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Deconvoluting thermomechanical effects in X-ray diffraction data using machine learning

X-ray diffraction is ideal for probing the sub-surface state during complex or rapid thermomechanical loading of crystalline materials. However, challenges arise as the size of diffraction volumes increases due to spatial broadening and because of the inability to deconvolute the effects of different lattice deformation mechanisms. Here, we present a novel approach that uses combinations of physics-based modeling and machine learning to deconvolve thermal and mechanical elastic strains for diffraction data analysis. The method builds on a previous effort to extract thermal strain distribution information from diffraction data. The new approach is applied to extract the evolution of the thermomechanical state during laser melting of an Inconel 625 wall specimen which produces significant residual stress upon cooling. A combination of heat transfer and fluid flow, elasto-plasticity and X-ray diffraction simulations is used to generate training data for machine-learning (Gaussian process regression, GPR) models that map diffracted intensity distributions to underlying thermomechanical strain fields. First-principles density functional theory is used to determine accurate temperature-dependent thermal expansion and elastic stiffness used for elasto-plasticity modeling. The trained GPR models are found to be capable of deconvoluting the effects of thermal and mechanical strains, in addition to providing information about underlying strain distributions, even from complex diffraction patterns with irregularly shaped peaks.

36 MATERIALS SCIENCE↗

Coupled Air Quality and Boundary-Layer Meteorology in Western U.S. Basins during Winter: Design and Rationale for a Comprehensive Study

The wintertime episodes of high aerosol concentrations occur frequently in urban and agricultural basins and valleys worldwide. These episodes often arise following development of persistent cold-air pools (PCAPs) that limit mixing and modify chemistry. While field campaigns targeting either basin meteorology or wintertime pollution chemistry have been conducted, coupling between interconnected chemical and meteorological processes remains an insufficiently studied research area. Gaps in understanding the coupled chemical–meteorological interactions that drive high-pollution events make identification of the most effective air-basin specific emission control strategies challenging. To address this, a September 2019 workshop occurred with the goal of planning a future research campaign to investigate air quality in western U.S. basins. Approximately 120 people participated, representing 50 institutions and five countries. Workshop participants outlined the rationale and design for a comprehensive wintertime study that would couple atmospheric chemistry and boundary layer and complex-terrain meteorology within western U.S. basins. Participants concluded the study should focus on two regions with contrasting aerosol chemistry: three populated valleys within Utah (Salt Lake, Utah, and Cache Valleys) and the San Joaquin Valley in California. This paper describes the scientific rationale for a campaign that will acquire chemical and meteorological datasets using airborne platforms with extensive range, coupled to surface-based measurements focusing on sampling within the near-surface boundary layer, and transport and mixing processes within this layer, with high vertical resolution at a number of representative sites. No prior wintertime basin-focused campaign has provided the breadth of observations necessary to characterize the meteorological–chemical linkages outlined here, nor to validate complex processes within coupled atmosphere–chemistry models.

54 ENVIRONMENTAL SCIENCES↗

Data, figures, animations, and scripts associated with the manuscript "Integrated Effects of Site Hydrology and Vegetation on Exchange Fluxes and Carbon Cycling at the Coastal Terrestrial Aquatic Interface"

This package contains the data, figures, animations, and scripts used in "Integrated Effects of Site Hydrology and Vegetation on Exchange Fluxes and Carbon Cycling at the Coastal Terrestrial Aquatic Interface" (Li et al., 2023). This study examines the interactions between soil, vegetation and hydrologic conditions in coastal areas, with a focus on the Chesapeake Bay region. The researchers used a mechanistic model called ATS-PFLOTRAN to explore how these interactions affect exchange process in different regions and the carbon/nitrogen cycle across the terrestrial-aquatic interface (TAI). Simulation scenarios isolate the effects of control factors and reaction constants derived from laboratory experiments. The results show a carbon cycle "hot zone" in coastal wetlands and in the transition zone between wetlands and uplands. Transpiration enhances fluxes between the surface and subsurface domains and increases dissolved oxygen in TAI. The decomposition of leaf-derived organic carbon provides an additional source of carbon for aerobic respiration and denitrification in the TAI. Microbial activity plays a key role in controlling redox conditions and their variability. This modeling study improves the understanding of complex TAI interactions and facilitates the representation of coastal ecosystems in larger-scale Earth system models.Several files can be found from this data package.1. Readme,md: This file describe the Title, Target Journal, Target submission date, Co-author, Science Questions, Hypotheses, Key words, Key message, Model and Data, Repo Structure. The user can read this file first and then go to details.2. mesh.zip: This file contains the mesh file for simulation cases. 3. Figure.zip: This file contains figures used in the manuscript . 4. animation.zip: This file contains animations used in the manuscript . 5. Data.zip: This file contains all required input data, such as concentration and flow boundaries. Also, it contains the DEM and processes results on area fraction. 6. Simulation_setup_and_results.zip: This file contains setup of cases used in the manuscript . The result files are too large, if you need that data, please contact to the Author. 7. notebooks.zip: This file contains the Jupyter notebooks for performing sensitivity analysis and other pre-process and post-process analyses.

