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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

From models to reality: a systematic review on simulated and measured residential heat pump energy savings

High-performance HVAC solutions are central to residential energy management. A substantial share of these are electric, reversible-cycle systems, with heat pumps representing the largest portion of current and near-term adoption. This review synthesizes peer-reviewed and grey literature on residential space heating and cooling heat pumps. The academic literature is dominated by modeling (73.8%), with limited field measurement (13.1%). Grey literature from United States serve as a supplemental resource providing measured savings. Conversions from electric-resistance heating consistently show the largest site energy reductions, while oil/propane baselines yield moderate savings, and gas baseline scenario often deliver small and region-dependent savings. This study cross-checks the grey literature measured data with simulation data filtered from the ResStock dataset. The comparison indicates a discrepancy between simulations and measured data: simulated site EUIs are typically lower than measured EUIs, but percentage energy savings fall in similar ranges, implying simulations capture directional effects while underestimating energy use. Factors associated with variability and model–measurement differences include system characterization and control representation (e.g., backup heat engagement, thermostat/setpoint strategies, commissioning/installation quality), occupant behavior, weather normalization, metering scope, and envelope characterization. This paper also outlines the proposed methodology for comparing simulation and measured data for heat pumps. It emphasizes the metrics used for comparison and units harmonization, building characteristics matching, and compact metadata are needed for simulations to match measured data. The proposed methodology is expected to improve the credibility of simulated savings as measured evidence grows.

Yu, Lili↗
DOE OSTI2023

Magnetic and singlet phases in the three-dimensional periodic Anderson Model

Heavy-fermion materials are compounds in which localized f orbitals hybridize with delocalized d ones, leading to quasiparticles with large renormalized masses. The presence of strongly correlated f electrons at the Fermi level may also lead to long-range order, such as magnetism, or unconventional superconductivity. From a theoretical point of view, the “standard model” for heavy-fermion compounds is the periodic Anderson model (PAM). Despite being extensively scrutinized, its thermodynamic properties in three-dimensional (3D) lattices have not been carefully addressed by unbiased methodologies. Here we investigate the 3D PAM employing state-of-the-art finite-temperature auxiliary-field quantum Monte Carlo simulations. Furthermore, we present the behavior of the kinetic energy, the entropy, the specific heat, and the double occupancy as functions of the temperature and the hybridization strength. From these quantities, and by the analysis of the spin-spin correlation functions, we investigate the occurrence of magnetic phase transitions at finite temperatures, and we determine the phase diagram of the model, including the behavior of the Néel temperature as a function of the external parameters.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

An ontology to represent synthetic building occupant characteristics and behavior

Since the introduction of the occupant behavior Drivers-Needs-Actions-Systems (DNAS) framework in 2013, researchers have used the framework or further developed it based on their case studies, which include efforts to collect new data on occupant behaviors. The effort is often costly for the relatively few new data points added. Problems emerge when the already collected data do not meet the modelers' interoperability requirements. Previous studies addressed this issue by developing more sophisticated ontologies that enable integration with other datasets and synthetic data methodologies that would meet unique research applications. This paper presents an extension of the DNAS framework for the representation of synthetic occupant data to support various applications and use cases across the building life cycle. An agent-based modeling application is one of our motivations that requires more elaborate characteristics of an occupant-agent or a group-of-agent. The extension, built upon a review of the literature, introduces new elements to the framework that fall into five categories, including socio-economic, geographical location, activities, subjective values, and individual and collective adaptive actions. On-going research includes identifying occupant datasets and developing data fusion methods to generate synthetic occupants, as well as to demonstrate its applications in agent-based modeling coupled with building performance simulation.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2020

Characterization of Connected Lighting System Potential for Grid Services Under Real-Time Pricing

