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

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

From occupants to occupants: A review of the occupant information understanding for building HVAC occupant-centric control

Occupants are the core of the built environment. Traditional Heating, Ventilation, and Air-Conditioning (HVAC) systems operate with predefined schedules and maximum occupancy assumptions with no consideration of specific occupant information. These generalized assumptions usually do not align with the actual demand and result in over-conditioning and occupant discomfort. In recent years, with the aid of Information & Communication Technology (ICT) and Computer Science (CS), it is possible to acquire real-time and accurate occupant information to satisfy the exact thermal requirement through specific HVAC control in one particular built environment. This mechanism is called HVAC “Occupant-centric Control (OCC).” HVAC OCC strategy starts with collecting the occupant’s information (e.g., presence/absence) and then applies it to meet the occupant’s requirement (e.g., thermal comfort). However, even though some research studies and field pilot demonstrations have been devoted to the field of OCC, there is a lack of systematic knowledge about occupant data, which is the principal component of OCC for HVAC researchers and practitioners. To fill this gap, this review paper discusses OCC with a particular emphasis on occupant information and investigates how this information can assist HVAC operation in providing an acceptable built environment in required spaces during the required time. Finally, we provide a fine-grained, comprehensive picture of occupant information, discuss its features, the modalities of information feed-in into the HVAC control, and the application of commonly utilized occupant information for OCC.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Energy Prediction Impact of the Space Level Occupancy Schedule for a Primary School

By using the same occupant schedule for all spaces, a building level occupancy schedule in building energy modelling can reduce the cost and time of data collection, especially for large-scale simulations or when detailed occupancy data cannot be obtained. However, by describing the unique occupancy status in each space, a space level schedule can better reflect real-world scenarios. This research investigates the energy prediction impact of a space level occupancy schedule for primary school modelling in 16 ASHRAE climate zones. The results show that when switched from a building level to a space level occupancy schedule, the energy prediction difference is between -1.0% and 0.8%. Generally, the predicted building energy consumption using a space level occupancy schedule is higher than when using a building level occupancy schedule in hot and warm climate zones, but lower in other climate zones.

building energy model↗
DOE OSTI2021

Occupant Preference-Aware Load Scheduling for Resilient Communities

The load scheduling of resilient communities in the islanded mode is subject to many uncertainties such as weather forecast errors and occupant behavior stochasticity. To date, it remains unclear how occupant preferences affect the effectiveness of the load scheduling of resilient communities. This paper proposes an occupant thermal preference-aware load scheduler for resilient communities operating in the islanded mode. First, key resilience indicators are selected to quantify its impacts on the load scheduling of a resilient community. A deterministic model predictive control-based load scheduling framework is adopted as the baseline. Then, a chance-constrained controller is proposed to address the occupant-induced uncertainty in room temperature setpoints. Finally, the chance-constrained controller is compared with the deterministic controller on a virtual community testbed based on a real-world net-zero energy community in Florida, U.S. Results have shown that the proposed chance-constrained controller performs better in terms of serving occupants’ thermal preference and the required battery sizes compared to the deterministic controller with the presence of the assumed stochastic occupant behavior. This work indicates that it is necessary to consider the stochasticity of the occupant behavior when designing optimal load schedulers for resilient communities.

Wang, Jing↗
DOE OSTI2022

Impact of WELL certification on occupant satisfaction and perceived health, well-being, and productivity: A multi-office pre- versus post-occupancy evaluation

The WELL Building Standard (WELL) is currently one of the most comprehensive building certification programs that aim to enhance the health and well-being of building occupants. However, there is a lack of systematic evaluation of the effectiveness of WELL in achieving its goal. This study investigates the impact of WELL certification on occupant satisfaction with the workplace and occupant perceived health, well-being, and productivity. More than 1300 pre- and post-occupancy survey responses provided by the nearly same cohort of occupants from six companies in North America were quantitatively analyzed. The results showed that transitioning to WELL certified offices from non-WELL certified offices had a positive impact on occupant satisfaction with the workplace and occupant perceived health, well-being, and productivity, with increases in means from pre-to post-occupancy being highly statistically significant. The majority of the studied occupant satisfaction parameters as well as occupant perceived mental health had large effect sizes. While they improved from pre-to post-occupancy, the analysis revealed small effect sizes for occupant perceived physical health and self-assessed productivity. The majority of the effect sizes for the perceived well-being parameters were large and medium. In addition to analyzing the survey responses in aggregate, the responses were examined at the individual company level to confirm the by-company and aggregate findings aligned.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Development and Evaluation of Occupancy-Aware HVAC Control for Residential Building Energy Efficiency and Occupant Comfort

