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DOE OSTI2025

Fundamental Interactions of Bimetallic Cu x Pd y ( x + y = 4) Clusters Supported on the α-WC(0001) Surface and Their Performance for CO 2 Adsorption and Dissociation

The tungsten carbide α-WC(0001) surface, an active system for the activation of H 2 and important hydrogenation processes involving unsaturated hydrocarbons, can serve as a support of bimetallic clusters to produce materials with unique catalytic properties, opening routes for a wide range of technical applications. In particular, Cu x Pd y clusters are of particular interest because they combine metals with different properties. A stochastic method was applied to obtain the geometry of Cu x Pd y (x + y = 4) bare clusters, evaluating thousands of possibilities to obtain stable structures, yielding one isomer for Cu 4 , Cu 2 Pd 2 , Cu 1 Pd 3 , and Pd 4 and two isomers for Cu 3 Pd 1 . These clusters were supported on C and W terminations of the tungsten carbide (0001) surface, exploring all of the binding possibilities. The adsorption energies on the C and W terminations are in the ranges from −2.51 to −3.02 eV and from −2.26 to −3.30 eV, respectively. The strongest and weakest binding was seen for monometallic Cu 4 and Pd 4 clusters on both C and W terminations, while the Cu-Pd bimetallics have intermediate adsorption energies but lack a clear trend in terms of composition. The location of Cu x Pd y clusters over the (0001) surface induces a decrease in the work function relative to the pristine surface, while the cluster-surface Bader charge transfer and variations in the partial density of states point to changes in the electronic structure of the carbide atoms upon binding of the metallic clusters. The d-band center of the Cu x Pd y deposited on WC(0001) indicates an intermediate reactivity among Cu(111) and Pd(111) surfaces, modulating the reactivity with small numbers of Cu and Pd atoms, i.e., atom economy in catalyst design. The likelihood of existence of the most stable Cu x Pd y (x + y = 4) clusters in the temperature range of 298-400 K is 100%. The composite Cu x Pd y /α-WC(0001) (x + y = 4), is a nontrivial system since 22 isomers are needed to completely describe its structural properties. Among the isomers, seven structures are necessary to represent Cu 3 Pd 1 /α-WC(0001), five for Pd 4 /α-WC(0001), two for Cu 4 /α-WC(0001), and four for Cu 2 Pd 2 /α-WC(0001) and Cu 1 Pd 3 /α-WC(0001). The large number of cluster isomers supported on the tungsten carbide surface opens the door for several applications in the heterogeneous catalysis of the Cu x Pd y /α-WC(0001) composite, with the possibility of modulating the geometric, electronic, and chemical properties according to a desired application. Test studies for the adsorption of CO 2 indicate that the Cu x Pd y /α-WC(0001) composites are highly active for the adsorption and decomposition of the molecule, with bimetallic and admetal-carbide interactions playing a key role in the binding performance. In conclusion, this high activity indicates that these systems should be useful as catalysts for the conversion of CO 2 to oxygenates or light alkanes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Quantifying Groundwater Response and Uncertainty in Beaver‐Influenced Mountainous Floodplains Using Machine Learning‐Based Model Calibration

