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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 73 records · Page 4

Newton trust-region methods with primary variable switching for simulating high temperature multiphase porous media flow

Coupling multiphase flow with energy transport due to high temperature heat sources introduces significant new challenges since boiling and condensation processes can lead to dry-out conditions with subsequent re-wetting. The transition between two-phase and single-phase behavior can require changes to the primary dependent variables adding discontinuities as well as extending constitutive nonlinear relations to extreme physical conditions. Practical simulations of large-scale engineered domains lead to Jacobian systems with a very large number of unknowns that must be solved efficiently using iterative methods in parallel on high-performance computers. Performance assessment of potential nuclear repositories, carbon sequestration sites and geothermal reservoirs can require numerous Monte-Carlo simulations to explore uncertainty in material properties, boundary conditions, and failure scenarios. Due to the numerical challenges, standard NR iteration may not converge over the range of required simulations and require more sophisticated optimization method like trust-region. In this study, we use the open-source simulator PFLOTRAN for the important practical problem of the safety assessment of future nuclear waste repositories in the U.S. DOE geologic disposal safety assessment Framework. The simulator applies the PETSc parallel framework and a backward Euler, finite volume discretization. We demonstrate failure of the conventional NR method and the success of trust-region modifications to Newton’s method for a series of test problems of increasing complexity. Trust-region methods essentially modify the Newton step size and direction under some circumstances where the standard NR iteration can cause the solution to diverge or oscillate. Furthermore, we show how the Newton Trust-Region method can be adapted for Primary Variable Switching (PVS) when the multiphase state changes due to boiling or condensation. The simulations with high-temperature heat sources which led to extreme nonlinear processes with many state changes in the domain did not converge with NR, but they do complete successfully with the trust-region methods modified for PVS. This implementation effectively decreased weeks of simulation time needing manual adjustments to complete a simulation down to a day. Finally, we show the strong scalability of the methods on a single node and multiple nodes in an HPC cluster.

54 ENVIRONMENTAL SCIENCES↗

Carbon management technology pathways for reaching a U.S. Economy-Wide net-Zero emissions goal

The Carbon Management Study Group of the 37 th Energy Modeling Forum (EMF 37) designed seven scenarios to explore the role of three potentially key technology suites – point source carbon dioxide capture and storage (PSCCS), direct air capture of carbon dioxide (DACCS), and hydrogen systems (H 2 ) – in shaping the broader technology pathways to reaching net-zero carbon dioxide (CO 2 ) emissions in United States by 2050. Each scenario was run by up to 13 models participating in the EMF 37 study. Results show that carbon dioxide removal technologies were consistently a major part of successful pathways to net-zero U.S. CO 2 emissions in 2050. Achieving this net-zero CO 2 goal without any form of carbon dioxide capture and storage was found to be impossible for most models; some models also found it impossible to reach net-zero without DACCS. The marginal cost of achieving net-zero CO 2 emissions in 2050 was between two and 10 times higher without PSCCS and/or DACCS available. The carbon price at which DACCS was deployed as a backstop technology depended upon the assumed cost at which DACCS was available at scale. Carbon prices were between $\$$250 and $\$$500 per ton CO 2 when DACCS deployed as a backstop. The average CO 2 capture rate across all models in 2050 in the central net-zero scenario was 1.3 GtCO 2 /year, which implies a substantial upscaling of capacity to move and store CO 2 . Finally, hydrogen sensitivity scenarios showed that H 2 typically constituted a relatively small share of the overall U.S. energy system; however, H 2 deployed in applications that are considered hard to decarbonize, facilitating transition towards net-zero emissions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Nanotubes from the Misfit Layered Compound (SmS) 1.19 TaS 2 : Atomic Structure, Charge Transfer, and Electrical Properties