Occupancy-aware heating, ventilation, and air conditioning (HVAC) control offers the opportunity to reduce energy use without sacrificing thermal comfort. Residential HVAC systems often use manually-adjusted or constant setpoint temperatures, which heat and cool the house regardless of whether it is needed. By incorporating occupancy-awareness into HVAC control, heating and cooling can be used for only those time periods it is needed. Yet, bringing this technology to fruition is dependent on accurately predicting occupancy. Non-probabilistic prediction models offer an opportunity to use collected occupancy data to predict future occupancy profiles. Smart devices, such as a connected thermostat, which already include occupancy sensors, can be used to provide a continually growing collection of data that can then be harnessed for short-term occupancy prediction by compiling and creating a binary occupancy prediction. Real occupancy data from six homes located in Colorado is analyzed and investigated using this occupancy prediction model. Results show that non-probabilistic occupancy models in combination with occupancy sensors can be combined to provide a hybrid HVAC control with savings on average of 5.0% and without degradation of thermal comfort. Model predictive control provides further opportunities, with the ability to adjust the relative importance between thermal comfort and energy savings to achieve savings between 1% and 13.3% depending on the relative weighting between thermal comfort and energy savings. In all cases, occupancy prediction allows the opportunity for a more intelligent and optimized strategy to residential HVAC control.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Development and Evaluation of Occupancy-Aware Model Predictive Control for Residential Building Energy Efficiency and Occupant Comfort

The residential sector accounts for 25% of global primary energy consumption. Two methods have previously been proposed to reduce residential energy use associated with the provision of occupant thermal comfort: 1. Occupancy-based HVAC control, operating systems only during confirmed occupancy, and 2. model predictive control (MPC), harnessing a mathematical model and forecasts to find optimal operating strategies. Previous studies estimate the average energy savings of the two methods individually in the range of 21% and 16%, respectively. The research presented herein was carried out to evaluate the energy savings potential in residential buildings by combining both approaches across different climates, house vintages, and occupancy patterns. Occupancy and eight different physical modalities (e.g. CO2 and VOC) data were collected from five homes for time periods of 4–9 weeks. Collected data sets were used to train occupancy prediction models suggested by an extensive literature survey of occupancy model types. The trained prediction models were combined with MPC and detailed EnergyPlus building simulation models to evaluate residential building performance in terms of annual energy savings and thermal comfort, along with discomfort exceedance metrics. Multiple home types and regions were analyzed to understand regional and climate-dependent potential. Based on actual field data, the occupancy models had a prediction inaccuracy between 8% and 35% across the investigated homes. Average occupancy for the collected data ranged from 56% to 86%, a typical range reported in the literature. Building simulations were conducted for three control scenarios: conventional thermostatic control, occupancy-based, and occupancy-based MPC. The results indicate that all advanced strategies improve upon the conventional control, with some scenarios cutting energy use in half with only occasional incurrence of discomfort. The findings indicate that occupancy-aware model predictive residential building control has the potential to drastically reduce energy use and associated emissions while maintaining occupant comfort for both new and existing buildings.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
DOE OSTI2023

Smart thermostat data-driven U.S. residential occupancy schedules and development of a U.S. residential occupancy schedule simulator