Abstract Beavers ( Castor canadensis ) alter river corridor hydrology by creating ponds and inundating floodplains, and thereby improving surface water storage. However, the impact of inundation on groundwater, particularly in mountainous alluvial floodplains with permeable gravel/cobble layers overlain by a soil layer, remains uncertain. Numerical modeling across various floodplain structures considers topographic and sediment complexity and multidirectional flow, linking inundation to groundwater response. This study develops a model‐data integration workflow to address uncertainty in groundwater response to beaver‐induced inundations in a mountainous alluvial floodplain in the Upper Colorado River Basin. Uncertain factors include seasonal hydrologic dynamics, hydraulic conductivities, floodplain structures, and meteorological forcings. We employed an ensemble of groundwater models, based on geophysical and hydrologic data, with machine learning‐based calibration using a neural density estimator. This allowed us to quantify the vertical flux from the soil layer to the permeable gravel bed, the down‐valley underflow within the gravel bed, and their ratios. Results show a significant increase in the vertical flux relative to down‐valley underflow, from 2 during dry pond periods to 20 during wet periods, serving as an analogy for conditions without and with beaver ponds. The study highlights the influence of floodplain structure on groundwater storage, water balance, and water quality impacted by beaver ponds. A thick gravel bed layer, with a large down‐valley underflow, minimizes the effect of beaver‐induced inundation on water quality. We emphasize the need for field‐scale measurements of floodplain structure and improved characterization of evapotranspiration changes to reduce uncertainty in groundwater response. Plain Language Summary Beavers change the flow of water in river corridors by creating ponds, expanding wetlands, and flooding floodplains. This increases surface water area, promotes plant growth, and enhances biodiversity. However, the impact of this flooding on groundwater flow is not well understood, especially in mountainous areas with gravel layers where water moves easily beneath soil. In this study, we used numerical modeling to investigate how beaver ponds influence groundwater in a mountainous floodplain of the Upper Colorado River Basin. We adapted a machine learning method to validate our numerical models using multiple field data sets. Our findings show that beaver ponds significantly increase vertical water flow from the soil to the gravel during wet periods, compared to when the ponds are fully drained. The study also highlights the importance of floodplain structure in controlling both water flow in gravel layers along the river direction and vertical flow from the soil to the gravel with the presence of beavers. To reduce uncertainty in groundwater response, we emphasize the need for more field‐scale measurements of floodplain structure, hydraulic properties, and evapotranspiration changes. Key Points Floodplain structures and hydraulic conductivities are important for groundwater response with beaver ponds in mountainous floodplains Large down‐valley underflow in permeability‐stratified floodplains reduces beaver‐induced impacts on groundwater storage and water quality Machine learning‐based model calibration methods are effective for estimating posterior distributions of groundwater model parameters

Wang, Lijing↗

DOE OSTI2022

Magnetic excitations, nonclassicality, and quantum wake spin dynamics in the Hubbard chain

Recent work has demonstrated that quantum Fisher information (QFI), a witness of multipartite entanglement, and magnetic Van Hove correlations G(r,t), a probe of local real-space real-time spin dynamics, can be successfully extracted from inelastic neutron scattering on spin systems through accurate measurements of the dynamical spin structure factor S(k,ω). In this work, we apply theoretically these ideas to the half-filled Hubbard chain with nearest-neighbor hopping, away from the strong-coupling limit. This model has nontrivial redistribution of spectral weight in S(k,ω) going from the noninteracting limit (U = 0) to strong coupling (U→∞), where it reduces to the Heisenberg quantum spin chain. We use the density matrix renormalization group to find S(k,ω), from which QFI is then calculated. We find that QFI grows with U. With realistic energy resolution it becomes capable of witnessing bipartite entanglement above U=2.5 (in units of the hopping), where it also changes slope. This point is also proximate to slope changes of the bandwidth W(U) and the half-chain von Neumann entanglement entropy. We compute G(r,t) by Fourier transforming S(k,ω). The results indicate a crossover in the short-time short-distance dynamics at low U characterized by ferromagnetic light-cone wavefronts, to a Heisenberg-type behavior at large U featuring antiferromagnetic light cones and spatially period-doubled antiferromagnetism. We find this crossover has largely been completed by U=3. Our results thus provide evidence that, in several aspects, the strong-coupling limit of the Hubbard chain is reached qualitatively already at a relatively modest interaction strength. We discuss experimental candidates for observing the G(r,t) dynamics found at low U.