Misfit layered compounds (MLCs) MX-TX 2 , where M, T = metal atoms and X = S, Se, or Te, and their nanotubes are of significant interest due to their rich chemistry and unique quasi-1D structure. In particular, LnX-TX 2 (Ln = rare-earth atom) constitute a relatively large family of MLCs, from which nanotubes have been synthesized. The properties of MLCs can be tuned by the chemical and structural interplay between LnX and TX 2 sublayers and alloying of each of the Ln, T, and X elements. In order to engineer them to gain desirable performance, a detailed understanding of their complex structure is indispensable. MLC nanotubes are a relative newcomer and offer new opportunities. In particular, like WS 2 nanotubes before, the confinement of the free carriers in these quasi-1D nanostructures and their chiral nature offer intriguing physical behavior. High-resolution transmission electron microscopy in conjunction with a focused ion beam are engaged to study SmS-TaS 2 nanotubes and their cross-sections at the atomic scale. The atomic resolution images distinctly reveal that Ta is in trigonal prismatic coordination with S atoms in a hexagonal structure. Furthermore, the position of the sulfur atoms in both the SmS and the TaS 2 sublattices is revealed. X-ray photoelectron spectroscopy, electron energy loss spectroscopy, and X-ray absorption spectroscopy are carried out. These analyses conclude that charge transfer from the Sm to the Ta atoms leads to filling of the Ta 5d z 2 level, which is confirmed by density functional theory (DFT) calculations. Transport measurements show that the nanotubes are semimetallic with resistivities in the range of 10 –4 Ω·cm at room temperature, and magnetic susceptibility measurements show a superconducting transition at 4 K.

36 MATERIALS SCIENCE↗

Optimizing the accuracy of viscoelastic characterization with AFM force–distance experiments in the time and frequency domains

Atomic Force Microscopy (AFM) force-distance (FD) experiments have emerged as an attractive alternative to traditional micro-rheology measurement techniques owing to their versatility of use in materials of a wide range of mechanical properties. Here, we show that the range of time dependent behaviour which can reliably be resolved from the typical method of FD inversion (fitting constitutive FD relations to FD data) is inherently restricted by the experimental parameters: sampling frequency, experiment length, and strain rate. Specifically, we demonstrate that violating these restrictions can result in errors in the values of the parameters of the complex modulus. In the case of complex materials, such as cells, whose behaviour is not specifically understood a priori, the physical sensibility of these parameters cannot be assessed and may lead to falsely attributing a physical phenomenon to an artifact of the violation of these restrictions. We use arguments from information theory to understand the nature of these inconsistencies as well as devise limits on the range of mechanical parameters which can be reliably obtained from FD experiments. The results further demonstrate that the nature of these restrictions depends on the domain (time or frequency) used in the inversion process, with the time domain being far more restrictive than the frequency domain. Lastly, we demonstrate how to use these restrictions to better design FD experiments to target specific timescales of a material's behaviour through our analysis of a polydimethylsiloxane (PDMS) polymer sample.

information theory↗

Tuning nonequilibrium phase transitions with inertia

In striking contrast to equilibrium systems, inertia can profoundly alter the structure of active systems. Here, we demonstrate that driven systems can exhibit effective equilibrium-like states with increasing particle inertia, despite rigorously violating the fluctuation–dissipation theorem. Increasing inertia progressively eliminates motility-induced phase separation and restores equilibrium crystallization for active Brownian spheres. This effect appears to be general for a wide class of active systems, including those driven by deterministic time-dependent external fields, whose nonequilibrium patterns ultimately disappear with increasing inertia. The path to this effective equilibrium limit can be complex, with finite inertia sometimes acting to accentuate nonequilibrium transitions. The restoration of near equilibrium statistics can be understood through the conversion of active momentum sources to passive-like stresses. Unlike truly equilibrium systems, the effective temperature is now density dependent, the only remnant of the nonequilibrium dynamics. Further, this density-dependent temperature can in principle introduce departures from equilibrium expectations, particularly in response to strong gradients. Our results provide additional insight into the effective temperature ansatz while revealing a mechanism to tune nonequilibrium phase transitions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Continuum Dislocation Dynamics Crystal Plasticity Approach to Irradiated Body-Centered Cubic α-Iron

Radiation-induced embrittlement of reactor pressure vessel (RPV) steels can potentially limit the operating life of nuclear power plants. Over extended exposure to radiation doses, these body-centered cubic (BCC) irons demonstrate irradiation damage. Here, we present a continuum dislocation density (CDD) crystal plasticity model to capture the interaction among dislocations and self-interstitial atom (SIA) loops in α-iron. We demonstrate the importance of modeling cross slip using a combined stochastic Monte Carlo approach and the role of slip system strength anisotropy in capturing stochastic cross slip interactions. Through these captured interactions, the CDD crystal plasticity model can capture both the stress response and the physical evolution of dislocations on different slip system planes. Single-crystal verification experiments are used to calibrate the CDD crystal plasticity model, and a set of simplified polycrystalline simulations demonstrates the model’s ability to capture the stress response from tensile experiments on α-iron.