54 ENVIRONMENTAL SCIENCES↗

Solar p-mode oscillations as a tracer of radial differential rotation

Photoelectric observations of solar p-modes obtained with improved wavenumber and frequency resolution are presented. The observations are compared with model calculations of the p-modes, and the degree of spatial and temporal coherence of the observed wave pattern is investigated. It is found that the p-mode oscillations pervade the visible surface of the sun with a high degree of coherence in space and time, so that the whole complex pattern of standing waves with its nodes and antinodes can be regarded as a fixed pattern corotating with the solar surface layers. The p-modes are introduced as a tracer of solar rotational flow velocities. The equatorial differential rotation is estimated as a function of effective depth on the basis of the theoretical contribution functions for the p-modes recently derived by Ulrich et al. (1978). The results strongly indicate that the angular speed of rotation is not uniform even in the relatively shallow layer extending about 20,000 km below the photosphere.

Deubner, F.-L.↗

Wing tip vortex calculations with an unstructured adaptive-grid Euler solver

A solution-adaptive grid method has been developed for computing tip-vortex flowfields around rectangular wings. This method uses subdivision in order to locally refine the grid in regions with high vorticity. Two different flow solvers are used. Each solves the three-dimensional Euler equations on unstructured grids. Computed results are compared to experimentally measured surface pressures and vortex velocities on a NACA 0015 rectangular wing. Predicted results for surface pressures and integrated lift agree well with the experimental data. The predicted size of the rotational vortex core is larger than the experimentally-measured value and the peak velocities are less. This discrepancy appears to be caused by deficiencies in the inviscid Euler-equation model. This model cannot capture the complex viscous effects at the tip that determine the detailed structure of the resulting vortex. In spite of this limitation, the present Euler unstructured adaptive-grid method demonstrates the ability to convert vortical flows with low numerical diffusion. Applications for modeling helicopter rotor wake systems are discussed.

Strawn, Roger C.↗

Constraints on the Martian cratering rate imposed by the SNC meteorites and Vallis Marineris layered deposits

Following two independent lines of evidence -- estimates of the age and formation time of a portion of the Martian geologic column exposed in the layered deposits and the crystallization and ejection ages of the SNC meteorites -- it appears that the Martian cratering rate must be double the lunar rate or even higher. This means models such as NHII or NHIII (Neukum and Hiller models II and III), which estimate the Martian cratering rate as being several times lunar are probably far closer to reality on Mars than lunar rates. The effect of such a shift is profound: Mars is transformed from a rather Moon-like place into a planet with vigorous dynamics, multiple large impacts, erosion, floods, and volcanism throughout its history. A strong shift upward in cratering rates on Mars apparently solves some glaring problems; however, it creates others. The period of time during which Earth-like atmospheric conditions existed, the liquid water era on Mars, persists in NHIII up to only 0.5 b.y. ago. Scenarios of extended Earth-like conditions on Mars have been discounted in the past because they would have removed many of the craters from the early bombardment era found in the south. It does appear that some process of crater removal was quite vigorous in the north during Mars' past. Evidence exists that the northern plains may have been the home of long-lived seas or perhaps even a paleo-ocean, so models exist for highly localized destruction of craters in the north. However, the question of how the ancient crater population could be preserved in the south under a long liquid-water era found in any high-cratering-rate models is a serious question that must be addressed. It does appear to be a higher-order problem because it involves low-energy dynamics acting in localized areas, i.e., erosion of craters in the south of Mars, whereas the two problems with the low-cratering-rate models involve high-energy events acting over large areas: the formation of the Vallis Marineris, the SNC ejecting impacts, and the global atmospheric pressure and temperature conditions that allow liquid water to exist as a robust entity anywhere on the Martian surface. In any case, it appears Mars is a more complex and dynamic planet than previously supposed. It has canyons dating from the middle to late period of its history that contain apparent lake sediments bedded deeper than most sediments on Earth. Recent multiple, violent impacts on Mars have apparently provided us with multiple random samples of its surface that all crystallized less than 1.5 b.y. ago. These things cannot be accommodated in our present cratering chronologies of Mars, based on 1x lunar cratering rates, without great difficulties. These difficulties suggest that a new chronology, probably based on NHII or even NHIII, should be adopted; this new chronology will provide us with a new view of Mars as a dynamic planet of rich history.