1-dimensional systems↗

DOE OSTI2023

Elementary excitations of a system of one-dimensional chiral fermions with short-range interactions

Here, we study general features of the excitation spectrum of a system of one-dimensional chiral spinless fermions with short-range interactions. We show that the nature of the elementary excitations of such a system depends strongly on the nonlinearity of the underlying dispersion of the fermions. In the case of quadratic nonlinearity, the low-momentum excitations are essentially fermionic quasiparticles and quasiholes, whereas the high-momentum ones are classical harmonic waves and solitons. In the case of cubic nonlinearity, the nature of the elementary excitations does not depend on momentum and is determined by the strength of the interactions. At a certain critical value of the interaction strength, the excitation spectrum changes qualitatively, pointing to a dynamic phase transition in the system.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Complexity Phase Diagram for Interacting and Long-Range Bosonic Hamiltonians

Here, we classify phases of a bosonic lattice model based on the computational complexity of classically simulating the system. We show that the system transitions from being classically simulable to classically hard to simulate as it evolves in time, extending previous results to include on-site number-conserving interactions and long-range hopping. Specifically, we construct a complexity phase diagram with easy and hard “phases” and derive analytic bounds on the location of the phase boundary with respect to the evolution time and the degree of locality. We find that the location of the phase transition is intimately related to upper bounds on the spread of quantum correlations and protocols to transfer quantum information. Remarkably, although the location of the transition point is unchanged by on-site interactions, the nature of the transition point does change. Specifically, we find that there are two kinds of transitions, sharp and coarse, broadly corresponding to interacting and noninteracting bosons, respectively. Our Letter motivates future studies of complexity in many-body systems and its interplay with the associated physical phenomena.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Prediction of s ± -Wave Superconductivity Enhanced by Electronic Doping in Trilayer Nickelates La 4 Ni 3 O 10 under Pressure

Motivated by the recently reported signatures of superconductivity in trilayer La 4 ⁢Ni 3 ⁢O 10 under pressure, here we comprehensively study this system using ab initio and random-phase approximation techniques. Without electronic interactions, the Ni d 3z 2 –r 2 orbitals show a bonding-antibonding and nonbonding splitting behavior via the O p z orbitals inducing a “trimer” lattice in La 4⁢ Ni 3 ⁢O 10 , analogous to the dimers of La 3 ⁢Ni 2 ⁢O 7 . The Fermi surface consists of three electron sheets with mixed e g orbitals, and a hole and an electron pocket made up of the d 3⁢z 2 –r 2 orbital, suggesting a Ni two-orbital minimum model. In addition, we find that superconducting pairing is induced in the s ± -wave channel due to partial nesting between the M = (π,π) centered pockets and portions of the Fermi surface centered at the Γ = (0,0) point. With changing electronic density n, the s ± instability remains leading and its pairing strength shows a domelike behavior with a maximum around n = 4.2 ( ~6.7% electron doping). The superconducting instability disappears at the same electronic density as that in the new 1313 stacking La 3 ⁢Ni 2 ⁢O 7 , correlated with the vanishing of the hole pocket that arises from the trilayer sublattice, suggesting that the high-T c superconductivity of La 3⁢ Ni 2 ⁢O 7 does not originate from a trilayer and monolayer structure. Furthermore, we confirm the experimentally proposed spin state in La 4 ⁢Ni 3 ⁢O 10 with an in-plane (π, π) order and antiferromagnetic coupling between the top and bottom Ni layers, and spin zero in the middle layer.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

TICC Clustering Library v.1.0

SAND2024-01234O TICC is a clustering algorithm that labels a sequence of data points according to numerical properties. This library is a Python implementation of the algorithm described in "Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data" (Hallac et al. 2017). It includes documentation, performance improvements, examples, and test coverage. This library allows users to automatically segment a series of multivariate data points according to their covariance—that is, the way the values at each data point are changing in relation to one another. This is useful for identifying periods in which a system is behaving. For example, if a sensor is measuring a car's velocity, steering wheel angle, braking and acceleration, TICC can determine when the car was stopped, beginning/exiting a turn, slowing or accelerating at an intersection, or driving on straight or curved roads. TICC can be applied to measure multiple quantities at known times. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525