36 MATERIALS SCIENCE↗

Multidimensional modeling of fuel-cladding friction in an LWR fuel rod

Solving finite element problems with friction often increases the level of difficulty to obtain properly converged solutions. This type of challenge becomes more salient when advanced, possibly multiscale, material models are employed to capture the thermomechanical behavior of fuel and cladding materials. Here the present work details our recent developments in a nuclear fuel performance finite element code for the systematic consideration of friction in nuclear reactor finite element simulations. We show the application of friction and its effects on the mechanics of light-water reactor rods accounting for various fuel constitutive modeling techniques, model dimensionalities, pellet assumed geometries, and power conditions. In particular, we focus on the fuel rod mechanical behavior as it relates to fuel constitutive models, sensitivity to the coefficient of friction, pellet states of stress, and rod elongation. We discuss the trade-offs between the various multidimensional modeling options and highlight the relevance of frictional effects in the prediction of the fuel rod deformation and interfacial stresses. To relate our modeling results with actual reactor operation, simulations including frictional effects are compared with fuel rod elongation experimental data and some challenges for carrying out a full validation of the axial mechanics are discussed.

42 ENGINEERING↗

Review: Inelastic Constitutive Modeling: Polycrystalline Materials

This article provides a literature review that details the development of inelastic constitutive modeling as it relates to polycrystalline materials. This review distinguishes between inelastic constitutive models that account for nonlinear behavior at the microstructural level, time-independent classic plasticity models, and time-dependent unified models. Particular emphasis is placed on understanding the underlying theoretical framework for unified viscoplasticity models where creep and classical plasticity behavior are considered the result of applied boundary conditions instead of separable rates representing distinct physical mechanisms. This article establishes a clear understanding of the advantages of the unified approach to improve material modeling. This review also discusses recent topics in constitutive modeling that offer new techniques that bridge the gap between the microstructure and the continuum.

36 MATERIALS SCIENCE↗

nn-PINNs: Non-Newtonian physics-informed neural networks for complex fluid modeling

Time- and rate-dependent material functions in non-Newtonian fluids in response to different deformation fields pose a challenge in integrating different constitutive models into conventional computational fluid dynamic platforms. Considering their relevance in many industrial and natural settings alike, robust data-driven frameworks that enable accurate modeling of these complex fluids are of great interest. The main goal is to solve the coupled Partial Differential Equations (PDEs) consisting of the constitutive equations that relate the shear stress to the deformation and fully capture the behavior of the fluid under various flow protocols with different boundary conditions. Here, in this work, we present non-Newtonian physics-informed neural networks (nn-PINNs) for solving systems of coupled PDEs adopted for complex fluid flow modeling. The proposed nn-PINN method is employed to solve the constitutive models in conjunction with conservation of mass and momentum by benefiting from Automatic Differentiation (AD) in neural networks, hence avoiding the mesh generation step. nn-PINNs are tested for a number of different complex fluids with different constitutive models and for several flow protocols. These include a range of Generalized Newtonian Fluid (GNF) empirical constitutive models, as well as some phenomenological models with memory effects and thixotropic timescales. nn-PINNs are found to obtain the correct solution of complex fluids in spatiotemporal domains with good accuracy compared to the ground truth solution. We also present applications of nn-PINNs for complex fluid modeling problems with unknown boundary conditions on the surface, and show that our approach can successfully recover the velocity and stress fields across the domain, including the boundaries, given some sparse velocity measurements.

42 ENGINEERING↗

Reassessing the proposed “CY chondrites”: Evidence for multiple meteorite types and parent bodies from Cr-Ti-H-C-N isotopes and bulk elemental compositions

