Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “energy and behavior”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10

Boron nitride - Composition, optical properties, and mechanical behavior

A low energy ion beam deposition technique was used to grow boron nitride films on quartz, germanium, silicon, gallium arsenide, and indium phosphate. The film structure was amorphous with evidence of a hexagonal phase. The peak boron concentration was 82 at. percent. The carbon and oxygen impurities were in the 5 to 8 at. percent range. Boron-nitrogen and boron-boron bonds were revealed by X-ray photoelectron spectroscopy. The index of refraction varied from 1.65 to 1.67 for films deposited on III-V compound semiconductors. The coefficient of friction for boron nitride in sliding contact with diamond was less than 0.1. The substrate was silicon.

Pouch, John J.↗

Performance, Defect Behavior and Carrier Enhancement in Low Energy, Proton Irradiated p(+)nn(+) InP Solar Cells

InP p(+)nn(+) cells, processed by MOCVD, were irradiated by 0.2 MeV protons and their performance and defect behavior observed to a maximum fluence of 10(exp 13)/sq cm. Their radiation induced degradation, over this fluence range, was considerably+less than observed for similarly irradiated, diffused junction n p InP cells. Significant degradation occurred in both the cell's emitter and base regions the least degradation occurring in the depletion region. A significant increase in series resistance occurs at the highest fluenc.e. Two majority carrier defect levels, E7 and E10, are observed by DLTS with activation energies at (E(sub C) - 0.39)eV and (E(sub C) - 0.74)eV respectively. The relative concentration of these defects differs considerably from that observed after 1 MeV electron irradiation. An increased carrier concentration in the cell's n-region was observed at the highest proton fluence, the change in carrier concentration being insignificant at the lower fluences. In agreement with previous results, for 1 and 1.5 MeV electron irradiated InP p(+)n junctions, the defect level E10 is attributed to a complex between zinc, diffused into the n-region from the zinc doped emitter, and a radiation induced defect. The latter is assumed to be either a phosphorus vacancy or interstitial. The increased, or enhanced carrier concentration is attributed to this complex acting as a donor.

Weinberg, I.↗

MSD CoP Webinar: "Generative agents: A new frontier for representing human actors and their behavior in MSD models"

Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org). Talk #1: Behavioral Generative Agents for Energy Operations Presenter: Dr. Cong Chen (Thayer School of Engineering, Dartmouth College) Abstract: Accurately modeling consumer behavior in energy operations remains challenging due to inherent uncertainties, behavioral complexities, and limited empirical data. This talk introduces a novel approach leveraging generative agents--artificial agents powered by large language models--to realistically simulate customer decision-making in dynamic energy operations. Talk #2: Simulating multiple human perspectives in socio-ecological systems using large language models Presenter: Dr. Yongchao Zeng (Institute of Meteorology and Climate Research, Atmospheric Environmental Research (IMK-IFU) of the Karlsruhe Institute of Technology in Germany) Abstract: Understanding socio-ecological systems requires insights from diverse stakeholder perspectives. This talk describes a novel simulation system called HoPeS (Human-oriented Perspective Shifting). HoPeS enables model users to not only explore simulated socio-ecological systems (SESs) from a third-person observer's perspective but also take any of the simulated stakeholder roles, like playing an RPG game. By shifting multiple perspectives, model users can reflect and integrate the situated knowledge learned through the participatory simulation, approximating a more holistic and less biased understanding of SESs. Moderators: Jim Yoon (MSD CoP Human Systems Modeling Working Group Co-Chair); Stefano Galelli (MSD CoP Using AI to Enhance MSD Research Working Group Co-Chair); Patrick M. Reed (MSD CoP Facilitation Team) This webinar was held on: November 13th, 2025 from 12-1 PM EST.

Artificial Intelligence↗

Annular Seals of High Energy Centrifugal Pumps: Presentation of Full Scale Measurement

Prediction of rotordynamic behavior for high energy concentration centrifugal pumps is a challenging task which still imposes considerable difficulties. While the mechanical modeling of the rotor is solved most satisfactorily by finite element techniques, accurate boundary conditions for arbitrary operating conditions are known for journal bearings only. Little information is available on the reactive forces of annular seals, such as neck ring and interstage seals and balance pistons, and on the impeller interaction forces. The present focus is to establish reliable boundary conditions at annular seals. For this purpose, a full scale test machine was set up and smooth and serrated seal configurations measured. Dimensionless coefficients are presented and compared with a state of the art theory.

