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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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11 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A zone-level occupancy counting system for commercial office spaces using low-resolution time-of-flight sensors

Understanding the locations of occupants in a commercial built environment is critical for realizing energy savings by delivering lighting, heating, and cooling only where it is needed. In this paper, we present an indoor occupancy counting system using a sparse array of inexpensive, low-resolution, and privacy-preserving time-of-flight sensors. We develop and validate an algorithm for zonal occupancy counting that can deal with multiple people walking underneath the sensors in arbitrary directions, and evaluate the system both in realistic simulations of office spaces and in a real-world installation. Finally, we found that our system has an error rate of around 0.4%, resulting in highly accurate person localization and zone counting using only a few sensors per space.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Solar PV, Wind Generation, and Load Forecasting Dataset for ERCOT 2018: Performance-Based Energy Resource Feedback, Optimization, and Risk Management (P.E.R.F.O.R.M.)

This report describes the Advanced Research Projects Agency-Energy Performance-Based Energy Resource Feedback, Optimization, and Risk Management (PERFORM) Electric Reliability Council of Texas (ERCOT) dataset consisting of load, solar, and wind deterministic and probabilistic forecasts at three timescales. This dataset consists of 1 year of time-coincident load, wind, and solar actuals and probabilistic forecasts for a region similar to ERCOT. All the data are stored in Hierarchical Data Format 5 (HDF5) files and have been uploaded to an Amazon Web Services repository. The ERCOT data set has 2 years (2017, 2018) of actuals and 1 year (2018) of probabilistic forecasts. These data are provided at various spatial (i.e., site-level, zone-level, and system-level) and temporal scales (i.e., day-ahead, intraday, and intra-hour). Specifically, data are provided for 125 existing wind sites, 22 existing solar sites, 139 proposed wind sites, and 204 proposed solar sites.

14 SOLAR ENERGY↗
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 OSTI2023

Exploring the Effects of Population and Employment Characteristics on Truck Flows: An Analysis of NextGen NHTS Origin-Destination Data

Truck transportation remains the dominant mode of US freight transportation because of its advantages, such as the flexibility of accessing pickup and drop-off points and faster delivery. Because of the massive freight volume transported by trucks, understanding the effects of population and employment characteristics on truck flows is critical for better transportation planning and investment decisions. The US Federal Highway Administration published a truck travel origin-destination data set as part of the Next Generation National Household Travel Survey program. This data set contains the total number of truck trips in 2020 within and between 583 predefined zones encompassing metropolitan and nonmetropolitan statistical areas within each state and Washington, DC. In this study, origin-destination-level truck trip flow data was augmented to include zone-level population and employment characteristics from the US Census Bureau. Census population and County Business Patterns data were included. The final data set was used to train a machine learning algorithm-based model, Extreme Gradient Boosting (XGBoost), where the target variable is the number of total truck trips. Shapley Additive ExPlanation (SHAP) was adopted to explain the model results. Results showed that the distance between the zones was the most important variable and had a nonlinear relationship with truck flows.

Uddin, Majbah↗
DOE OSTI2021

A Spatiotemporal Prediction Model for Regional Scheduling of Shared Bicycles Based on the INLA Method

Dock-less bicycle-sharing programs have been widely accepted as an efficient mode to benefit health and reduce congestions. And modeling and prediction has always been a core proposition in the field of transportation. Most of the existing demand prediction models for shared bikes take regions as research objects; therefore, a POI-based method can be a beneficial complement to existing research, including zone-level, OD-level, and station-level techniques. Point of interest (POI) is the location description of spatial entities, which can reflect the cycling route characteristics for both commuting and noncommuting trips to a certain extent, and is also the main generating point and attraction point of shared-bike travel flow. In this study, we make an effort to model a POI-level cycling demand with a Bayesian hierarchical method. The proposed model combines the integrated nested Laplace approximation (INLA) and random partial differential equation (SPDE) to cope with the huge computation in the modeling process. In particular, we have adopted the dock-less bicycle-sharing rental records of Mobike as a case study to validate our method; the study area was one of the fastest growing urban districts in Shanghai in August 2016. The operation results show that the method can help better understand, measure, and characterize spatiotemporal patterns of bike-share ridership at the POI level and quantify the impact of the spatiotemporal effect on bicycle-sharing use.

Yu, Zhuoran↗
DOE OSTI2021

Surface soil temperature and water content from warming experiment located at the Rocky Mountain Biological Laboratory, Colorado, 2015 to 2019

This data package consists of soil temperature and soil water content sensor data from the warming experiment near the Rocky Mountain Biological Laboratory. Data range is from summer 2015 to summer 2019, when the warming manipulation was terminated. The location of the warming experiment is in the upper montane life zone and consists of meadow vegetation with a mixture of sagebrush (Artemisia tridentata), forb species (Erigeron speciosus, Helianthella quinquenervis, Lathyrus lanszwertii), and graminoid species (Festuca thurberi, Carex spps). Early studies showed that the heating treatment led to earlier snowmelt as well as warmer and drier surface soils, and changes in the functional composition of aboveground biomass favoring sagebrush over forb species (Harte and Shaw, 1995). These changes were mainly observed in the upper, naturally drier zone for the experimental plots. More recent observations of aboveground biomass, soil carbon, and microbial composition require concurrent information about the abiotic environment for interpretation and extrapolation to process-based models. This data package provides the plot- and zone-level abiotic context for the final years of the experiment and consists of csv files with hourly soil temperature (WM_ST.csv) and soil water content (WM_SWC.csv).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Surrogate Model of Flexible Research Platform EnergyPlus Models to Enable Sensitivity Analysis

