Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Energy use”

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 973 records · Page 54

Summary of Expansions and Updates in GREET® 2020

The GREET® (Greenhouse gases, Regulated Emissions, and Energy use in Technologies) model has been developed by Argonne National Laboratory with the support of the U.S. Department of Energy (DOE). GREET is a life-cycle analysis (LCA) tool, structured to systematically examine the energy and environmental effects of a wide variety of transportation fuels and vehicle technologies in major transportation sectors (i.e., road, air, marine, and rail) and other end-use sectors, and energy systems. Argonne has expanded and updated the model in various sectors in GREET 2020, and this report provides a summary of the release.

33 ADVANCED PROPULSION SYSTEMS↗

Atomically Precise Membranes for the Separation of Gases

Industrial separations require enormous amounts of energy, accounting for approximately half the industrial energy use and 10–15% of the total energy consumption. Distillation alone accounts for about half the energy demand for industrial separations. If these processes could be replaced by an energy-efficient membrane separation process, this energy demand could be reduced by 90%. However, although some membrane processes have made inroads into thermal distillation, for membrane-based separations to replace the distillation process to a far more significant and practical level, new membranes with higher robustness, selectivity, and flux still need be developed. In this membrane development program, we leveraged Temple University’s prior work in spiroligomers to develop robust membrane structures. These structures can be formed into atomically precise pores by controlling the chemical synthesis and the oligomer building blocks to first build precisely controlled macrocycles and then subsequently crosslinking these macrocycles to produce a membrane. Furthermore, through the highly controllable chemistry of our molecular building blocks, not only can we integrate pores with highly controllable and reproducible size and morphology, but we can also target internal functionalization. By using a range of scalable membrane synthesis approaches, combined with control of each and every pores internal chemistry and molecular conformation we can achieve membrane structures that can display the ultimate in high selectivity and permeance. The Mainstream-Temple University membranes can be designed to achieve ultra-selective separations based on the key factors of molecular size, shape, and functionality. In our approach to fabricate scalable atomically precise membranes, we used our molecular Lego nanostructures. We demonstrated an approach to create atomically precise pores within the membrane with pores that are the dimensions of the molecule we are trying to separate. Moreover, in addition to controlling the morphology of the membrane structure by controlling the size of every pore, we can also decorate every pore with precisely targeted and placed functional groups. These accurately placed functional groups can provide selective binding to molecules and provide enhanced selectivity via a facilitated transport mechanism. In Phase II, the Mainstream-Temple University team demonstrated the scalable synthesis of oligomers and the ability to control the pore internal and external functionality, or chemistry, to allow the fabrication of a thin-film membrane. The initial steps of the spiroligomer synthesis to produce the two key bis-amino enantiomer building blocks were scaled from the gram scale to the kilogram scale, obtaining 25 kg of the materials by transferring the procedure to a toll manufacturer. Finally, we successfully optimized the fabrication of these macrocycles into robust membranes. We successfully transitioned from a laboratory based, hard-to-scale Langmuir trough synthesis to a highly scalable, roll-to-roll applicable, interfacial polymerization process. During this Phase II program, we established a platform of atomically precise membranes where our highly controllable, atomically precise macrocycles served as a scaffold with precisely and uniformly controlled pores. Furthermore, this layer can be tailored to accommodate a diverse range of functional groups, which both further controlled the pore size to enhance the sieving effect as well as imparting precisely controlled targeted selectivity through biomimetic molecular interactions. In this Phase II, we established and scaled up a platform approach to both tune the pore size and chemistry as well as scale it to produce membranes that can be applied to a wide range of industries. In future development, the project team expects to scale up both the macrocycle building block production and interfacial polymerization process to produce the atomically precise membrane with targeted pore sizes and pore chemistries.