Brandenburg, J. E.↗

Expression and affinity purification of recombinant proteins from plants

With recent advances in plant biotechnology, transgenic plants have been targeted as an inexpensive means for the mass production of proteins for biopharmaceutical and industrial uses. However, the current plant purification techniques lack a generally applicable, economic, large-scale strategy. In this study, we demonstrate the purification of a model protein, beta-glucuronidase (GUS), by employing the protein calmodulin (CaM) as an affinity tag. In the proposed system, CaM is fused to GUS. In the presence of calcium, the calmodulin fusion protein binds specifically to a phenothiazine-modified surface of an affinity column. When calcium is removed with a complexing agent, e.g., EDTA, calmodulin undergoes a conformational change allowing the dissociation of the calmodulin-phenothiazine complex and, therefore, permitting the elution of the GUS-CaM fusion protein. The advantages of this approach are the fast, efficient, and economical isolation of the target protein under mild elution conditions, thus preserving the activity of the target protein. Two types of transformation methods were used in this study, namely, the Agrobacterium-mediated system and the viral-vector-mediated transformation system. Copyright 2002 Elsevier Science (USA).

Non-NASA Center↗

Advanced Electromagnetic Methods for Aerospace Vehicles

The imminent destructive threats of Lightning on helicopters and other airborne systems has always been a topic of great interest to this research grant. Previously, the lightning induced currents on the surface of the fuselage and its interior were predicted using the finite-difference time-domain (FDTD) method as well as the NEC code. The limitations of both methods, as applied to lightning, were identified and extensively discussed in the last meeting. After a thorough investigation of the capabilities of the FDTD, it was decided to incorporate into the numerical method a subcell model to accurately represent current diffusion through conducting materials of high conductivity and finite thickness. Because of the complexity of the model, its validity will be first tested for a one-dimensional FDTD problem. Although results are not available yet, the theory and formulation of the subcell model are presented and discussed here to a certain degree. Besides lightning induced currents in the interior of an aircraft, penetration of electromagnetic fields through apertures (e.g., windows and cracks) could also be devastating for the navigation equipment, electronics, and communications systems in general. The main focus of this study is understanding and quantifying field penetration through apertures. The simulation is done using the FDTD method and the predictions are compared with measurements and moment method solutions obtained from the NASA Langley Research Center. Cavity-backed slot (CBS) antennas or slot antennas in general have many applications in aircraft-satellite type of communications. These can be flushmounted on the surface of the fuselage and, therefore, they retain the aerodynamic shape of the aircraft. In the past, input impedance and radiation patterns of CBS antennas were computed using a hybrid FEM/MoM code. The analysis is now extended to coupling between two identical slot antennas mounted on the same structure. The predictions are performed using both the hybrid FEM/MoM and the FDTD NEWS code. The results are compared with each other as well as with measurements performed in the ElectroMagnetic Anechoic Chamber (EMAC) of ASU. In addition to self and mutual impedances versus frequency, the comparisons include mutual coupling S(sub 12) as a function of distance for various slot orientations.

Balanis, Constantine A.↗

Applications of Fractal Analytical Techniques in the Estimation of Operational Scale