Here, we report a coordinated bulk Cr-Ti-H-C-N isotopic and compositional study of six carbonaceous chondrites from Antarctica that are often considered to be related and termed Yamato-like carbonaceous (CY) chondrites. These meteorites are known to have undergone extensive aqueous alteration followed by different degrees of thermal alteration, to be similar to one another in regard to mineralogy, and share affinities with both the Ivuna-like carbonaceous (CI) and Mighei-like carbonaceous (CM) chondrites. While mineralogically similar, a key difference among these samples is that chondrules have been found in some of these samples, but not in others. The aim of this study is to evaluate the relationship of these meteorites to one another, and investigate how they relate to the CI and CM chondrite groups. We find that with the addition of the isotopic compositions of these ‘CY’ chondrites, there is now a continuum of isotopic compositions among the carbonaceous chondrites. The CI chondrites are no longer separate in O isotopic compositions from the other carbonaceous chondrite groups in plots of Cr-O and Ti-O. We also find that the ‘CY’ chondrites represent two distinct populations, which correlate with their heating stage. However, the peak temperatures experienced by each population can only explain the differences in H and C isotopes and abundances and N abundances between samples, and cannot have caused the differences in N, Cr, and Ti isotopes, or all the volatile element depletions of the sample’s bulk compositions. Instead, we conclude that the compositional and isotopic data of these two populations correlate with their known chondrule abundances, indicating distinct precursors for each population. We find it most likely that these samples originate from two distinct asteroids, implying that among the six samples studied here, there are not five related samples to constitute a new meteorite group. The chondrule-free heating Stage III samples are most likely heated CI chondrites, while the chondrule-bearing heating Stage IV samples could be heated CM chondrites.

58 GEOSCIENCES↗

The expression of genes encoding novel Sesame oleosin variants facilitates enhanced triacylglycerol accumulation in Arabidopsis leaves and seeds

Summary Triacylglycerols (TAG), accumulate within lipid droplets (LD), predominantly surrounded by OLEOSINs (OLE), that protect TAG from hydrolysis. We tested the hypothesis that identifying and removing degradation signals from OLE would promote its abundance, preventing TAG degradation and enhancing TAG accumulation. We tested whether mutating potential ubiquitin‐conjugation sites in a previously reported improved Sesamum indicum OLE ( SiO ) variant, o3‐3 Cys‐OLE ( SiCO herein), would stabilize it and increase its lipogenic potential. SiCOv1 was created by replacing all five lysines in SiCO with arginines. Separately, six cysteine residues within SiCO were deleted to create SiCOv2. SiCOv1 and SiCOv2 mutations were combined to create SiCOv3. Transient expression of SiCOv3 in Nicotiana benthamiana increased TAG by two‐fold relative to SiCO. Constitutive expression of SiCOv3 or SiCOv5 , containing the five predominant TAG‐increasing mutations from SiCOv3 , in Arabidopsis along with mouse DGAT2 ( mD ) increased TAG accumulation by 54% in leaves and 13% in seeds compared with control lines coexpressing SiCO and mD. Lipid synthesis rates increased, consistent with an increase in lipid sink strength that sequesters newly synthesized TAG, thereby relieving the constitutive BADC‐dependent inhibition of ACCase reported for WT Arabidopsis. These OLE variants represent novel factors for potentially increasing TAG accumulation in a variety of oil crops.

59 BASIC BIOLOGICAL SCIENCES↗

Data for the Expression of Genes Encoding Novel Sesame Oleosin Variants Facilitates Enhanced Triacylglycerol Accumulation in Arabidopsis Leaves and Seeds

Triacylglycerols (TAG), accumulate within lipid droplets (LD), predominantly surrounded by OLEOSINs (OLE), that protect TAG from hydrolysis. We tested the hypothesis that identifying and removing degradation signals from OLE would promote its abundance, preventing TAG degradation and enhancing TAG accumulation. We tested whether mutating potential ubiquitin-conjugation sites in a previously reported improved Sesamum indicum OLE ( SiO ) variant, o3-3 Cys-OLE ( SiCO herein), would stabilize it and increase its lipogenic potential. SiCOv1 was created by replacing all five lysines in SiCO with arginines. Separately, six cysteine residues within SiCO were deleted to create SiCOv2. SiCOv1 and SiCOv2 mutations were combined to create SiCOv3. Transient expression of SiCOv3 in Nicotiana benthamiana increased TAG by two-fold relative to SiCO. Constitutive expression of SiCOv3 or SiCOv5 , containing the five predominant TAG-increasing mutations from SiCOv3 , in Arabidopsis along with mouse DGAT2 ( mD ) increased TAG accumulation by 54% in leaves and 13% in seeds compared with control lines coexpressing SiCO and mD . Lipid synthesis rates increased, consistent with an increase in lipid sink strength that sequesters newly synthesized TAG, thereby relieving the constitutive BADC-dependent inhibition of ACCase reported for WT Arabidopsis. These OLE variants represent novel factors for potentially increasing TAG accumulation in a variety of oil crops.