Increasingly over the last decade, the management of end-use electricity demand has been examined as a potential source of services for the electric power grid beyond contracts with large commercial and industrial customers. Lighting represents about 17\% of U.S. commercial building annual electricity consumption; however, its potential rapid speed of response may position it to uniquely contribute to services that improve the reliability and resilience of the grid. Connected lighting systems (CLS), which build upon solid-state lamp technology, can change state by adjusting power demand more quickly than most other building electricity end uses and could be used as a platform to monitor lighting electricity use and space conditions. But the potential of CLS to provide grid services has not been extensively studied. In this paper, we describe initial research to evaluate the potential of CLS for grid services. We develop a model for CLS using a set of parameters to represent operation behaviors and constraints: maximal power, minimal power, nominal power, ramp rate, and time delay. Parameter values are generated for representative building types. CLS demand curves are constructed, indirectly capturing building occupant preferences for lighting as functions of electricity price. The CLS model and the demand curves are incorporated into a Transactive Control and Coordination (TCC) Platform to simulate CLS providing grid services. Previous research has shown TCC to be a powerful tool to enable end uses to provide grid services through a hybrid economic-control approach. Initial quantitative results will be provided for CLS grid services potential.

Wang, Peng↗
DOE OSTI2025

Electromagnetic moments of 215,217 Bi: Probing shell evolution beyond N = 126

The nuclear properties of bismuth isotopes (Z = 83) , with just one valence proton above the closed spherical shell at (Z = 82) , are expected to be governed by a single unpaired proton. However, already in semimagic 209 Bi (Z = 83, N = 126) , , the magnetic moment (μ) strongly deviates from the single-particle Schmidt value. A near linear decrease in μ with the increase of N after the N = 126 magic number was observed up to N = 130 . In order to test whether this trend is kept at N > 130 and to reveal the underlying mechanisms, an investigation of 215,217 Bi (N = 132, 134) has been undertaken. The magnetic dipole and electric quadrupole moments of the I π = 9/2 - nuclear ground states in these isotopes have been measured for the first time using the in-source resonance-ionization spectroscopy technique at ISOLDE (CERN). It has been shown that the linearly decreasing trend of μ( 209,211,213 Bi g ) is broken in 215,217 Bi with a nearly constant value of μ observed. Experimental data have been compared to calculations in the framework of the configuration-interaction shell model with the monopole-based universal V MU +LS interaction. The peculiarities in the behavior of μ(Bi, 9/2 - ) with increasing neutron number are explained as being due to the shell evolution, change of the neutron orbitals occupancies and strong configuration mixing beyond N = 130 . Also, the difference in the μ trends for bismuth (Z = 83) and astatine (Z = 85) isotopes with N > 126 are reproduced by the shell-model calculations. It is shown that monopole interaction plays noticeable role in the description of the peculiarities of the μ behaviour. Additionally, the extension of the application of the V MU interaction to the μ isotopic trends for heavy nuclei is important for further study of the capabilities of this promising version of the shell-model calculations.

Dipole magnetic moments↗
DOE OSTI2022

Probabilistic Modeling of Commercial Building Occupancy Patterns Using Location-Based Map Data: Preprint

Considering occupancy patterns is crucial to simulate buildings' energy use. Current energy models use inputs that simplify the actual diversity in occupancy into static occupancy patterns and are not able to represent the numerous variations in occupancy patterns between buildings and across different locations. Recently, inferring occupancy schedules from metered electricity consumption data was used to model occupancy in commercial buildings. However, the translation from metered data to occupancy schedules requires many assumptions that might not capture the reality, and the process is hindered by the availability of data from advanced metering infrastructure. With the development of information technologies, occupancy modeling should not be limited to traditional approaches. The prevalence of social networks and location services with real-time user feedback provides publicly accessible data via Maps Application Programming Interfaces (APIs) such as Google Maps, SafeGraph, Mapbox, Foursquare, etc. This paper presents an automated framework for modeling parametric occupancy patterns using such APIs to calibrate commercial district buildings' energy models. This process includes three main steps: data extraction and processing, parametric schedules generation, and schedules integration. We demonstrated this framework in districts where we used maps API to generate more accurate behavioral patterns for operations and electric vehicle charging events. We used these patterns to determine differences in energy use across key sociodemographic and spatial parameters. The presented method has the potential for worldwide applications. Users can utilize this framework to extract data for selected locations of interest to create more realistic behavioral patterns for commercial facilities across different districts.