The observational scale and the resolution of remotely sensed imagery are essential considerations in the interpretation process. Many atmospheric, hydrologic, and other natural and human-influenced spatial phenomena are inherently scale dependent and are governed by different physical processes at different spatial domains. This spatial and operational heterogeneity constrains the ability to compare interpretations of phenomena and processes observed in higher spatial resolution imagery to similar interpretations obtained from lower resolution imagery. This is a particularly acute problem, since longterm global change investigations will require high spatial resolution Earth Observing System (EOS), Landsat 7, or commercial satellite data to be combined with lower resolution imagery from older sensors such as Landsat TM and MSS. Fractal analysis is a useful technique for identifying the effects of scale changes on remotely sensed imagery. The fractal dimension of an image is a non-integer value between two and three which indicates the degree of complexity in the texture and shapes depicted in the image. A true fractal surface exhibits self-similarity, a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution, and the slope of the fractal dimension-resolution relationship would be zero. Most geographical phenomena, however, are not self-similar at all scales, but they can be modeled by a stochastic fractal in which the scaling properties of the image exhibit patterns that can be described by statistics such as area-perimeter ratios and autocovariances. Stochastic fractal sets relax the self-similarity assumption and measure many scales and resolutions to represent the varying form of a phenomenon as the pixel size is increased in a convolution process. We have observed that for images of homogeneous land covers, the fractal dimension varies linearly with changes in resolution or pixel size over the range of past, current, and planned space-borne sensors. This relationship differs significantly in images of agricultural, urban, and forest land covers, with urban areas retaining the same level of complexity, forested areas growing smoother, and agricultural areas growing more complex as small pixels are aggregated into larger, mixed pixels. Images of scenes having a mixture of land covers have fractal dimensions that exhibit a non-linear, complex relationship to pixel size. Measuring the fractal dimension of a difference image derived from two images of the same area obtained on different dates showed that the fractal dimension increased steadily, then exhibited a sharp decrease at increasing levels of pixel aggregation. This breakpoint of the fractal dimension/resolution plot is related to the spatial domain or operational scale of the phenomenon exhibiting the predominant visible difference between the two images (in this case, mountain snow cover). The degree to which an image departs from a theoretical ideal fractal surface provides clues as to how much information is altered or lost in the processes of rescaling and rectification. The measured fractal dimension of complex, composite land covers such as urban areas also provides a useful textural index that can assist image classification of complex scenes.

Emerson, Charles W.↗

Integrated Effects of Site Hydrology and Vegetation on Exchange Fluxes and Nutrient Cycling at a Coastal Terrestrial‐Aquatic Interface

Abstract The complex interactions among soil, vegetation, and site hydrologic conditions driven by precipitation and tidal cycles control the biogeochemical transformations and bi‐directional exchange of carbon and nutrients across the terrestrial–aquatic interfaces (TAIs) in coastal regions. This study uses a highly mechanistic model, Advanced Terrestrial Simulator (ATS)‐PFLOTRAN, to explore how these interactions affect exchanges of materials and carbon and nitrogen cycling. We used a transect in the Chesapeake Bay region that spans zones of open water, coastal wetland, transition, and upland forest. We designed several simulation scenarios to parse the effects of the individual controlling factors and the sensitivity of carbon cycling to reaction rate parameters derived from laboratory experiments. Our simulations reveal an active zone for carbon cycling under the transition zones between the wetland and the upland. Evapotranspiration is found to enhance the exchange fluxes between the surface and subsurface domains, resulting in a higher dissolved oxygen concentration in the TAIs. The transport of organic carbon derived from plant leaves and roots provide an additional source of organic carbon needed for the aerobic respiration and denitrification processes in the TAIs. The variability in reaction rate parameters associated with microbial activities is also found to play a dominant role in controlling the heterogeneity and dynamics of the simulated redox conditions. This modeling‐focused exploratory study enabled us to better understand the complex interactions among soil, water and microbes that govern the hydro‐biogeochemical processes at the TAIs, which is an important step toward representing coastal ecosystems in larger‐scale Earth system models.

54 ENVIRONMENTAL SCIENCES↗

PRODEM: An Annual Series of Summer DEMs (2019 through 2022) of the Marginal Areas of the Greenland Ice Sheet