Feedstock Production↗

Hydro-Code Implementation and Testing of a Kinetic Phase Transition Framework

In this report we describe the Kinetic Phase Transition (KPT) framework that has been worked out over the last 10 years (from around 2014) and the implementation of it into three different codes, the one-dimensional hydro- LASLO and the three-dimensional magneto-hydro- ALEGRA, Sandia codes, via subroutines in the LAMBDA Equations of State and constitutive models package, and Flag, an arbitrary Lagrangian-Eulerian multiphysics code developed within the Lagrangian Applications project (LAP) at LANL. We discuss the introduction of phase mass (and/or volume) fractions that are needed in a code for it to be ‘phase aware’, that is, not only the thermodynamic state is known in each point but also the mixture of the materials’ phases in that point. Further we point to the need of a full Equations of State for each phase in a material to achieve phase awareness and we review the equilibrium phase model, where a phase mixture is at its lowest Gibbs free energy state, to make this point clear. Contrasting the kinetic phase transition to this equilibrium model seamlessly introduce us to the KPT framework that is subsequently thoroughly discussed. While the determination of the total state and the states and mass fractions of phases in each point is a problem that can borrow many of its numerical details from Eulerian codes and mixture of materials (not phases), the update of mass fractions with time in a KPT framework needs a new set of considerations. General for any update model is that we need to prevent mass fractions from becoming unphysical (negative or their sum to be larger than one). We have solved this problem by implementing a subdivision of the hydro time step that prevents the phase from being fully present to not present at all in one subdivided time step by limiting the size of the subdivided time step. This scheme also corrects numerical problems from abrupt changes in parameter values, the so called Gibbs phenomena, that gives rise to slushing between phases in the KPT framework. Interspersed throughout the report are discussions on different thermodynamics considerations. EOS validity windows, limitations on the EOS phase space, are needed for the KPT framework and are discussed separately and exemplified. The KPT framework described in this report has been verified by code comparison, but validation is still an active area of research. There is room for improvement in the update model, both in the model for determination of rates and in how to prevent the mass fractions from becoming unphysical. In addition, the parameters in the KPT update model and the placement of the phase boundary in the EOS phase space, and interactions with other constitutive models, are closely related and interfering with each other. One possible way forward is to simultaneously develop KPT parameters, EOS, and constitutive models for each material.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Multiphysics Thermoelastoviscoplastic Damage Internal State Variable Constitutive Model including Magnetism

We present a macroscale constitutive model that couples magnetism with thermal, elastic, plastic, and damage effects in an Internal State Variable (ISV) theory. Previous constitutive models did not include an interdependence between the internal magnetic (magnetostriction and magnetic flux) and mechanical fields. Although constitutive models explaining the mechanisms behind mechanical deformations caused by magnetization changes have been presented in the literature, they mainly focus on nanoscale structure–property relations. A fully coupled multiphysics macroscale ISV model presented herein admits lower length scale information from the nanoscale and microscale descriptions of the multiphysics behavior, thus capturing the effects of magnetic field forces with isotropic and anisotropic magnetization terms and moments under thermomechanical deformations. For the first time, this ISV modeling framework internally coheres to the kinematic, thermodynamic, and kinetic relationships of deformation using the evolving ISV histories. For the kinematics, a multiplicative decomposition of deformation gradient is employed including a magnetization term; hence, the Jacobian represents the conservation of mass and conservation of momentum including magnetism. The first and second laws of thermodynamics are used to constrain the appropriate constitutive relations through the Clausius–Duhem inequality. The kinetic framework employs a stress–strain relationship with a flow rule that couples the thermal, mechanical, and magnetic terms. Experimental data from the literature for three different materials (iron, nickel, and cobalt) are used to compare with the model’s results showing good correlations.

36 MATERIALS SCIENCE↗

A Multiphysics Thermoelastoviscoplastic Damage Internal State Variable Constitutive Model including Magnetism

We present a macroscale constitutive model that couples magnetism with thermal, elastic, plastic, and damage effects in an Internal State Variable (ISV) theory. Previous constitutive models did not include an interdependence between the internal magnetic (magnetostriction and magnetic flux) and mechanical fields. Although constitutive models explaining the mechanisms behind mechanical deformations caused by magnetization changes have been presented in the literature, they mainly focus on nanoscale structure–property relations. A fully coupled multiphysics macroscale ISV model presented herein admits lower length scale information from the nanoscale and microscale descriptions of the multiphysics behavior, thus capturing the effects of magnetic field forces with isotropic and anisotropic magnetization terms and moments under thermomechanical deformations. For the first time, this ISV modeling framework internally coheres to the kinematic, thermodynamic, and kinetic relationships of deformation using the evolving ISV histories. For the kinematics, a multiplicative decomposition of deformation gradient is employed including a magnetization term; hence, the Jacobian represents the conservation of mass and conservation of momentum including magnetism. The first and second laws of thermodynamics are used to constrain the appropriate constitutive relations through the Clausius–Duhem inequality. The kinetic framework employs a stress–strain relationship with a flow rule that couples the thermal, mechanical, and magnetic terms. Experimental data from the literature for three different materials (iron, nickel, and cobalt) are used to compare with the model’s results showing good correlations.