Florjancic, S.↗

A comparison study on trading behavior and profit distribution in local energy transaction games

With the increasing integration of distributed energy resources, localized peer-to-peer energy transactions are receiving more attention since they could absorb more distributed renewables locally and stabilize the power grid. To better study the trading behavior and provide guidance for a viable local market design, different game-theoretical frameworks including cooperative and non-cooperative games are established and compared here. For the cooperative grand coalition, the maximum social welfare is guaranteed, the Shapley value and bargaining based approaches are implemented for further profit redistribution. It is shown that the asymmetrical bargaining power can be critical in the final payment clearing and it is equivalent to the Shapley value allocation if prosumers bargain based on their marginal contributions. Non-cooperative trading is formulated by using a Stackelberg bilevel model in which the upper level has the privilege in internal price setting. However, system optimum is not obtained due to competition, and the selfish leader could take away 89% of the collective benefit by price-gap based arbitraging. Aiming for a long-lasting trading market, a virtual benevolent leader and a uniform price structure in which purchase price equals selling price are tested. Experimental results indicate that maximum social welfare and a fairer profit allocation can be achieved with a uniform price structure, regardless of the selfish or benevolent attitude.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A dataset for understanding self-reported patterns influencing residential energy decisions

Household occupant behavior and decision-making dynamics substantially impact technology uptake and residential building energy performance. Although significant research underscores the importance of social science in energy studies, few public data with representative samples on household energy decision-making patterns are available. The dataset (UPGRADE-E: Understanding Patterns Guiding Residential Adoption and Decisions about Energy Efficiency) presents 9,919 responses from U.S. residents of single-family and small multifamily homes. Derived from a national-scale internet survey, the dataset contains 391 variables: demographics, building characteristics, home modifications, willingness to adopt new technologies, motivations for making changes, barriers, program participation, trusted information sources, and energy scenarios. Responses were validated via internal consistency checks and comparison with other U.S. national scale datasets. UPGRADE-E advances knowledge of household energy related decision-making, tying demographics, home modifications, and self-reported cognitive drivers together at a scale and breadth that has not been previously achieved. Policymakers and researchers at local, regional, and national levels may leverage this dataset to understand drivers influencing the adoption of key technologies in U.S. homes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Numerical and experimental evaluation of mechanical performance of the multifunctional energy storage composites

This work presents numerical simulation methods to model the mechanical behavior of the multifunctional energy storage composites (MESCs), which consist of a stack of multiple thin battery layers reinforced with through-the-hole polymer rivets and embedded inside carbon fiber composite laminates. MESC has been demonstrated through earlier experiments on its exceptional behavior as a structural element as well as a battery. However, the inherent complex infrastructure of the MESC design has created significant challenges in simulation and modeling. A novel homogenization technique was adopted to characterize the multi-layer properties of battery material using physics-based constitutive equations combined with nonlinear deformation theories to handle the interface between the battery layers. Second, mechanical damage and failure modes among battery materials, polymer reinforcements, and carbon fiber-polymer interfaces were characterized through appropriate models and experiments. The model of MESCs has been implemented in a commercial finite element code in ABAQUS. A comparison of structural response and failure modes from numerical simulations and experimental tests are presented. The results of the study showed that the predictions of elastic and damage responses of MESCs at various loading conditions agreed well with the experimental data. © 2021

Materials Science↗

Understanding Electric Vehicle Range and Charging Needs: Interactions Between Ambient Temperature, Commute Patterns, and State-of-Charge Usage

Electric vehicle (EV) performance can vary substantially under real-world operating conditions, particularly due to ambient temperature effects on energy consumption, battery behavior, and thermal management requirements. This study quantifies how weather conditions, daily driving patterns, and State-of-Charge (SOC) usage strategies jointly influence EV driving range, charging frequency, and overall energy efficiency. A detailed and experimentally validated Autonomie vehicle model is developed, integrating a powertrain, a mono-zonal cabin model, and a battery electro-thermal model. Three battery sizes (200-, 300-, and 400-mile homologated ranges) are assessed across five commute profiles (20–200 miles) and six ambient temperatures (−18 °C to 50 °C), including scenarios with and without preconditioning. Results show that extreme temperatures could significantly decrease the maximum achievable range by up to 55% in cold conditions (−18 °C) and 40% in hot conditions (50 °C), relative to moderate conditions. Larger battery packs retain a greater fraction of their nominal range under thermal stress, while smaller packs experience sharper relative penalties due to the higher contribution of thermal loads to total energy demand. The analysis further demonstrates that limiting operation to partial SOC windows (e.g., 80–20%), a common real-world practice, significantly reduces achievable range and increases charging frequency, particularly in cold weather. Thermal preconditioning while plugged in is shown to mitigate these effects for short trips, reducing energy consumption by up to 31% in hot conditions and 7% in cold conditions. The findings demonstrate how climate, SOC usage behavior, and thermal management jointly shape the practical driving capability of EVs, highlighting the importance of efficient thermal management and realistic user charging strategies for ensuring reliable EV operation across diverse climatic scenarios.