Surface topography across the marginal zone of the Greenland Ice Sheet is constantly evolving in response to changing weather, season, climate, and ice dynamics. However, current digital elevation models (DEMs) for the ice sheet are usually based on data from a multi-year period, thus obscuring these changes over time. Here we present four 500 m resolution summer DEMs (PRODEMs) of the Greenland Ice Sheet marginal zone for 2019 through 2022. The PRODEMs cover the marginal zone from the ice edge to 50 km inland, hence capturing all Greenland outlet glaciers. Each PRODEM is based on data fusion of CryoSat-2 radar altimetry and ICESat-2 laser altimetry using regionally varying kriging of elevation anomalies relative to ArcticDEM. The PRODEMs are validated using leave-one-out cross-validation, and PRODEM19 is further validated against an external data set, showcasing their ability to correctly represent surface elevations within the associated spatially varying prediction uncertainties. We observe a general lowering of surface elevations during the 4-year PRODEM period, but the spatial pattern of change is highly complex and with annual changes superimposed. The PRODEMs enable detailed studies of the marginal ice sheet elevation changes. With their high spatio-temporal resolution, the PRODEMs will be of value to a wide range of researchers and users studying ice sheet dynamics and monitoring how the ice sheet responds to changing environmental conditions. PRODEMs from summer 2019 through 2022 are available at https://doi.org/10.22008/FK2/52WWHG (Winstrup, 2024), and we plan to annually update the product henceforth.

Digital Elevation Models↗

Meso-beta scale numerical simulation studies of terrain-induced jet streak mass/momentum perturbations

Work performed during the report period is summarized. The first numerical experiment which was performed on the North Carolina Supercomputer Center's CRAY-YMP machine during the second half of FY92 involved a 36 hour simulation of the CCOPE case study. This first coarse-mesh simulation employed the GMASS model with a 178 x 108 x 32 matrix of grid points spaced approximately 24 km apart. The initial data was comprised of the global 2.5 x 2.5 degree analyses as well as all available North American rawinsonde data valid at 0000 UTC 11 July 1981. Highly-smoothed LFM-derived terrain data were utilized so as to determine the mesoscale response of the three-dimensional atmosphere to weak terrain forcing prior to including the observed highly complex terrain of the northern Rocky Mountain region. It was felt that the model should be run with a spectrum of terrain geometries, ranging from observed complex terrain to no terrain at all, to determine how crucial the terrain was in forcing the mesoscale phenomena. Both convection and stratiform (stable) precipitation were not allowed in this simulation so that their relative importance could be determined by inclusion in forth-coming simulations. A full suite of planetary boundary layer forcing was allowed in the simulation, including surface sensible and latent heat fluxes employing the Blakadar PBL formulation. The details of this simulation, which in many ways could be considered the control simulation, including the important synoptic-scale, meso-alpha scale, and meso-beta scale circulations is described. These results are compared to the observations diagnosed by Koch and his colleagues as well as hypotheses set forth in the project proposal for terrain-influences upon the jet stream and their role in the generation of mesoscale wave phenomenon. The fundamental goal of the analyses being the discrimination among background geostrophic adjustment, terrain influences, and shearing instability in the initiation and maintainance of mesoscale internal wave phenomena. Based upon these findings, FY93 plans are discussed. A review of linear theory and theoretical modeling of a geostrophic zonal wind anomaly is included.

Lin, Yuh-Lang↗

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials

Atomic disorder can strongly influence material properties such as charge transport, optical response, and catalytic activity. However, efficiently modeling these disorder effects remains challenging for first-principles methods due to the cost of sampling large configurational spaces and computing complex physical quantities. Recent advances of machine learning techniques, particularly graph neural networks (GNNs), has enabled the efficient and accurate predictions of complex material properties, offering promising tools for studying disordered systems. In this work, we present a general machine-learning-assisted computational framework that integrates equivariant GNNs with Monte Carlo simulations to compute the thermodynamic and ensemble-averaged functional properties of disordered materials. Using the surface-termination-disordered MXene monolayer Ti 3 C 2 T 2–x as a representative system, we find that electrical conductivity exhibits an emergent peak near the order–disorder phase transition temperature due to the interplay between electron scattering and doping. In contrast, optical conductivity remains largely insensitive to local atomic disorder and reflects the global surface chemical composition. These results highlight the role of atomic disorder in affecting material properties and demonstrate the potential of our approach for statistically modeling disorder effects in a wide range of materials such as high-entropy alloys and spin liquids.