Dalbey, Keith↗

DOE OSTI2024

New U.S. Data Tools are Playing a Crucial Role in Decarbonizing Buildings at Speed, Scale, and Low Cost

Preparing buildings for retrofits traditionally requires expensive on-site audits or timeintensive simulation models. As a result, the majority of buildings fail to pursue cost-saving retrofits. To address these barriers, the U.S. Department of Energy (DOE) has introduced the Building Efficiency Targeting Tool for Energy Retrofits (BETTER)-a new, free, on-line tool that utilizes a data-driven analytical engine and user-friendly web interface to automatically analyze a building's monthly energy usage in response to weather conditions. The tool benchmarks a building's electric and fossil energy usage against peers; estimates energy, cost, and emissions reductions at the building and portfolio levels; recommends energy efficiency measures; and prioritizes buildings for net-zero energy retrofits. Thanks to interoperability with the DOE's Standard Energy Efficiency Data (SEED) platform, BETTER is supporting U.S. jurisdictions to prepare buildings for retrofit at speed, scale, and low cost to comply with energy policies. This paper discusses the use of BETTER and SEED by one of the branches of the California state government to streamline a retrofit program across 455 public non-residential buildings to align with state goals to reduce greenhouse gas emissions. It describes the organization's challenge to reduce energy consumption across a geographically diverse, aging portfolio; explores how BETTER and SEED improved workflow efficiency; presents preliminary results, including avoiding audit costs of $3.28 million and developing the groundwork for retrofit projects estimated to prevent emission of 2,271 t CO2e annually; and provides guidance for other jurisdictions seeking similar results.

BETTER↗

DOE OSTI2024

Opportunities for Earth Observation to Inform Risk Management for Ocean Tipping Points

Abstract As climate change continues, the likelihood of passing critical thresholds or tipping points increases. Hence, there is a need to advance the science for detecting such thresholds. In this paper, we assess the needs and opportunities for Earth Observation (EO, here understood to refer to satellite observations) to inform society in responding to the risks associated with ten potential large-scale ocean tipping elements: Atlantic Meridional Overturning Circulation; Atlantic Subpolar Gyre; Beaufort Gyre; Arctic halocline; Kuroshio Large Meander; deoxygenation; phytoplankton; zooplankton; higher level ecosystems (including fisheries); and marine biodiversity. We review current scientific understanding and identify specific EO and related modelling needs for each of these tipping elements. We draw out some generic points that apply across several of the elements. These common points include the importance of maintaining long-term, consistent time series; the need to combine EO data consistently with in situ data types (including subsurface), for example through data assimilation; and the need to reduce or work with current mismatches in resolution (in both directions) between climate models and EO datasets. Our analysis shows that developing EO, modelling and prediction systems together, with understanding of the strengths and limitations of each, provides many promising paths towards monitoring and early warning systems for tipping, and towards the development of the next generation of climate models.

Wood, Richard A. (ORCID:0000000239609513)↗

DOE OSTI2022

Turning points in the age–metallicity relations – created by late satellite infall and enhanced by radial migration

ABSTRACT The present-day age–metallicity relation (AMR) is a record of the star formation history of galaxies, as this traces the chemical enrichment of the gas over time. We use a zoomed-in cosmological simulation that reproduces key signatures of the Milky Way (MW), g2.79e12 from the NIHAO-UHD project, to examine how stellar migration and satellite infall shape the AMR across the disc. We find in the simulation, similar to the MW, the AMR in small spatial regions (R, z) shows turning points that connect changes in the direction of the relations. The turning points in the AMR in the simulation are a signature of late satellite infall. This satellite infall has a mass radio similar as that of the Sagittarius dwarf to the MW (∼0.001). Stars in the apex of the turning points are young and have nearly not migrated. The late satellite infall creates the turning points via depositing metal-poor gas in the disc, triggering star formation of stars in a narrow metallicity range compared to the overall AMR. The main effect of radial migration on the AMR turning points is to widen the metallicity range of the apex. This can happen when radial migration brings stars born from the infallen gas in other spatial bins, with slightly different metallicities, into the spatial bin of interest. These results indicate that it is possible that the passage of the Sagittarius dwarf galaxy played a role in creating the turning points that we see in the AMR in the Milky Way.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