This letter report describes the surrogate models developed from the EnergyPlus model of Oak Ridge National Laboratory’s Flexible Research Platform. Two data-driven black-box models were developed, and the outputs of the surrogate models were compared with the EnergyPlus model. The two models developed are a multilayer perceptron deep learning model, and a long short-term memory (LSTM) neural network model. The three factors for selecting the black-box models are scalability, computation time, and accuracy. A total of 107 input variables were the dominant variables in determining the outputs of building energy consumptions and thermal comfort. A total of 54 output variables were identified as the prediction targets, including the system- and zone-level outputs. The large set of the simulation cases were generated by integrating sensor errors into an emulator based on EnergyPlus and Python EMS, which includes advanced control sequences from ASHRAE Guideline 36-2018: High-Performance Sequences of Operation. The surrogate models were developed based on a set of large-scale simulation runs (i.e., 4,000 runs) on a cloud platform. The comparison analysis shows that the two black-box models had good accuracy for predicting new outputs for sensitivity analysis using the root mean square error metric. As a next step, the developed surrogate models will be used to perform sensitivity analysis for different sensor impacts (e.g., sensor types, sensor locations).

42 ENGINEERING↗
NASA NTRS1990

Effect of neutron irradiation on the thermoelectric properties of SiGe alloys

Zone-leveled and hot-pressed n- and p-type Si80Ge20 alloys were irradiated with neutrons to a fluence of 4 x 1018 n/sq cm and to a fluence of 5.4 x 1019 n/sq cm at a temperature of approximately 200-300 C. The effect of neutron irradiation on the thermoelectric properties of these alloys was evaluated. The carrier concentration and mobility (and hence the resistivity) were measured at room temperature while the thermal diffusivity was measured at 177-192 C both before and after the irradiation and after each subsequent 2-h heat treatment at 350 C, 600, and 1000 C. The irradiation increased the resistivity significantly, but the thermal conductivity decreased only by about 10-15 percent. This tends to indicate that the radiation produced only small defects (single pairs and small vacancy chains). The samples all returned to almost exactly their preirradiation state after the 1000 C anneal. This indicates that SiGe alloys can be operated in this neutron fluence at high temperatures without a degradation of thermoelectric properties.

Vandersande, Jan W.↗
NASA NTRS1990

Experimental approaches for improving SiGe thermoelectric efficiency at JPL

Efforts to improve the thermoelectric efficiency of silicon-germanium alloys are discussed. These efforts are essentially focused on substantially enhancing carrier concentration levels and thus increasing the power factor values of n-type materials. With the help of thermodynamic phase diagram calculations, a combination of various crystal growth and dopant saturation techniques is used for this purpose. Bulk polycrystal growth of double-doped materials is achieved by zone leveling while a new method (the traveling heater method) for high-quality single-crystal growth of SiGe is being developed. Thin films of homogeneous single-crystalline multidoped Si80Ge20 have also been successfully grown from low-temperature melts to investigate combined dopant solid solubility variations. Very high carrier concentration levels were obtained by (P+As)-combined diffusion in zone-leveled and hot-pressed materials. The good overall understanding of doping mechanisms which has been achieved should enable optimization of the thermoelectric properties over this extended carrier concentration range. Reductions in thermal conductivity are being sought by introduction of very small phonon scattering centers (inert material) in the initial powders-precursors of Si-Ge alloys. This approach should benefit both n- and p-type materials.

Borshchevsky, Alex↗
NASA NTRS1991

Thermoelectric properties of pressure-sintered Si(0.8)Ge(0.2) thermoelectric alloys

The thermoelectric properties of 28 sintered Si(0.8)Ge(0.2) alloys, heavily doped with either B or P and prepared from powders with median particle sizes ranging from about 1 to over 100 microns, have been determined from 300 to 1300 K. The thermal conductivity decreases with decreasing particle size; however, the figure of merit is not significantly increased due to a compensating reduction in the electrical conductivity. The thermoelectric figure of merit is in good agreement with results of Dismukes et al. (1964) on similarly doped alloys prepared by zone-leveling techniques. The electrical and thermal conductivity are found to be sensitive to preparation procedure while the Seebeck coefficient and figure of merit are much less sensitive. The high-temperature electrical properties are consistent with charge carrier scattering by acoustic or optical phonons.

Vining, Cronin B.↗
DOE OSTI2020

EMPIRICAL VALIDATION OF MULTI-ZONE BUILDING AND HVAC SYSTEM MODELS UNDER UNCERTAINTY

This study implemented a framework of empirical validation of building energy models under uncertainty to a set of controlled experiments that aim to validate multi-zone building and HVAC system models. Energy models were created through iterative acquisitions of information and data and uses measurement data from various types of sensors as both inputs and as observations to validate predictions. Experimental and modeling uncertainties were quantified and propagated accordingly, and probabilistic accuracy metrics were used to evaluate the agreement between model predictions and observations under uncertainty. Sensitivity analysis was performed to identify the most influential uncertainties that will be prioritized to be addressed in the next steps. Current results of two cooling tests show an overall good agreement between predictions and observations on a set of HVAC system outputs despite considerable and influential uncertainty in DX cooling coil COP. Agreements on zone-level responses vary notably among individual rooms, likely because of significant uncertainties in room radiation heat gain and system supply air.

Li, Qi↗