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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6

Global Sensitivity Analysis Using the Ultra‐Low Resolution Energy Exascale Earth System Model

Abstract For decades, Arctic temperatures have increased twice as fast as average global temperatures. As a first step toward quantifying parametric uncertainty in Arctic climate, we performed a variance‐based global sensitivity analysis (GSA) using a fully coupled, ultra‐low resolution (ULR) configuration of version 1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SMv1). Specifically, we quantified the sensitivity of six quantities of interests (QOIs), which characterize changes in Arctic climate over a 75 year period, to uncertainties in nine model parameters spanning the sea ice, atmosphere, and ocean components of E3SMv1. Sensitivity indices for each QOI were computed with a Gaussian process emulator using 139 random realizations of the random parameters and fixed preindustrial forcing. Uncertainties in the atmospheric parameters in the Cloud Layers Unified by Binormals (CLUBB) scheme were found to have the most impact on sea ice status and the larger Arctic climate. Our results demonstrate the importance of conducting sensitivity analyses with fully coupled climate models. The ULR configuration makes such studies computationally feasible today due to its low computational cost. When advances in computational power and modeling algorithms enable the tractable use of higher‐resolution models, our results will provide a baseline that can quantify the impact of model resolution on the accuracy of sensitivity indices. Moreover, the confidence intervals provided by our study, which we used to quantify the impact of the number of model evaluations on the accuracy of sensitivity estimates, have the potential to inform the computational resources needed for future sensitivity studies.

54 ENVIRONMENTAL SCIENCES↗

GeoBridge: Connecting Communities to Geothermal Information and Opportunities

The geothermal community is well established with long-standing events, organizations, and tools that are known across the geothermal community. But many of these tools and resources are located behind pay walls, require memberships, or are otherwise difficult to find, especially for people looking to join the geothermal community. These barriers to access can prevent outsiders from discovering valuable geothermal resources, limiting the geothermal community's potential for collaboration with other communities, such as clean energy entrepreneurs looking to expand into geothermal energy. The Department of Energy's (DOE) GeoBridge serves to bring these communities together by acting as a single, publicly accessible, searchable portal that facilitates easy access to available geothermal knowledge and information. It works to expand and diversify the pool of geothermal stakeholders by providing in-roads to geothermal information and community resources. It helps build a stronger geothermal community; one inclusive of individuals and groups from a variety of different backgrounds, including potential investors and start-up companies looking to accelerate innovation in geothermal technologies. By linking communities to geothermal information, analysis and expertise, GeoBridge serves as a launch point, directing interested parties to existing data and tools, events, educational resources, STEM programs, permitting and regulatory information, and other resources that can be used to evaluate, promote, and discover geothermal opportunities.

access↗

Grassmannian Shape Representations for Aerodynamic Applications

Airfoil shape design is a classical problem in engineering, science, and manufacturing. Our motivation is to combine principled physics-based considerations for the shape design problem with modern computational techniques informed by a data-driven approach. Traditional analyses of airfoil shapes emphasize a flow-based sensitivity to deformations which can be represented generally by affine transformations (rotation, scaling, shearing, shifting). We present a novel representation of shapes which decouples affine-style deformations from a rich set of data-driven deformations over a submanifold of the Grassmannian. The Grassmannian representation, informed by a database of physically relevant airfoils, offers (i) a rich set of novel 2D airfoil deformations not previously captured in the data, (ii) improved low-dimensional parameter domain for inferential statistics, and (iii) consistent 3D blade representation and perturbation over a sequence of nominal shapes.

blade representation↗

An integrated numerical model for coupled poro-hydro-mechanics and fracture propagation using embedded meshes

Integrated models for fluid-driven fracture propagation and general multiphase flow in porous media are valuable to the study and engineering of several systems, including hydraulic fracturing, underground disposal of waste, and geohazard mitigation across such applications. This work extends the coupled model multiphase flow and poromechanical model of Ren et al. (2018) to admit fracture propagation (FP). The coupled XFEM-EDFM scheme utilizes a separate fracture mesh that is embedded on a static background mesh. The onset and dynamics of fracture propagation are governed by the equivalent stress intensity factor (SIF) criterion. A domain-integral method (J integral) is applied to compute this information. Additionally, an adaptive time-marching scheme is proposed to rapidly restrict and grow temporal resolution to match the underlying time-scales. The proposed model is verified with analytical solutions, and shows the capability to accurately and adaptively co-simulate fluid transport and deformation as well as the propagation of multiple fractures.