A first-principles investigation of point defect structure and energetics in ThO 2

The structure and energetics of charged point defects in thorium dioxide (ThO 2 ) have been investigated using the density functional theory (DFT) and phonon simulations. DFT simulations were performed under both zero-pressure and constant volume conditions. Termed as the free volume change of the point defects, the change in volume of the supercell has been computed in the zero-pressure case. Supercell expansion was observed with the increase of the (nominal) charge state of anion (O) interstitials and cation (Th) vacancies from neutral to its maximum. On the contrary, contraction of the supercell has been observed with anion vacancies and cation interstitials as the defect charge increases. The supercell volume change with respect to the charge state has been correlated with the resulting defect energetics. It has been observed that, as the defect charge increased, the internal energy and entropy of defect formation of the cation vacancies and anion interstitials were found to increase, while that of the cation interstitials and anion vacancies decreased. Here, the temperature dependence of internal energy and entropy has also been examined. It was found that, as the temperature increases, the internal energies of the formation of cation vacancies and anion interstitials decrease, while those of the cation interstitials and anion vacancies increase. An opposite observation is seen for the entropies of formation defects when above room temperatures.

42 ENGINEERING↗

DOE OSTI2021

Forecasting Dynamic Line Rating with Spatial Variation Considerations

Dynamic line rating (DLR) is a technology that allows the ampacity of an electrical conductor to be calculated using real-time or forecasted weather conditions. Historically, the ampacity of a conductor has been determined using a static line rating method which assumes conservative weather assumptions. Therefore, not only can DLR give a more accurate measurement of the true ampacity of a conductor, but it can also increase its ampacity during weather conditions with greater thermal mitigations. The two primary cooling factors in the ampacity calculations are wind speed and direction. In complex terrain, wind speed and direction can have large variations over short distances. Therefore, accurately identifying the limiting span of a transmission line requires high spatial resolution of the wind along its path. One solution is to install dense weather stations along their path, though this can become costly over long distances. Therefore, researchers have investigated the use of Computation Fluid Dynamic (CFD) simulations to accurately compute the wind field along the path of a transmission line and use these results to identify the limiting section of the conductor. This work presents a case study that evaluates the coupling of CFD simulations and forecasted weather simulations using the High-Resolution Rapid Refresh (HRRR) model points over a 2-year span within a region in south eastern Idaho. The primary goal of the work is the evaluation of the number of HRRR model points used, i.e., weather stations, along the path of the line and the accuracy of the resulting DLR ampacity. This was done using 4, 10, 17, 26, and 35 HRRR model points along two transmission line paths. The results indicate that as the number of model points are increased, the DLR ampacity of the lines decrease, yet converge as more points are added and demonstrate little change with additional HRRR points. It is expected that these results can help transmission line operators identify the number of weather stations that must be installed when coupled with CFD simulations and DLR ampacity to ensure accurate ratings and safe operations.