36 MATERIALS SCIENCE↗

Scientific machine learning for modeling and simulating complex fluids

The formulation of rheological constitutive equations—models that relate internal stresses and deformations in complex fluids—is a critical step in the engineering of systems involving soft materials. While data-driven models provide accessible alternatives to expensive first-principles models and less accurate empirical models in many engineering disciplines, the development of similar models for complex fluids has lagged. The diversity of techniques for characterizing non-Newtonian fluid dynamics creates a challenge for classical machine learning approaches, which require uniformly structured training data. Consequently, early machine-learning based constitutive equations have not been portable between different deformation protocols or mechanical observables. Here, we present a data-driven framework that resolves such issues, allowing rheologists to construct learnable models that incorporate essential physical information, while remaining agnostic to details regarding particular experimental protocols or flow kinematics. These scientific machine learning models incorporate a universal approximator within a materially objective tensorial constitutive framework. By construction, these models respect physical constraints, such as frame-invariance and tensor symmetry, required by continuum mechanics. We demonstrate that this framework facilitates the rapid discovery of accurate constitutive equations from limited data and that the learned models may be used to describe more kinematically complex flows. This inherent flexibility admits the application of these “digital fluid twins” to a range of material systems and engineering problems. We illustrate this flexibility by deploying a trained model within a multidimensional computational fluid dynamics simulation—a task that is not achievable using any previously developed data-driven rheological equation of state.

Science & Technology - Other Topics↗

Extending the Brick schema to represent metadata of occupants

Here, energy-related behaviors of occupants constitute a key factor influencing building performance; accordingly, the measured occupant data can support the objective assessment of the indoor environment and energy performance of buildings, which can inform building design and operational decisions. Existing data schemas focus on metadata of sensors, meters, physical equipment, and IoT devices in buildings; however, they are limited in representing the metadata of occupant data, including occupants' presence in spaces, movement between spaces, interactions with building systems or IoT devices, and preference of indoor environmental needs. To address this gap, an extension to the widely adopted metadata schema, Brick, is proposed to represent the contextual, behavioral, and demographic information of occupants. The proposed extension includes four parts: (1) a new “Occupant” class to represent occupants' demography and energy related behavioral patterns, (2) new subclasses under the Equipment class to represent envelope system and personal thermal comfort devices, (3) new subclasses under the Point class to represent occupant sensing and status, and (4) new auxiliary properties for occupant interactable equipment to represent the level of controllability for each piece of equipment by occupants. The extension is implemented in the Brick schema and has been tested using multiple occupant datasets from the ASHRAE Global Occupant Database. The extension enables Brick schema to capture diverse types of occupant sensing data and their metadata for FAIR data research and applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Structural basis of RNA conformational switching in the transcriptional regulator 7SK RNP

7SK non-coding RNA (7SK) negatively regulates RNA polymerase II (RNA Pol II) elongation by inhibiting positive transcription elongation factor b (P-TEFb), and its ribonucleoprotein complex (RNP) is hijacked by HIV-1 for viral transcription and replication. Methylphosphate capping enzyme (MePCE) and La-related protein 7 (Larp7) constitutively associate with 7SK to form a core RNP, while P-TEFb and other proteins dynamically assemble to form different complexes. Here, we present the cryo-EM structures of 7SK core RNP formed with two 7SK conformations, circular and linear, and uncover a common RNA-dependent MePCE-Larp7 complex. Further, together with NMR, biochemical, and cellular data, these structures reveal the mechanism of MePCE catalytic inactivation in the core RNP, unexpected interactions between Larp7 and RNA that facilitate a role as an RNP chaperone, and that MePCE-7SK-Larp7 core RNP serves as a scaffold for switching between different 7SK conformations essential for RNP assembly and regulation of P-TEFb sequestration and release.

59 BASIC BIOLOGICAL SCIENCES↗