building energy modeling↗
DOE OSTI2022

Phase diagram of the Su-Schrieffer-Heeger-Hubbard model on a square lattice

The Hubbard and Su-Schrieffer-Heeger (SSH) Hamiltonians are iconic models for understanding the qualitative effects of electron-electron and electron-phonon interactions, respectively. In the two-dimensional square lattice Hubbard model at half filling, the on-site Coulomb repulsion U between up and down electrons induces antiferromagnetic (AFM) order and a Mott insulating phase. On the other hand, for the SSH model, there is an AFM phase when the electron-phonon coupling λ is less than a critical value λ c and a bond order wave when λ > λ c . In this Letter, we perform numerical studies on the square lattice optical Su-Schrieffer-Heeger-Hubbard Hamiltonian, which combines both interactions. We use the determinant quantum Monte Carlo method which does not suffer from the fermionic sign problem at half filling. We map out the phase diagram and find that it exhibits a direct first-order transition between an antiferromagnetic phase and a bond-ordered wave as λ increases. Here, the AFM phase is characterized by two different regions. At smaller λ the behavior is similar to that of the pure Hubbard model; the other region, while maintaining long-range AFM order, exhibits larger kinetic energies and double occupancy, i.e., larger quantum fluctuations, similar to the AFM phase found in the pure SSH model.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Developing occupant archetypes within urban low-income housing: A case study in Mumbai, India

Rapid urbanization pressure and poverty have created a push for affordable housing within the global south. The design of affordable housing can have consequences on the thermal (dis)comfort and behaviour of the occupants, hence requiring an occupant-centric approach to ensure sustainability. This paper investigates occupant behaviour within the urban poor households of Mumbai, India and its impact on their thermal comfort and energy use. This study is a first-of-its-kind attempt to explore the socio-demographic characteristics and energy-related behaviour of low-income occupants within Indian context. Three occupant archetypes, Indifferent Consumers; Considerate Savers; and Conscious Conventionals, were identified from the behavioural and psychographic characteristics gathered through a transverse field survey. A two-step clustering approach was adopted for occupant segmentation that highlighted considerable diversity in occupants’ adaptation measures, energy knowledge, energy habits, and their pro-environmental behaviour within similar socio-economic group. Building energy simulation of the representative archetype behaviour estimated up to 37% variations for air-conditioned and up to 8% variation for fan-assisted naturally ventilated housing units during peak summer months. The results from this study establish the significance of occupant factors in shaping energy demand and thermal comfort within low-income housing and pave way for developing occupant-centric building design strategies to serve this marginalized population. The developed low-income occupant archetypes would be useful for architects and energy modelers to generate realistic energy use profiles and improve building performance simulation results.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Dirty dishes or dirty laundry? Comparing two methods for quantifying American consumers' preferences for load management in a smart home

One challenge of transitioning to renewable energy is that household electricity use and renewable generation are often misaligned. Smart home energy management systems hold promise for shifting usage to match generation, but these systems need to be designed with the occupants’ preferences in mind. The purpose of the present research is to compare two approaches for collecting and modeling consumers’ load management preferences, both of which are amenable to use in a home energy management system. Specifically, we examine the performance of Simple Multi-Attribute Rating Technique Exploiting Ranks (SMARTER) and Analytic Hierarchy Process (AHP) in quantifying consumers’ preferences regarding air temperature (air conditioning and heating), water heating, dishwashing, clothes washing and drying, monetary costs, environmental impacts, and comfort/convenience. Two studies are presented: Study 1 examines the SMARTER approach, and Study 2 focuses on the AHP approach. In both studies, online surveys (N SMARTER = 956 and N AHP = 1023) were conducted to elicit preferences from participants across the United States. The preferences modeled by both approaches were validated based on (a) their ability to predict participants’ choices in a Discrete Choice Experiment and (b) their convergence with previous research on load-shifting behavior. The validation procedure suggests that the SMARTER approach is superior in modeling consumers’ preferences for load management. Overall, this research lays the groundwork for designing a smart home interface capable of collecting occupants’ preferences and using those preferences to deliver improved occupant comfort, lower operating costs, reduced environmental impact, and more significant demand response than exists today.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Stochastic Pricing Game for Aggregated Demand Response Considering Comfort Level