33 ADVANCED PROPULSION SYSTEMS↗

A triple junction energy study using an inclination-dependent anisotropic Monte Carlo Potts grain growth model

This work presents a Monte Carlo Potts grain growth model in which the grain boundary (GB) energies depend on the GB inclination. The inclination is calculated using a linear smoothing approach developed by the authors. In bicrystal simulations with a shrinking grain, the grain changes shape to prefer low energy GB inclinations. However, in polycrystal simulations the preferred inclinations depend on the approach used to assign the triple junction (TJ) energies. Approaches that produce unimodal TJ energy distributions result in the expected behavior of preferring low energy GB inclinations. However, approaches that produce bimodal TJ energy distributions result in medium energy or even high energy inclinations being preferred. Overall, this study underscores the importance of TJs in anisotropic grain growth.

Grain boundary inclination↗

Chapter 17: Residential Behavior Evaluation Protocol. The Uniform Methods Project: Methods for Determining Energy Efficiency Savings for Specific Measures, September 2011 - August 2020

This document has been updated in August 2020. This document was developed for the U.S. Department of Energy Uniform Methods Project (UMP). The UMP provides model protocols for determining energy and demand savings that result from specific energy-efficiency measures implemented through state and utility programs. In most cases, the measure protocols are based on a particular option identified by the International Performance Verification and Measurement Protocol; however, this work provides a more detailed approach to implementing that option. Each chapter is written by technical experts in collaboration with their peers, reviewed by industry experts, and subject to public review and comment. The protocols are updated on an as-needed basis. The UMP protocols can be used by utilities, program administrators, public utility commissions,evaluators, and other stakeholders for both program planning and evaluation. To learn more about the UMP, visit the website, https://energy.gov/eere/about-us/ump-home, or download the UMP introduction document at http://www.nrel.gov/docs/fy17osti/68557.pdf.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Theoretical Investigations in Elementary Particle Physics and Cosmological Physics

The goals of this project were to improve our understanding of the fundamental constituents of the universe, at both the smallest and largest scales. At the smallest scales, we examined the masses and mixings of neutrinos, to understand and probe for physics beyond the Standard Model at the LHC, and to explore models in quantum field theory. At the largest scales, we investigated the sources of high-energy neutrinos and cosmic rays, the nature of dark matter, and the behavior of dark energy. This report centers on the final extension period, which was focused on publications of the research.

79 ASTRONOMY AND ASTROPHYSICS↗

An experimental test for the charge state of the 'anomalous' helium component

Observations of phase lags between intensity variations for various particle species and energy ranges in the low-energy galactic cosmic radiation during the general intensity decrease observed in 1974-1975 show that, for particles whose charge state is known (i.e., 'normal' cosmic-ray components), particles with higher rigidities respond more quickly to changes in modulation conditions than do those with lower rigidities. When compared with particles of known energy and charge, the behavior of the 'anomalous' low-energy helium component is consistent with these observations only if the helium is singly rather than doubly charged.

Mckibben, R. B.↗

Performance, defect behavior and carrier enhancement in low energy, proton irradiated p+nn+ InP solar cells

