantages and shortcomings.

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