42 ENGINEERING↗

Grassmannian Shape Representations for Aerodynamic Applications: Preprint

Airfoil shape design is a classical problem in engineering, science, and manufacturing. Our motivation is to combine principled physics-based considerations for the shape design problem with modern computational techniques informed by a data-driven approach. Traditional analyses of airfoil shapes emphasize a flow-based sensitivity to deformations which can be represented generally by affine transformations (rotation, scaling, shearing, shifting). We present a novel representation of shapes which decouples affine-style deformations from a rich set of data-driven deformations over a submanifold of the Grassmannian. The Grassmannian representation, informed by a database of physically relevant airfoils, offers (i) a rich set of novel 2D airfoil deformations not previously captured in the data, (ii) improved low-dimensional parameter domain for inferential statistics, and (iii) consistent 3D blade representation and perturbation over a sequence of nominal shapes.

blade representation↗

Experimental Guesswork with Quantum Side Information Using Twisted Light

Guesswork is an information–theoretic quantity which can be seen as an alternate security criterion to entropy. Recent work has established the theoretical framework for guesswork in the presence of quantum side information, which we extend both theoretically and experimentally. We consider guesswork when the side information consists of the BB84 states and their higher-dimensional generalizations. With this side information, we compute the guesswork for two different scenarios for each dimension. We then performed a proof-of-principle experiment using Laguerre–Gauss modes to experimentally compute the guesswork for higher-dimensional generalizations of the BB84 states. We find that our experimental results agree closely with our theoretical predictions. This work shows that guesswork can be a viable security criterion in cryptographic tasks and is experimentally accessible in a number of optical setups.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Automated Credibility Assessments of User Features in Scientific Software

Scientific software (SciSoft) is complex, often containing a mixture of production capabilities co-mingled with features under active research and development. Furthermore, SciSoft is often developed over decades by non-computer scientists who may not have a strong background in or prioritize software architecture design, testing, and quality (e.g., test coverage). These conditions lead to difficulty in understanding which software components or functions implement what user-facing features and therefore those features’ software quality pedigree. This lack of understanding poses challenges in assessing readiness and credibility of user features, and often relies on a SciSoft subject matter expert’s (SME) laborious investigation and assertion. This final report of a one-year Computing and Information Sciences Lab Directed Research and Development project presents a general framework for modeling SciSoft architecture as a direct relationship between user features and the software components/functions that implement them. Our approach leverages automated labeling of the SciSoft’s regression test suite and employs machine learning algorithms to construct the architecture model. We demonstrate this framework on the Solid Mechanics component of the SIERRA multi-physics engineering analysis suite developed at Sandia National Laboratories.

97 MATHEMATICS AND COMPUTING↗

Latest Development to the Mass Tracking System (MTG)

This poster informs about the ongoing development project of the Mass Tracking System (MTG) taking place in Fuels Conditioning Complex at MFC. The information is about the MTG utilization, the possible complications in the future with the system and the solution for those complication. Furthermore, the poster reports about the progress and the future plans of the project after brief insight on how the MTG operates in the facility. Essentially, the project is separated in three different phases starting with the back-end development focusing on conversion and migration phases and finalizing with the front-end development of the website phase to provide FCF with versatile and efficient system.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Effect of Hydrophilicity-Imparting Substituents on Exciton Delocalization in Squaraine Dye Aggregates Covalently Templated to DNA Holliday Junctions

Molecular aggregates exhibit emergent properties, including the collective sharing of electronic excitation energy known as exciton delocalization, that can be leveraged in applications such as quantum computing, optical information processing, and light harvesting. In a previous study, we found unexpectedly large excitonic interactions (quantified by the excitonic hopping parameter J m,n ) in DNA-templated aggregates of squaraine (SQ) dyes with hydrophilic-imparting sulfo and butylsulfo substituents. Here, we characterize DNA Holliday junction (DNA-HJ) templated aggregates of an expanded set of SQs and evaluate their optical properties in the context of structural heterogeneity. Specifically, we characterized the orientation of and J m,n between dyes in dimer aggregates of non-chlorinated and chlorinated SQs. Here, three new chlorinated SQs that feature a varying number of butylsulfo substituents were synthesized and attached to a DNA-HJ via a covalent linker to form adjacent and transverse dimers. Various characteristics of the dye, including its hydrophilicity (in terms of log P o/w ) and surface area, and of the substituents, including their local bulkiness and electron withdrawing capacity, were quantified computationally.