36 MATERIALS SCIENCE↗

Comparative life cycle analysis on ethylene production from electrocatalytic reduction of carbon dioxide

Ethylene is one of the largest greenhouse gas emitters and the most diversly used commodity chemicals globally. Electrocatalytic reduction of CO 2 to ethylene received great attention from the research society to decarbonize the ethylene production. Here, in this study, a life-cycle analysis is conducted using the Greenhouse Gases, Regulated Emissions, and Energy use in Technologies (GREET) model on the three electrocatalytic CO 2 -reduction pathways (or “e-ethylene” pathways): i) cascade conversion via carbon monoxide intermediate; ii) single-step conversion in membrane electrode assembly (MEA); and iii) single-step conversion in alkaline flow cell. The results showed that the electricity consumption is the lowest for the cascade pathway (164 MJ/kg), thus resulting in the lowest cradle-to-gate carbon intensity [18 kgCO 2 e/kg with United States (US) average grid)] among the three pathways followed by the single-step MEA (32 kgCO 2 e/kg) and then by the single-step alkaline (56 kgCO 2 e/kg). However, all three e-ethylene pathways were significantly more carbon-intensive than their fossil-based counterpart (1.1 kgCO 2 e/kg) due to their excessive energy consumption with the current state of technology. With renewable electricity, all three pathways yielded negative carbon intensity: from -3.1 kgCO 2 e/kg to -1.6 kgCO 2 e/kg depending on the source of CO 2 . The threshold carbon intensity of electricity (TCIE), defined as the upper bound of the carbon intensity of electricity to achieve lower carbon intensity for e-ethylene compared to fossil-based ethylene, is calculated for both current and future state of e-ethylene technologies. The cascade pathway had the highest TCIE out of the three e-ethylene pathways for both current (92 gCO 2 e/kWh) and future (124 gCO 2 e/kWh) state of technologies. However, the carbon intensity of average US grid (i.e., 467 and 303 gCO 2 e/kWh for current and future projections) were higher than the TCIEs of the corresponding timeline. Thus, reducing electricity requirement for e-ethylene pathways and bringing low-carbon generation mix in the United States (US) grid faster than the current projection are both essential to decarbonize ethylene and its downstream chemicals/polymers.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Patch-Based Convolutional Neural Networks for Multiple Microstructural Features Detection in FIB-SEM Micrographs of Irradiated Nuclear Fuel

Focused ion beam scanning electron microscopy (FIB-SEM) tomography has increasingly been utilized for acquiring three-dimensional (3D) microstructure features at the sub-micron scale in irradiated nuclear materials. This technique involves sequential ion beam slicing followed by electron beam imaging and compositional mapping using energy dispersive spectroscopy (EDS). Despite its growing use, several challenges persist. These include the time-intensive nature of data collection of EDS data, difficulties in distinguishing between various microstructures, and issues with image alignment. These challenges currently limit the broader application of FIB-SEM tomography in the field. To overcome these limitations, we propose using convolutional neural networks (CNNs) to automate microstructure identification in SEM images. Our study introduces a new framework for identifying microstructures in irradiated U-10Zr (wt. %) metallic fuel with limited annotated data. The framework includes the creation of a reliable annotated dataset with paired SEM and ground truth data from EDS maps, the applications of CNNs for microstructure identification, and the validation of model performance. Specifically, we employed the Segment Anything Model (SAM) to align SEM images with corresponding EDS maps and focused ion beam (FIB) tomography SEM data. We evaluate several models, including Patch-based U-Net, Attention U-Net, and Residual U-Net, finding that patch-based U-Net exhibits superior segmentation performance and consistency. This approach reduces reliance on EDS detectors and aids in accelerating nuclear material analysis process, highlighting the potential of advanced deep learning techniques to improve microstructural understanding in nuclear material. This is the first framework to integrate SAM and Patch-based CNN models for semantic segmentation of irradiated nuclear materials, with potential applicability to other tomography datasets.

36 - MATERIALS SCIENCE↗

Sensitivity analysis of cool-down strategies for a transonic cryogenic tunnel

Guidelines and suggestions substantiated by real-time simulation data to ensure optimum time and energy use of injected liquid nitrogen for cooling the Langley 0.3-Meter Transonic Cryogenic Tunnel (TCT) are presented. It is directed toward enabling operators and researchers to become cognizant of criteria for using the 0.3-m TCT in an energy- or time-efficient manner. Operational recommendations were developed based on information collected from a validated simulator of the 0.3-m TCT and experimental data from the tunnel. Results and trends, however, can be extrapolated to other similarly constructed cryogenic wind tunnels.