In recent years, demand response (DR) has been explored as a fundamental strategy for demand-side management due to its advantages in mediating intermittency of renewable energy generation, load shifting, etc. To engage customers in DR programs, several deterministic price-based DR strategies have been developed and implemented. However, the stochastic weather conditions and occupants' consumption behaviors often make the deterministic solution less robust to uncertainties. In this paper, with the consideration of the uncertainties, a stochastic Stackelberg game is proposed to model the price-demand negotiation between a distributed system operator and load aggregators, where the virtual battery constraints are extracted from the building thermostatically controlled loads (TCLs)‘ characteristics to guarantee comfortable TCLs' levels. Following the negotiation, a priority-based control method is used to allocate the optimal aggregated power DR profile at the building level and track the power signal. Several groups of experiments have demonstrated the effectiveness and robustness of the stochastic solutions.

Chen, Yang↗
DOE OSTI2024

An Open-Source Framework for Characterizing Urban Energy Models: Integrating Top-Down and Bottom-Up Methods to Predict Residential Buildings Characteristics: Preprint

Bottom-up urban energy models are crucial for understanding current energy use patterns and informing design strategies. However, accurately characterizing these models to represent different communities remains a challenge due to the extensive data needed for simulating existing energy use behavior. This data includes information related to human activities and building characteristics, all of which correlate with socioeconomic factors. To overcome this challenge, we developed an automated framework that utilizes both top-down and bottom-up data, to predict unknown building and occupant characteristics that are needed for more accurate and equitable modeling and analytics. Our framework, integrated into the URBANopt district energy modeling platform, uses statistical data models from ResStock. URBANopt models co-located buildings and neighborhoods. At this scale there are data gaps in building characteristic data, such as materials, insulation, occupancy, income, and energy usage of the buildings. To address this data gap, we use ResStock data, representative at the census tract scale, and develop machine-learning and deeplearning techniques to disaggregate it to individual buildings. By mapping unique occupant, building and economic properties to URBANopt energy models, we gain detailed insights into the variability of building energy use across different neighborhoods. This insight helps deploy technologies for co-located buildings and supports targeted upgrades for communities with unique economic and demographic characteristics, ensuring energy equity. Accurate characterization of energy models allows us to develop equitable strategies tailored to diverse neighborhoods, whether underserved or affluent. Our automated framework streamlines energy modeling and provides a reliable tool for building energy characterization.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
DOE OSTI2022

The Impact of Structural Distortions on the Magnetism of Double Perovskites Containing 5d 1 Transition-Metal Ions