59 BASIC BIOLOGICAL SCIENCES↗

Binding, Release and Functionalization of Intact Pnictogen Tetrahedra Coordinated to Dicopper Complexes

The bridging MeCN ligand in the dicopper(I) complexes [(DPFN)Cu 2 (μ,η 1 : η 1 -MeCN)][X] 2 (X=weakly coordinating anion, NTf 2 (1 a), FAl[OC 6 F 10 (C 6 F 5 )] 3 (1 b), Al[OC(CF 3 ) 3 ] 4 (1 c)) was replaced by white phosphorus (P 4 ) or yellow arsenic (As 4 ) to yield [(DPFN)Cu 2 (μ,η 2 : η 2 -E 4 )][X] 2 (E=P (2 a-c), As (3 a-c)). The molecular structures in the solid state reveal novel coordination modes for E 4 tetrahedra bonded to coinage metal ions. Experimental data and quantum chemical computations provide information concerning perturbations to the bonding in coordinated E 4 tetrahedra. Reactions with N-heterocyclic carbenes (NHCs) led to replacement of the E 4 tetrahedra with release of P 4 or As 4 and formation of [(DPFN)Cu 2 (μ,η 1 : η 1 - Me NHC)][X] 2 (4 a,b) or to an opening of one E-E bond leading to an unusual E 4 butterfly structural motif in [(DPFN)Cu 2 (μ,η 1 : η 1 -E 4 Dipp NHC)][X] 2 (E=P (5 a,b), E=As (6)). With a cyclic alkyl amino carbene ( Et CAAC), cleavage of two As-As bonds was observed to give two isomers of [(DPFN)Cu 2 (μ,η 2 : η 2 -As 4 Et CAAC)][X] 2 (7 a,b) with an unusual As 4 -triangle+1 unit.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Monitoring installation of partially occluded subassemblies in modular construction factories using BIM, ray tracing, and computer vision

Modular and offsite construction methods are being increasingly adopted due to the advantages they offer in terms of project completion time, quality, and energy-efficiency. Despite these advantages, the current state of monitoring systems in modular construction factories highly relies on labor-intensive, subjective, and error-prone observational methods. A large body of research has aimed to automate the monitoring process using an array of sensors, such as IMUs and RFIDs, during the past two decades. Recently, computer vision-based methods have gained increasing interest as a non-intrusive technology to monitor the process inside modular construction factories. However, partial occlusion challenges have impeded their practical application on a large scale. This challenge is specifically important for monitoring the installation of subassemblies since they can obstruct the view of the monitoring camera, especially those that enable long-term monitoring like closed-circuit television (CCTV) fixed-view surveillance cameras. Here, this paper aims to address this challenge by proposing a novel computer vision-based method to monitor the installation of new subassemblies inside modular factories in highly occluded scenes. The proposed methodology identifies the subassemblies in the CCTV video footage using computer vision, analyzes the occlusions using BIM and ray casting techniques, and estimates the progress of assembly by comparing the BIM model with the detected subassemblies in the video. The proposed methodology was successfully validated on surveillance videos captured from a volumetric modular construction factory in the U.S., achieving 93% accuracy in identifying the installation of subassemblies. The results from this research show that the integration of BIM and computer vision is a promising method for monitoring the installation processes inside modular factories under severe occlusion.