The highest AMO efficiency (19.1 percent) InP solar cell consisted of an n+pp+ structure epitaxially grown on a p+ InP substrate. However, the high cost and relative fragility of InP served as motivation for research efforts directed at heteroepitaxial growth of InP on more viable substrates. The highest AMO efficiency (13.7 percent) for this type of cell was achieved using a GaAs substrate. Considering only cost and fracture toughness, Si would be the preferred substrate. The fact that Si is a donor in InP introduces complexities which are necessary in order to avoid the formation of an efficiency limiting counterdiode. One method used to overcome this problem lies in employing an n+p+ tunnel junction in contact with the cell's p region. A simpler method consists of using an n+ substrate and processing the cell in the p+ nn+ configuration. This eliminates the need for a tunnel junction. Unfortunately, the p/n configuration has received relatively little attention the best cell with this geometry having achieved an efficiency of 17 percent. Irradiation of these homoepitaxial cells, with 1 Mev electrons, showed that they were slightly more radiation resistant than diffused junction n/p cells. Additional p/n InP cells have been processed by some activity aimed at diffusion. Currently, there has been some activity aimed at producing heteroepitaxial p+nn+ InP cells using n+ Ge substrates. Since, like Si, Ge is an n-dopant in InP, use of this configuration obviates the need for a tunnel junction. Obviously, before attempting to process heteroepitaxial cells, one must produce a reasonably good homoepitaxial cell. In the present case we focus our attention on homoepitaxially on an n+ Ge substrate.

Weinberg, I.↗

Data-driven occupant-behavior analytics for residential buildings

Many advances have been made in building technology to help save energy, but influencing the behavior of the occupants is still necessary to achieve low-energy use targets. One of the most practical ways to influence and change occupant behaviors is through incentives. Developing incentives for energy-saving and quantifying the impact of occupant behaviors are both active areas of research. Here, we propose a data analytics framework for detecting changes in occupant behaviors, which will help build an analytics feedback loop from behavior impact to incentive design. The framework has two major parts. The first forecasts energy consumption for each occupant, while the second determines a probability distribution for changes in energy consumption. The parts are interchangeable with other existing machine learning and statistical methods. A specific instantiation of the framework, using kernel ridge-regression for forecasting and k-means to find an empirical behavior distribution, is described in detail. An HVAC use-case with 5 different incentivized behaviors is used as an example to show that the framework can detect behavior changes induced by incentives. Furthermore, we show that some simpler behavior-change detection methods do not work, further justifying the use of advanced analytics.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Enhancing occupant behavior representation for interoperability between building information modeling and building energy modeling

Building Performance Simulation (BPS) has been adopted as an essential tool for designing, operating, and retrofitting buildings to optimize energy efficiency throughout the building life cycle. The Green Building XML (gbXML) schema facilitates seamless data exchange between Building Information Modeling (BIM) and Building Energy Modeling (BEM) software tools. However, limited occupant behavior (OB) representation in BIM often leads to inconsistent and inaccurate energy simulation in BEM software. This paper presents 154 systematic enhancements to the existing occupant behavior XML (obXML) schema v1.3.4, initially developed for standardizing OB representation for BEM, to address existing limitations and improve interoperability with BIM models. The enhancements encompass improved integration with BIM models through extended building representations and system operations, expanded support for advanced OB models with additional environmental parameters and mathematical capabilities, and implementation of a standardized model documentation framework. To facilitate seamless data transformation between gbXML and obXML schemas, we developed a publicly available gb-obXML Schema Converter. Three case studies demonstrate the enhanced schema’s capabilities: representation of building information using a two-story office building model, documentation of a window operation behavior model, and validation of the schema converter’s functionality. The enhanced obXML schema v1.4 enables sophisticated modeling of occupant-building interactions while maintaining consistency with industry-standard BIM schemas. The standardized documentation framework facilitates reproducibility and knowledge sharing in the OB research community, while the schema converter automates the integration of building information into OB simulation workflows. These enhancements establish a foundation for more accurate building performance simulation by supporting sophisticated representation of occupant behavior within the BIM-to-BEM simulation workflows.

Chung, Jihoon↗

Composition and spectra of primary cosmic-ray electrons and nuclei above 10 GeV

Recent experiments have extended the knowledge of the flux and energy spectra of individual cosmic-ray components to much higher energies than had previously been accessible. Both electron and nuclear components show a behavior at high energy which is unexpected, and which carries information regarding the sources and the propagation of particles between sources and observer. Electromagnetic interactions which are suffered by the electrons in interstellar space should steepen their spectrum, a steepening that would reveal the average lifetime a cosmic-ray particle spends in the galaxy. Measurements up to 1000 GeV show no such steepening. It was discovered that the composition of the nuclear species which is now measured up to 100 GeV/nucleon changes with energy. This change indicates traversal of less interstellar matter by the high energy particles than by those of lower energy.-

Meyer, P.↗