17 WIND ENERGY↗

DOE OSTI2021

Forecasting Dynamic Line Rating with Spatial Variation Considerations

Dynamic line rating (DLR) is a technology that allows the ampacity of an electrical conductor to be calculated using real-time or forecasted weather conditions. Historically, the ampacity of a conductor has been determined using a static line rating method which assumes conservative weather assumptions. Therefore, not only can DLR give a more accurate measurement of the true ampacity of a conductor, but it can also increase its ampacity during weather conditions with greater thermal mitigations. The two primary cooling factors in the ampacity calculations are wind speed and direction. In complex terrain, wind speed and direction can have large variations over short distances. Therefore, accurately identifying the limiting span of a transmission line requires high spatial resolution of the wind along its path. One solution is to install dense weather stations along their path, though this can become costly over long distances. Therefore, researchers have investigated the use of Computation Fluid Dynamic (CFD) simulations to accurately compute the wind field along the path of a transmission line and use these results to identify the limiting section of the conductor. This work presents a case study that evaluates the coupling of CFD simulations and forecasted weather simulations using the High-Resolution Rapid Refresh (HRRR) model points over a 2-year span within a region in south eastern Idaho. The primary goal of the work is the evaluation of the number of HRRR model points used, i.e., weather stations, along the path of the line and the accuracy of the resulting ampacity. This was done using 4, 10, 17, 26, and 35 HRRR model points along two transmission line paths. The results indicate that as the number of model points are increased, the DLR ampacity of the lines decrease, yet converge as more points are added and demonstrate little change with additional HRRR points. It is expected that these results can help transmission line operators identify the number of weather stations that must be installed when coupled with CFD simulations and DLR ampacity to ensure accurate ratings and safe operations.

17 WIND ENERGY↗

DOE OSTI2025

Reorganization of Water at Aqueous Aluminum Chloride (AlCl 3 ) Interfaces: Vibrational Sum Frequency Generation and Molecular Dynamics Simulations

AlCl 3 hydration states and complexation are not well understood both in solutions and at the air–aqueous interface despite their potential significance in natural waters and their industrial and energy-related applications. Here, we investigated Al 3+ and Cl – ion behaviors in an AlCl 3 aqueous bulk solution and at the air–aqueous interface using interface-selective vibrational sum frequency generation (SFG), Raman and infrared spectroscopies, molecular dynamics (MD) simulation, as well as molecular-informed reduced modeling. Our reduced modeling reveals relatively long-range effects for Al 3+ as compared to monovalent ions such as Na + indicating that the interfacial depth of trivalent ions can be significantly larger than that of monovalent ions at the air–water interface. MD simulations reveal interfacial stratification and multiple layering of the ions. Compression of the Al 3+ and Cl – distributions with increasing concentrations from 0.5 to 2.5 m is also observed in the subsurface regions. Significant SSP- and PPP-polarized SFG OH spectral intensity increases are observed from 0.5 to 1.5 m and 0.5 to 2.5 m, respectively, indicative of interfacial depth increases and a change in average orientation above 1.5 m. Extensive evaluation of SFG spectra, Fresnel-corrected using several approaches, shows the same trends. The nonmonotonic trend points to a changing structure in surface and subsurface water orientation and hydrogen bonding environment generally consistent with the MD simulation of stratification and water orientation changes. Furthermore, solvent-shared ion pairing is implicated with MD simulation radial distribution analysis and consistent with infrared spectral identification of the hexaaqua aluminum ion in the solution phase. Spectral evidence of a strong Al 3+ hydration shell and the acidic behavior of the Al 3+ ions is obvious in the Raman and infrared spectra of the bulk solution. In conclusion, we show that the MD dipole potential is directly related to the MD second-order susceptibility of the interface, χ SFG–MD (2) , both of which correlate up to ∼35 Å with the spectral observations of increasing and then saturating intensities, suggesting that both ion stratification and interfacial depth determine the water orientations at an air–water interface of 1-3 electrolyte solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

BENEFIT with Northeastern University: HVAC Hardware-in-the-Loop Experimental Testing of a Heat Pump and Air Conditioner