97 MATHEMATICS AND COMPUTING↗

Nonlinear sparse Bayesian learning for physics-based models

This paper addresses the issue of overfitting while calibrating unknown parameters of over-parameterized physics-based models with noisy and incomplete observations. Here, a semi-analytical Bayesian framework of nonlinear sparse Bayesian learning (NSBL) is proposed to identify sparsity among model parameters during Bayesian inversion. NSBL offers significant advantages over machine learning algorithm of sparse Bayesian learning (SBL) for physics-based models, such as 1) the likelihood function or the posterior parameter distribution is not required to be Gaussian, and 2) prior parameter knowledge is incorporated into sparse learning (i.e. not all parameters are treated as questionable). NSBL employs the concept of automatic relevance determination (ARD) to facilitate sparsity among questionable parameters through parameterized prior distributions. The analytical tractability of NSBL is enabled by employing Gaussian ARD priors and by building a Gaussian mixture-model approximation of the posterior parameter distribution that excludes the contribution of ARD priors. Subsequently, type-II maximum likelihood is executed using Newton's method whereby the evidence and its gradient and Hessian information are computed in a semi-analytical fashion. We show numerically and analytically that SBL is a special case of NSBL for linear regression models. Subsequently, a linear regression example involving multimodality in both parameter posterior pdf and model evidence is considered to demonstrate the performance of NSBL in cases where SBL is inapplicable. Next, NSBL is applied to identify sparsity among the damping coefficients of a mass-spring-damper model of a shear building frame. These numerical studies demonstrate the robustness and efficiency of NSBL in alleviating overfitting during Bayesian inversion of nonlinear physics-based models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Turning Outsiders into Insiders: A Call for Papers to Expand the Reach of National Laboratories’ Safety Successes, Challenges, Research, and Approaches

The most complex challenges facing the world today comprise the work of [Department of Energy’s] (DOE’s) 17 National Laboratories: [...] From furthering U.S. energy independence and leadership in clean technologies; to promoting innovation that advances U.S. economic competitiveness; to conducting research of the highest caliber in the physical, chemical, biological, materials, computational, and information sciences to advance understanding of the world around us-the Laboratories’ purview is expansive and further their contributions are indispensable.

99 GENERAL AND MISCELLANEOUS↗

Enhancing f -Element Separations with ADAAM-EH: The Impact of Phase Modifiers and a DGA Aqueous Complexant

Recent investigations have used a 2-ethylhexyl diamide amine (ADAAM-EH) for Am/Cm separations in combination with N,N,N ',N '-tetraethyldiglycolamide as an aqueous complexant to achieve an unprecedented separation factor of 41. The aim of this research effort is to understand the speciation of trivalent lanthanide (Ln) and actinide (An) ions in the organic phase of an ADAAM-EH extraction system, both with and without phase modifiers (PM) (1-octanol and tri-n-butyl phosphate (TBP)). Leveraging spectroscopic techniques in combination with distribution ratio measurements provides an understanding of organic phase f-element ligand complexation. In the absence of PM, Ln is extracted in a stoichiometric 1:1 [M(ADAAM-EH) 1 (NO 3 ) x (H 2 O) 1 ](NO 3 ) 3-x complex. The addition of 1-octanol at 20 vol % results in multiple species present. One of the species is the same as the no PM case, and the other species results in an increased -OH coordination to the inner sphere, potentially displacing some NO 3 . In the case of TBP, increasing concentration results in additional red-shifted bands in the UV-visible spectra, suggesting the complexation of additional ligands of either ADAAM-EH or TBP. Finally, the new system knowledge obtained by and spectroscopic experiments will provide benchmarking information for computational studies of the inner- and outer-sphere coordination environments of f-element cations and insights into ADAAM-EH adduct formation with PM, like 1-octanol and TBP.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Prospects of Nanoscience with Nanocrystals: 2025 Edition

Abstract Nanocrystals (NCs) of various compositions have made important contributions to science and technology, with their impact recognized by the 2023 Nobel Prize in Chemistry for the discovery and synthesis of semiconductor quantum dots (QDs). Over four decades of research into NCs has led to numerous advancements in diverse fields, such as optoelectronics, catalysis, energy, medicine, and recently, quantum information and computing. The last 10 years since the predecessor perspective “Prospect of Nanoscience with Nanocrystals” was published in ACS Nano have seen NC research continuously evolve, yielding critical advances in fundamental understanding and practical applications. Mechanistic insights into NC formation have translated into precision control over NC size, shape, and composition. Emerging synthesis techniques have broadened the landscape of compounds obtainable in colloidal NC form. Sophistication in surface chemistry, jointly bolstered by theoretical models and experimental findings, has facilitated refined control over NC properties and represents a trusted gateway to enhanced NC stability and processability. The assembly of NCs into superlattices, along with two-dimensional (2D) photolithography and three-dimensional (3D) printing, has expanded their utility in creating materials with tailored properties. Applications of NCs are also flourishing, consolidating progress in fields targeted early on, such as optoelectronics and catalysis, and extending into areas ranging from quantum technology to phase-change memories. In this perspective, we review the extensive progress in research on NCs over the past decade and highlight key areas where future research may bring further breakthroughs.