Thibodeaux, J. J.↗

Summary of Expansions and Updates in R&D GREET ® 2023

The Greenhouse gases, Regulated Emissions, and Energy use in Technologies (GREET®) model was developed by Argonne National Laboratory (Argonne) with the support of the U.S. Department of Energy (DOE) and other federal agencies. R&D GREET is a life cycle analysis (LCA) model, structured to systematically examine the energy and environmental effects of a wide variety of transportation fuels and vehicle technologies in major transportation sectors (i.e., road, air, marine, and rail), other end-use sectors, and energy systems. Argonne has expanded and updated the model in various areas in R&D GREET 2023. This report provides a summary of the expansions and updates.

33 ADVANCED PROPULSION SYSTEMS↗

Summary of Expansions and Updates in GREET ® 2021

The GREET® (Greenhouse gases, Regulated Emissions, and Energy use in Technologies) model has been developed by Argonne National Laboratory (Argonne) with the support of the U.S. Department of Energy (DOE). GREET is a life-cycle analysis (LCA) tool, structured to systematically examine the energy and environmental effects of a wide variety of transportation fuels and vehicle technologies in major transportation sectors (i.e., road, air, marine, and rail) and other end-use sectors, and energy systems. Within the transportation sector, GREET covers road, air, water, and rail transportation sub-sectors. Recently, GREET was expanded to cover the building sector. Historically, GREET includes LCA of various materials such as steel, aluminum, cement, and different plastic types. Argonne has expanded and updated the model in various sectors in GREET 2021, and this report provides a summary of the release.

09 BIOMASS FUELS↗

Summary of Expansions and Updates in GREET ® 2022

The GREET ® (Greenhouse gases, Regulated Emissions, and Energy use in Technologies) model has been developed by Argonne National Laboratory (Argonne) with the support of the U.S. Department of Energy (DOE) and other federal agencies. GREET is a life cycle analysis (LCA) tool, structured to systematically examine the energy and environmental effects of a wide variety of transportation fuels and vehicle technologies in major transportation sectors (i.e., road, air, marine, and rail) and other end-use sectors, and energy systems. Argonne has expanded and updated the model in various sectors in GREET 2022, and this report provides a summary of the release.

25 ENERGY STORAGE↗

Micro-Environmental Control System (Final Report)

This project developed an innovative micro-environmental control system (µX) that enables office buildings to reduce energy used for heating and cooling by 15% or more. The µX is a compact, quiet, and ergonomic device that is designed to be installed under an office workstation; it is designed to maintain occupant comfort when room thermostat setpoints are incremented by 4°F or more (warmer in the summer and cooler in the winter) to save energy. When ambient room temperatures are outside of the usual comfort range, the µX maintains occupant comfort by delivering personalized cooling or heating locally to each office worker. The µX provides personalized cooling using a micro vapor compression system that includes a new high-performance micro-scroll compressor and a novel thermal storage unit. The vapor compression system operates at night to freeze a phase-change material (PCM). During the workday, the cooling stored in the PCM is released as a cool breeze of air to make occupants more comfortable. The micro-scroll compressor was developed specifically for this application; it is smaller than any of its type, minimizing the amount of power needed. In heating mode, the µX maintains occupant comfort using a foot heating mat with an infrared reflective box. The µX R&D project was conducted by Syracuse University in collaboration with United Technologies Research Center, Air Innovations, Bush Technical, and Cornell University. Over the course of the initial three-year project, the team developed and evaluated four versions of the unit, advancing the concept to Technology Readiness Level 6. The capabilities of individual proof-of-concept prototypes were verified in tests that were conducted with: 1) units in psychrometric chambers, 2) an instrumented manikin in a laboratory, and 3) human subjects in laboratories that simulate office environments. The tests verified that the µX prototypes met or exceeded all performance targets required to enable office buildings to reduce energy used for heating and cooling by 15% or more by maintaining occupant comfort when thermostat setpoints are incremented by 4°F or more.

25 ENERGY STORAGE↗

Incorporating Elevation in Traffic-Vehicle CO-Simulation: Issues, Impacts, and Solutions

Traffic-vehicle co-simulation couples microscopic traffic simulation with full-body vehicle dynamics to assess system-level impacts on mobility, energy, and safety with greater realism. Incorporating elevation is critical for accurately modeling vehicle behavior and energy use, especially for gradient-sensitive vehicles such as electric and heavy-duty trucks. However, raw elevation data often contain noise, discontinuities, and inconsistencies. While such issues may be negligible in traditional traffic simulations, they significantly affect traffic-vehicle co-simulations where vehicle dynamics are sensitive to road grade variations. This paper investigates the impact of unprocessed elevation data on vehicle behavior and energy consumption using a 42-mile simulation along Interstate 81. We propose an elevation processing workflow that can mitigate the effects stem from elevation data issues, improving the realism and stability of traffic-vehicle co-simulation. Results show that the method effectively removes noise and abrupt elevation transitions while preserving roadway geometry.