Occupancy schedule is one of the key inputs in Building Energy Modeling (BEM) to reflect the interaction between buildings and occupants. Over the past decades, standardized occupancy schedules, developed mainly by engineering rule-of-thumb, have been widely used in BEM due to its simplicity and lack of real measured occupancy data. However, the BEM community has recognized their association with uncertainty and reliability in simulation results from BEM. This study introduces representative occupancy schedules in the U.S. residential buildings, derived from a large smart thermostat dataset and time-series K-means clustering, and an open-source tool to generate a stochastic residential occupancy schedule. Over 90,000 residential occupancy schedules were estimated from the ecobee Donate Your Data dataset. Then, the representative occupancy schedules were identified through clustering. This study further investigated the impacts of three parameters (day, house type, and state) on residential occupancy schedules. Then, a tool, the Residential Occupancy Schedule Simulator (ROSS), is developed using the representative occupancy schedules derived in this study. Details of this tool are presented in this paper. In conclusion, the derived representative occupancy schedules and the ROSS tool can help improve the energy modeling of residential buildings.

42 ENGINEERING↗
DOE OSTI2020

Nationwide HVAC Energy-Saving Potential Quantification for Office Buildings with Occupant-Centric Controls in Various Climates

The occupant-centric control (OCC) is receiving an increasing attention due to its ability to reduce building heating ventilation and air-conditioning (HVAC) system energy consumptions while not affecting the occupant thermal comfort. This paper aims to investigate and quantify the nationwide energy-saving potential of implementing the occupant-centric HVAC controls in typical office buildings using a whole building simulation software EnergyPlus. First, the medium office and large office from the Department of Energy (DOE) Commercial Prototype Building Models (CBPM) were enhanced to have detailed layouts and dynamic occupancy schedules. Then, a comprehensive simulation plan was created by incorporating the multiple zone-level and system-level occupant-centric building HVAC controls recommended by the updated ASHRAE Standard 90.1 – 2019 and ASHRAE Guideline 36 – 2018. Three control scenarios with different occupancy sensing methods were identified in this simulation plan. A nation-wide parametric analysis which includes two building types, three occupancy sensing scenarios, two building code versions, and 16 U.S. climate zones was carried out. The simulation results of the key control variables and HVAC energy consumption suggest that generally, both the occupancy presence sensor and occupant counting sensor could achieve energy savings for the office buildings in majority of the scenarios. However, compared with the occupancy presence sensor, which could support both the temperature setpoint reset and operational breathing zone airflow rate reset for the unoccupied zones, the occupant counting sensor only brings a marginal benefit. Besides, a higher HVAC energy-saving ratio could be achieved in the heating-dominated zone, since the energy reduction brought with the minimum outdoor airflow rate reset is stronger in the heating mode.

Pang, Zhihong↗
DOE OSTI2018

Occupancy-Based HVAC Control with Short-Term Occupancy Prediction Algorithms for Energy-Efficient Buildings

This study aims to develop a concrete occupancy prediction as well as an optimal occupancy-based control solution for improving the efficiency of Heating, Ventilation, and Air-Conditioning (HVAC) systems. Accurate occupancy prediction is a key enabler for demand-based HVAC control so as to ensure HVAC is not run needlessly when when a room/zone is unoccupied. In this paper, we propose simple yet effective algorithms to predict occupancy alongside an algorithm for automatically assigning temperature set-points. Utilizing past occupancy observations, we introduce three different techniques for occupancy prediction. Firstly, we propose an identification-based approach, which identifies the model via Expectation Maximization (EM) algorithm. Secondly, we study a novel finite state automata (FSA) which can be reconstructed by a general systems problem solver (GSPS). Thirdly, we introduce an alternative stochastic model based on uncertain basis functions. The results show that all the proposed occupancy prediction techniques could achieve around 70% accuracy. Then, we have proposed a scheme to adaptively adjust the temperature set-points according to a novel temperature set algorithm with customers’ different discomfort tolerance indexes. By cooperating with the temperature set algorithm, our occupancy-based HVAC control shows 20% energy saving while still maintaining building comfort requirements.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

A novel occupancy detection solution using low-power IR-FPA based wireless occupancy sensor