Chemistry↗

Systematic Catalyst Variation for Improved Stereoselective Epoxide Polymerization: Subtle Modifications Resulting in Superior Efficiency

Isotactic poly(propylene oxide) (iPPO) is a semicrystalline polyether that has emerged as a high-strength, photodegradable material for marine applications. To improve the accessibility of i PPO, catalysts with higher activity and selectivity are required. Using rational catalyst design informed by computational insights, we developed a flexibly tethered, bimetallic chromium catalyst exhibiting high enantioselectivity ( k rel ∼ 100) and unprecedented activity (TOF ∼ 50,000 h −1 ) for propylene oxide (PO) polymerization. Mechanistic studies reveal that high enantioselectivity originates from increased steric bulk at the ortho position of the salicylimine moiety, which increases steric repulsion between the alkoxide chain end and the ligand in the disfavored transition state. Furthermore, introducing geminal dimethyl groups that rigidify the flexible tether between the two ligand moieties significantly enhances catalyst activity by destabilizing the resting state during polymerization. The catalyst remains active at loadings as low as 0.5 ppm, enabling the synthesis of colorless, tough i PPO.

Ren, Bai-Hao [Cornell Univ., Ithaca, NY (United St↗

Insights Into Seismicity Associated With Flexibly Operating Enhanced Geothermal System From Real‐Time Distributed Acoustic Sensing

Enhanced Geothermal Systems (EGS) have the capacity to broaden the accessible resource pool for geothermal power generation. Traditionally viewed as a “baseload” resource, their flexible operation might also enable dispatchable load‐following generation and long‐term energy storage, aligning them with the evolving landscape of decarbonized electricity systems. However, increasing permeability and extracting energy during EGS operations can induce microseismic events; for many prior EGS efforts, some associated seismicity has been observed. While energetically beneficial, the flexibility of EGS operations prompts our inquiry into whether new types of operations will yield previously unseen seismicity patterns. We demonstrate the use of distributed acoustic sensing (DAS) with real‐time edge computing to monitor seismicity during a pilot test of a cyclically operated EGS facility at the Blue Mountain geothermal field. Our focus lies in uncovering seismicity insights from the real‐time microseismic catalog, particularly during load‐following dispatchability tests simulating flexible EGS operation. Here, we find that variations in pore pressure consistently correlate with seismicity, and that controlling pressure cycles during flexible operations appears to constrain microseismic activity during subsequent cycles. The spatio‐temporal evolution of microseismic clouds recorded during cyclic injection cycles fits diffusive models over our available observation period. Additionally, seismicity elevation lags behind pore pressure increases, likely due to pressure diffusion to the fracture system boundary. Through real‐time monitoring, we offer novel insights into seismicity associated with flexibly operating EGS. Our findings suggest that leveraging DAS and edge computing can inform EGS operations and help mitigate induced seismicity.

Chamarczuk, Michal [Rice Univ., Houston, TX (Unite↗

Gate-free state preparation for fast variational quantum eigensolver simulations

Abstract The variational quantum eigensolver is currently the flagship algorithm for solving electronic structure problems on near-term quantum computers. The algorithm involves implementing a sequence of parameterized gates on quantum hardware to generate a target quantum state, and then measuring the molecular energy. Due to finite coherence times and gate errors, the number of gates that can be implemented remains limited. In this work, we propose an alternative algorithm where device-level pulse shapes are variationally optimized for the state preparation rather than using an abstract-level quantum circuit. In doing so, the coherence time required for the state preparation is drastically reduced. We numerically demonstrate this by directly optimizing pulse shapes which accurately model the dissociation of H 2 and HeH + , and we compute the ground state energy for LiH with four transmons where we see reductions in state preparation times of roughly three orders of magnitude compared to gate-based strategies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