MXene↗

Probing supersymmetric black holes with surface defects

It has long been conjectured that the large N deconfinement phase transition of $\mathcal{N}$ = 4 SU(N) super-Yang-Mills corresponds via AdS/CFT to the Hawking-Page transition in which black holes dominate the thermal ensemble, and quantitative evidence of this has come through the recent matching of the superconformal index of $\frac{1}{16}$-BPS states to the supersymmetric black hole entropy. Here we introduce the half-BPS Gukov-Witten surface defect as a probe of the superconformal index, which also serves as an order parameter for the deconfinement transition. This can be studied directly in field theory as a modification of the usual unitary matrix model or in the dual description as a D3-brane probe in the background of a (complex) supersymmetric black hole. Using a saddle point approximation, we determine our defect index in the large N limit as a simple function of the chemical potentials and show independently that it is reproduced by the renormalized action of the brane in the black hole background. Along the way, we also comment on the Cardy limit and the thermodynamics of the D3-brane in the generalized ensemble. The defect index sharply distinguishes between the confining and the deconfining phases of the gauge theory and thus is a supersymmetric non-perturbative order parameter for these large N phase transitions which deserves further investigation. Finally, our work provides an example where the properties of a black hole coupled to an external system can be analyzed precisely.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Quantum sensing of paramagnetic analytes by nanodiamonds in levitated microdroplets and aqueous solutions

Nanodiamonds (ND) hosting negatively charged nitrogen-vacancy (NV-) color centers have received attention for applications in magnetic field, electric field, chemical, and bio-sensing. The versatility of these probes is their excellent room-temperature optical and spin properties, along with their small size, functionalized surfaces and resistance to bleaching, making them ideal as nanoscopic sensors in picoliter volumes (e.g. single cells, but also microcompartments and aerosols). For quantitative ND-NV- sensing of paramagnetic analytes in such contexts, however, there remains an incomplete understanding of how factors related to the aqueous phase environment control detection efficiency. To address this, optically detected magnetic resonance (ODMR) is measured in bulk macroscale solutions and single levitated microdroplets as a function of Gd+3 concentration (340 nM to 1.5 mM), nanodiamond size, pH, competitor ions, and ligands. The ODMR response to [Gd+3] is found to be nonlinear, and pH, ND and sample volume dependent; indicating the detection of Gd+3 requires efficient adsorption of the analyte to the diamond surface. Langmuir adsorption isotherms embedded in a quantitative photophysical model links the ODMR response to adsorption thermodynamics of Gd+3. The equilibrium constant for Gd+3 adsorption to a carboxylated ND surface is determined to be (1 ± 0.5) x 105 M-1 corresponding to a free energy of adsorption of (-28 ± 1) kJ mol-1. These results provide general insight into how complex aqueous and microscale environments impact nanodiamond based quantum sensing modalities, and portend their application as quantitative chemical sensors in microenvironments.

Brown, Emily K↗

Probing the Critical Nucleus Size in the Metal-Insulator Phase Transition of VO 2

In a first-order phase transition, critical nucleus size governs nucleation kinetics, but the direct experimental test of the theory and determination of the critical nucleation size have been achieved only recently in the case of ice formation in supercooled water. The widely known metal-insulator phase transition (MIT) in strongly correlated VO 2 is a first-order electronic phase transition coupled with a solid-solid structural transformation. It is unclear whether classical nucleation theory applies in such a complex case. Here we directly measure the critical nucleus size of the MIT by introducing size-controlled nanoscale nucleation seeds with focused ion irradiation at the surface of a deeply supercooled metal phase of VO 2 . The results compare favorably with classical nucleation theory and are further explained by phase-field modeling. This Letter validates the application of classical nucleation theory as a parametrizable model to describe phase transitions of strongly correlated electron materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Tensorized Interior Radiative Heat Transfer for a Scalable and Calibrated Building Energy Simulator

Building energy simulation is a critical tool for developing and testing advanced control strategies, such as Reinforcement Learning (RL), to provide demand flexibility and affordable energy costs. The recently introduced Smart Buildings Control Suite (sbsim) provides a lightweight, scalable, and data-calibrated simulation environment based on a 2D finite-difference model. However, the initial model primarily focused on conductive and convective heat transfer, neglecting the significant impact of long-wave radiative heat exchange between interior surfaces. This paper presents a significant extension to the sbsim framework by incorporating a physically-grounded model for interior radiative heat transfer. Our primary contribution is the development and integration of a fully tensorized radiative heat transfer module, which preserves the computational efficiency and scalability of the original simulator. This was achieved by developing a pipeline for view factor calculation, including an algorithm to identify directly seeing surfaces within complex floor plans, and formulating the net radiation equations for efficient execution on modern hardware accelerators. We validate the numerical accuracy of our tensorized implementation by comparing its results against a traditional iterative approach, demonstrating identical outcomes. This enhancement increases the physical fidelity of sbsim, enabling more accurate training of RL agents for building energy optimization.

Ham, Sang woo↗