Five double perovskites, each containing a transition-metal ion with a 5d 1 configuration, have been studied to better understand the surprising diversity of magnetic ground states seen in these isoelectronic compounds. Ba 2 ZnReO 6 adopts the cubic double perovskite structure and magnetically orders below 16 K, with a canted ferromagnetic structure and a saturated magnetization of ~0.24 μ B /Re. X-ray magnetic circular dichroism indicates a substantial orbital moment of approximately 0.4 μ B /Re that opposes the spin moment. The structures of Ba 2 NaOsO 6 (canted ferromagnet, T C = 7 K) and Ba 2 LiOsO 6 (antiferromagnet, T N = 8 K) are reinvestigated using time-of-flight neutron powder diffraction and found to crystallize with the cubic double perovskite structure. No evidence for a structural distortion can be found in either compound down to 10 K. Ba 2 CdReO 6 is also cubic at room temperature but undergoes a structural transition upon cooling below ~180 K to a tetragonal structure with I4/m symmetry that involves compression of the Re–O bonds that are parallel to the c-axis. Sr 2 LiOsO 6 shows a similar tetragonal distortion at room temperature and maintains that structure down to 10 K. Surprisingly, the Os-centered octahedron in Sr 2 LiOsO 6 is distorted in the opposite direction, exhibiting an elongation of the Os–O bonds along the c-axis. Differences in the distortions of the octahedra lead to different magnetic ground states, antiferromagnetic (T N = 4 K) for Ba 2 CdReO 6 and spin glass (T g = 30 K) for Sr 2 LiOsO 6 . Theoretical modeling shows that the varied magnetic behaviors of double perovskites containing 5d 1 ions are closely tied to crystallographic distortions. Furthermore, these distortions remove the degeneracy of the 5d t 2g orbitals, leading to changes in orbital occupation that ultimately determine which of the several competing magnetic ground states is favored.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Structural complexity of snapshots of two-dimensional Fermi-Hubbard systems

The development of quantum gas microscopy for two-dimensional optical lattices has provided an unparalleled tool to study the Fermi-Hubbard model (FHM) with ultracold atoms. Spin-resolved projective measurements, or snapshots, have played a significant role in quantifying correlation functions, theory verification, and thus the uncovering of underlying physical phenomena such as antiferromagnetism at commensurate filling on bipartite lattices and other charge and spin correlations, as well as dynamical properties at various densities. Here we employ a recent concept, the multiscale structural complexity, and show that when computed for the snapshots (of single spin species, local moments, or total density) it can provide a theory-free property, immediately accessible to experiments. Specifically, after benchmarking results for Ising and $XY$ models, we study the structural complexity of snapshots of the repulsive FHM in the two-dimensional square lattice as a function of doping and temperature. We generate projective measurements using determinant quantum Monte Carlo and compare their complexities against those from the experiment. We demonstrate that these complexities are linked to relevant physical observables such as the entropy and double occupancy. Their behaviors capture the development of correlations and relevant length scales in the system. Furthermore, we provide an open-source code in python which can be implemented into data analysis routines in experimental settings for the square lattice.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Integration of Electric Vehicle Charging Loads in Residential Building Stock Energy Modeling

The rapid adoption of electric vehicles (EVs) has resulted in significant new household electric loads that have the potential to change how energy costs are incurred by homeowners and the landscape of utility operations and energy infrastructure. Whereas adoption patterns and magnitudes of residential building and EV charging loads are influenced by distinct factors, the loads themselves are tightly coupled with the behavior of the individual occupants and EV owners.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Modeling Savings for ENERGY STAR Smart Home Energy Management Systems

The objective of this study was to develop a repeatable and defensible methodology to analyze the energy savings for Home Energy Management Systems (HEMS) that meets the minimum requirements for certification under ENERGY STAR ® Smart Home Energy Management System (SHEMS) Version 1. Mandatory connected loads include a smart thermostat, two smart lights, and one smart power strip or smart outlet. Control strategies must include feedback to occupants through an in-home display, user programming, occupancy sensor-based controls, and responsiveness to utility signals such as demand response programs. Several occupant behavior patterns were selected to quantify the range of energy savings potential for a HEMS with this basic functionality. A literature review was conducted to establish realistic room-by-room occupancy levels and usage patterns for connected devices. A series of event-driven hourly profiles were created, followed by adjustments based on application of HEMS control strategies to thermostats, interior lighting, and plug load schedules. EnergyPlus modeling was performed using these hourly schedules in three locations (Boston, Houston, and Phoenix) to examine climate dependence of energy savings. Total site energy savings ranged from 4.3 to 27.1 MBtu/year (7%-35%), and utility bill savings ranged from $\$$123 to $\$$670/year (6%-29%). The highest predicted savings was realized by occupants that were not energy conscious prior to HEMS installation, but highly engaged with the HEMS controls once the system was installed. The smart thermostat accounted for most of the savings, followed by the smart power strip. Smart lighting did not save a significant amount of energy in our analysis, based on an assumption that efficient LEDs with no standby power would normally be installed anyway.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