Significant energy savings can be achieved by operating heating, ventilation, and air conditioning control systems with indoor occupancy measurement information. This paper presents a novel plug-and-play occupancy sensing method which will enable temporal minimization of building energy consumption to meet building usage behavior without privacy concerns. The proposed wireless occupancy sensing platform is based on long-wave infra-red (LWIR) focal-plane arrays (FPAs), or thermal imagers, that detect thermal energy rather than visible light. We developed an advanced sensor package consisting of multiple thermal imagers with low-cost optical enhancements to increase field of view and increase sensitivity to occupant detection (filtering building clutter). These imagers can be coupled with radio frequency and ultrasonic-based radar to enhance data collection at key occupant zone boundaries to improve accuracy. Standard filtering and estimation techniques from the image processing and computer vision communities are introduced to overcome the accuracy issues suffered by traditional PIR based sensing, especially when occupants remain relatively still. Accurate low-level counting of individuals can be achieved with minimal impact on privacy. As a result, the proposed occupancy detection method can work as a retrofit to enable real-time understanding of the building operational state and usage behavior. Sensor data obtained from real test building zones was used to test the efficacy of the method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

X-ray emission spectroscopy: an effective route to extract site occupation of cations

Cation site occupation is an important determinant of materials properties, especially in a complex system with multiple cations such as in ternary spinels. In this work, we show that XES provides not only the site occupation information as EXAFS, but also additional information on the oxidation states of the cations at each site. Additionally, we show that XES is a superior and a far more accurate method than EXAFS.

Bhargava, Anuj↗
DOE OSTI2018

Occupation probabilities as variables in electronic structure theory: cooper pairing, OP-NSOFT-Cs,t, and the homogeneous electron liquid

The energy functional of a novel electronic structure theory, OP-NSOFT, has as variables the natural spin orbitals (NSO) of the trial function and their joint occupation probabilities in the search for the ground state energy. When occupancy is restricted to the spin-paired NSOs of DOCI, the resulting theory, OP-NSOFT-0, scales as M 3 , with M the size of the one-electron basis set. Accurate results were obtained for small molecules, particularly near dissociation where single reference theories like DFT are inaccurate. The homogeneous electron liquid (HEL) could serve as a test bed of OP-NSOFT for condensed systems, but OP-NSOFT-0 reduces to the Hartree–Fock approximation for the HEL. Cooper pairing is introduced instead, both singlet pairing, OP-NOFT-Cs, and fully polarized triplet pairing, OP-NSOFT-Ct. The former yields 1/3 of the diffusion-Monte-Carlo correlation energy, the latter 1/2 to 1/3 with decreasing electron density for r s values between 1 and 10. Both yield the discontinuity in the single-particle occupation number required by the Luttinger theorem. Furthermore, two-state joint occupation probabilities illustrate the importance of electron–electron small-angle scattering in establishing electron correlation in the unpolarized HEL.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Occupational and dietary differences in hydroxylated and methoxylated PBDEs and metals in plasma from Puget Sound, Washington, USA region volunteers

BACKGROUND: Electronic waste (E-waste) recycling is a rapidly growing occupation in the USA with the potential for elevated exposure to flame retardants and metals associated with electronic devices. We previously measured polybrominated diphenyl ethers (PBDEs) in plasma from E-waste workers and found them similar to non-E-waste workers. OBJECTIVES: This study focused on structurally related PBDE derivatives, the hydroxylated (OH-PBDEs) and methoxylated (MeO-PBDEs) forms along with metals known to occur in E-waste. Humans can metabolize PBDEs and some MeO-PBDEs into OH-PBDEs, which is a concern due to greater health risks associated with OH-PBDEs METHODS: We measured 32 different OH-PBDEs and MeO-PBDEs in plasma samples provided by 113 volunteers living in the greater Puget Sound region of Washington State, USA. We measured 14 metals in a subset of 10 E-waste and 10 non-E-waste volunteers. Volunteers were classified based on occupational and dietary habits: work outdoors and weekly consume = 5 seafood servings (outdoor), electronic waste recycling (E-waste) or non-specific indoor occupations (indoor). A two-week food consumption diary was obtained from each volunteer prior to blood sampling. RESULTS: OH-PBDEs were detected in all volunteers varying between 0.27 – 102 ng/g/g-lipid. The MeO-PBDEs were detected in most, but not all volunteers varying between 0 – 60.4 ng/g/g-lipid. E-waste recyclers had OH-PBDE and MeO-PBDE plasma levels that were similar to the indoor group. The outdoor group had significantly higher levels of MeO-PBDEs, but not OH-PBDEs. Comparison of plasma concentrations of BDE-47 with its known hydroxylated metabolites suggested OH-PBDE levels were likely determined by biotransformation and at least two subpopulations identified differing in their apparent rates of OH-PBDE formation. The metals analysis indicated no significant differences between E-waste workers and non-E-waste workers. CONCLUSIONS: Our results indicate E-waste workers do not have elevated plasma levels of these contaminants relative to non-E-waste workers with similar dietary habits.