This dataset includes HVAC Hardware-in-the-Loop (HIL) experimental results for a single stage, SEER 16, HSPF 9.5, 3-ton single-speed air source heat pump with 15 kW of backup auxiliary heating tested in both cooling and heating mode, and a two stage, SEER 21, 2-ton central air conditioner tested in cooling mode for a set of outdoor temperatures and indoor setpoint temperatures. In addition to these tests, experimental tests focused on the operation of auxiliary heating for the heat pump for winter condition were also conducted. The laboratory experiments for transient testing of the heat pump and air conditioner were conducted using the two HIL systems in the Systems Performance Laboratory (SPL) at NREL’s Energy Systems Integration Facility (ESIF). Further information on laboratory design and capabilities of the SPL along with the architecture of HVAC HIL system can be found in: Sparn, B. F. 2018. Laboratory Resources and Techniques to Evaluate Smart Home Technology (No. NREL/CP-5500-71696). National Renewable Energy Laboratory (NREL), Golden, CO (United States). https://www.nrel.gov/docs/fy18osti/71696.pdf and the experimental setup and validation of HVAC HIL platform can be found in: Ramaraj, S. and Sparn, B. 2022. Validation of HVAC Hardware-In-the-Loop Simulation for Advanced Control Strategies in Smart Homes (No. NREL/CP-5500-82562). National Renewable Energy Lab (NREL), Golden, CO (United States). https://www.nrel.gov/docs/fy22osti/82562.pdf. These experimental results can be used to validate how we currently model the cycling behavior of heat pumps and air conditioners. Additionally, many demand response programs implement heat pump and air conditioner control by changing the thermostat set point – these data may also be used to verify our models for heat pump and air conditioner demand response control are implemented correctly. The Test_Matrix file describes all the indoor and outdoor test conditions for heat pump and air conditioner and the file names of data sets include information about the test conditions. A wide range of outdoor air temperatures were chosen to accommodate summer and winter conditions. In addition to operating the HVAC equipment with different outdoor temperatures, we also operate the system with different indoor temperature set points to represent different grid signals or different operating conditions. For cooling conditions, the baseline set point is 72°F. To represent Load Up signals, the setpoint is changed to 68°F. The Load Shed set point is 76°F. For heating conditions, the baseline set point was assumed to be 68°F. The Load add set point is 72°F and the Load shed set point is 64°F. The starting indoor temperature for cooling conditions was set ~2°F above the indoor setpoint temperature so that the equipment turned on quickly. Similarly, the initial indoor temperature was set ~2°F lower than setpoint for heating mode tests to ensure that heating began quickly. The return air temperature was assumed to be equal to the indoor setpoint temperature in all cases. The experimental data are sampled at 1-second intervals. The data from ecobee thermostat at 5-minute interval are resampled and added to the corresponding file. The content of each data set is as follows: • T_Return (C): Measured return air temperature [C] • T_Return_SP (C): Return air temperature setpoint from E+ model, sent to HIL [C] • T_Supply (C): Measured supply air temperature at evaporator outlet [C] • T_Outdoor (C): Measured outdoor air temperature [C] • T_Outdoor_SP (C): Outdoor air temperature setpoint from weather file, sent to HIL [C] • T_Indoor (C): Measured indoor air temperature [C] • T_Indoor_SP (C): Indoor air temperature setpoint from E+ model, sent to HIL [C] • Outdoor Unit Power (W): Measured power of the outdoor unit [W] • Indoor Unit Power (W): Measured power of the indoor unit [W] • Evaporator Airflow Rate (CFM): Measured evaporator or indoor unit airflow rate sent to E+ model [CFM] • Cooling/Heating Capacity (kW): Calculated cooling/heating capacity sent to E+ model [kW] • T_SP_Thermostat (C): Thermostat cooling/heating setpoint temperature [C] • T_Indoor_Thermostat (C): Thermostat indoor air temperature [C]

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Electronic device and method for compressing sampled data

An electronic device for compressing sampled data comprises a memory element and a processing element. The memory element is configured to store sampled data points and sampled times. The processing element is in electronic communication with the memory element and is configured to receive a plurality of sampled data points, a slope for each sampled data point in succession, the slope being a value of a change between the sampled data point and its successive sampled data point, and store the sampled data point in the memory element when the slope changes in value from a previous sampled data point.

Morrow, Mitchell Hedges↗

DOE OSTI2021

Electronic device and method for compressing sampled data

Tohlen, Michael Aaron↗

DOE OSTI2021

Electronic device and method for compressing sampled data

Morrow, Mitchell Hedges↗