NMF-Based Anomaly Detection in CMS 2D Tracking Occupancy Histograms

The CMS experiment relies on Data Quality Monitoring (DQM) to ensure that recorded collision data are suitable for physics analysis. During LHC Run 3, each run contains many lumisections and tracking monitoring elements, making offline inspection challenging, especially for localized detector effects that may appear only for short periods of time. This poster presents an unsupervised machine-learning approach to identify anomalous lumisections in CMS tracking occupancy histograms using Non-Negative Matrix Factorization (NMF). The workflow uses offline CMS DQMIO tracking histograms retrieved with the CMS DIALS API and organized as two-dimensional occupancy maps for each lumisection. After selecting stable lumisections, the occupancy maps are normalized and arranged into a non-negative data matrix. The NMF model learns a compact set of basis patterns describing normal tracking occupancy. Each lumisection is then reconstructed from these learned components, and the reconstruction error is used as an anomaly score. Large residuals indicate occupancy patterns that deviate from normal detector behavior and are flagged for further inspection. This NMF-based approach provides a fast and interpretable way to flag lumisections whose tracking occupancy patterns differ from normal detector behavior. Preliminary studies show sensitivity to known tracking anomalies, and ongoing work is focused on validating the method across additional Run 3 Pixel and Strip detector issues.

Rodríguez Ramos, Iliomar [Puerto Rico U., Mayaguez↗
DOE OSTI2021

Nuclear spin features relevant to ab initio nucleon-nucleus elastic scattering

Effective interactions for elastic nucleon-nucleus scattering from first principles require the use of the same nucleon-nucleon interaction in the structure and reaction calculations, as well as a consistent treatment of the relevant operators at each order. Previous work using these interactions has shown good agreement with available data. Here, we study the physical relevance of one of these operators, which involves the spin of the struck nucleon, and examine the interpretation of this quantity in a nuclear structure context. Using the framework of the spectator expansion and the underlying framework of the no-core shell model, we calculate and examine spin-projected, one-body momentum distributions required for effective nucleon-nucleus interactions in $J=0$ nuclear states. The calculated spin-projected, one-body momentum distributions for $^4$He, $^6$He, and $^8$He display characteristic behavior based on the occupation of protons and neutrons in single particle levels, with more nucleons of one type yielding momentum distributions with larger values. Additionally, we find this quantity is strongly correlated to the magnetic moment of the $2^+$ excited state in the ground state rotational band for each nucleus considered. In conclusion, we find that spin-projected, one-body momentum distributions can probe the spin content of a $J=0$ wave function. This feature may allow future ab initio nucleon-nucleus scattering studies to inform spin properties of the underlying nucleon-nucleon interactions. The observed correlation to the magnetic moment of excited states illustrates a previously unknown connection between reaction observables such as the analyzing power and structure observables like the magnetic moment.

6 ≤ A ≤ 19↗
DOE OSTI2020

A method to generate heating and cooling schedules based on data from connected thermostats

Internet-connected thermostats are a promising new source of temperature and operational data in homes because they record inside temperatures, setpoints, and HVAC runtimes every five minutes. Over 20 million Internet-connected thermostats have already been installed in American homes. Data from about 20,000 connected thermostats were collected and organized by climate zone, number of occupants, floor area, and day type. A method was developed to create up to 40 representative temperature schedules which, together, can more accurately capture the diversity of heating and cooling behaviors. These results are suitable for input into schedules for building energy simulation models. This information enables more realistic simulations of American heating and cooling behavior, leading to more accurate estimates of energy consumption and savings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