Schultz, Irvin↗
DOE OSTI2020

Fractional occupation numbers and self-interaction correction-scaling methods with the Fermi-Löwdin orbital self-interaction correction approach

In this work, we present a new assessment of the Fermi-Löwdin orbital self-interaction correction (FLO-SIC) approach with an emphasis on its performance for predicting energies as a function of fractional occupation numbers (FONs) for various multielectron systems. Our approach is implemented in the massively parallelized NWChem quantum chemistry software package and has been benchmarked on the prediction of total energies, atomization energies, and ionization potentials of small molecules and relatively large aromatic systems. Within our study, we also derive an alternate expression for the FLO-SIC energy gradient expressed in terms of gradients of the Fermi-orbital eigenvalues and revisit how the FLO-SIC methodology can be seen as a constrained unitary transformation of the canonical Kohn–Sham orbitals. Finally, we conclude with calculations of energies as a function of FONs using various SIC-scaling methods to test the limits of the FLO-SIC formalism on a variety of multielectron systems. We find that these relatively simple scaling methods do improve the prediction of total energies of atomic systems as well as enhance the accuracy of energies as a function of FONs for other multielectron chemical species.

fractional occupation number↗
DOE OSTI2017

Nonadiabatic Ab Initio Molecular Dynamics with the Floating Occupation Molecular Orbital-Complete Active Space Configuration Interaction Method [Non-Adiabatic Ab Initio Molecular Dynamics with Floating Occupation Molecular Orbitals CASCI Method]

Here, we show that the floating occupation molecular orbital complete active space configuration interaction (FOMO-CASCI) method is a promising alternative to the widely used complete active space self-consistent field (CASSCF) method in direct nonadiabatic dynamics simulations. We have simulated photodynamics of three archetypal molecules in photodynamics: ethylene, methaniminium cation, and malonaldehyde. We compared the time evolution of electronic populations and reaction mechanisms as revealed by the FOMO-CASCI and CASSCF approaches. Generally, the two approaches provide similar results. Some dynamical differences are observed, but these can be traced back to energetically minor differences in the potential energy surfaces. We suggest that the FOMO-CASCI method represents, due to its efficiency and stability, a promising approach for direct ab initio dynamics in the excited state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Nonthermal Site Occupation at the Donor-Acceptor Interface of Organic Solar Cells

Here, we investigate the nature of occupation and relaxation within the charge transfer density of states (CT DOS) for bulk heterojunction organic solar cells consisting of the donor boron subphthalocyanine chloride and the acceptor C 60 . We observe relaxation of geminate CT states on a sub-ns timescale via an approximately 70-meV dynamic redshift in their photoluminescence, whereas free carrier relaxation at longer times leads to the formation of nongeminate CT states at even lower energy. In steady state, we find that thermalization within the DOS is incomplete, resulting in a Boltzmann-like CT state distribution characterized by an effective temperature above that of the ambient. These findings confirm that electron and hole populations can be far from equilibrium in organic solar cells and may prompt a reassessment of analyses that assume the same temperature for their charge-carrier distributions in the dark and under illumination.

14 SOLAR ENERGY↗