Xu, Guanhao [ORNL] (ORCID:0000000214326357)↗

Holistic Transportation and Energy Modeling

This project advances the development and application of the TEMPO transportation energy systems model to support DOE analysis of evolving mobility futures. Recent work has focused on improving model transparency, performance, and fidelity through a redesigned software architecture and updated technology adoption scenarios aligned with the latest data and assumptions. Ongoing efforts aim to expand TEMPO's ability to assess transportation affordability and consumer decision-making, including vehicle ownership dynamics and distributional impacts across households. These enhancements position TEMPO to better inform policy and R&D decisions by providing more behaviorally realistic and policy-relevant insights into transportation energy use, technology adoption, and system-level outcomes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Energy efficiency and thermal resilience analysis for row houses using representative building energy models

Row houses, a prevalent medium-density urban archetype, were popularized during industrial era to accommodate the working class in the U.S. cities. Today, many of these structures are deteriorating, exacerbating the energy cost for residents with limited economic resources. Moreover, many households that lack Air Conditioning (AC) are vulnerable to extreme summer heat, an issue expected to worsen in the future. Energy-efficient retrofits can help mitigate these challenges. However, current literature provides limited insight into how existing building energy codes impact the energy efficiency and thermal resilience of row houses in current and future weather scenarios. This study provides a detailed method to address this gap by employing calibrated representative energy models of row houses as a baseline, and evaluating the annual energy savings and summertime thermal safety improvements from code compliant retrofits under current and future typical weather conditions. Using Baltimore City as a case study, results show that under current weather, retrofitting row houses yields significant energy savings along with notable thermal resilience improvements. The end unit row house realizes higher energy savings, whereas the interior unit experiences greater thermal resilience improvement after retrofitting. In future, retrofitted row houses can still save energy, but residents will face numerous hours of fatal indoor temperatures without AC in summer. Additionally, findings reveal stark zone-wise variations in thermal safety, and elevated humidity risks in certain zones post-retrofit, emphasizing the need for zonal retrofit strategies and better natural ventilation strategies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Comparing energy and water use of aqueous and gas-based metalworking fluids

Gas-based metalworking fluids (MWFs) have been proposed as alternative coolants and lubricants in machining operations to mitigate concerns surrounding water use and pollution, industrial hygiene, occupational health, and performance limitations associated with water-based (aqueous) MWFs that are ubiquitously used in the metals manufacturing industry. This study compares the primary energy and water use associated with the consumptive use, delivery, and disposal of aqueous MWFs with three gas-based MWFs in the literature-minimum quantity lubricant-in-compressed air (MQL), liquid/gaseous N-2, and liquid/supercritical CO2. The comparison accounts for reported differences in machining performance in peer-reviewed experimental studies across several machining processes and materials. The analysis shows that despite the reported improvement in tool life with N-2 and CO2-based MWFs, the electricity- and water-intensive separation and purification processes for N-2 and CO2 lead to their higher primary energy and water use per volume of material machined relative to water-based MWFs. Although MQL is found to have lower primary energy use, significant consumptive water use associated with the vegetable oil commonly used with this MWF leads to higher overall water use than aqueous MWF, which is operated in a recirculative system. Gas-based MWFs thus shift the water use upstream of the manufacturing plant. Primary energy and water use of gas-based MWFs could be reduced by focusing on achieving higher material removal rates and throughput compared to aqueous MWF instead of solely targeting improvements in tool life. Additionally, the consumptive use of CO2 and N-2 MWFs could be minimized by optimizing their flow rates and delivery to precisely meet the cooling and lubrication needs of specific machining processes instead of flooding the tool and workpiece with these gases. This article met the requirements for a gold-gold JIE data openness badge described at http://jie.click/badges.

cutting fluids↗

Summary of Expansions and Updates in R&D GREET® 2025

The research and development (R&D) version of Greenhouse gases, Regulated Emissions, and Energy use in Technologies (GREET®) model, or R&D GREET, is developed by Argonne National Laboratory (Argonne) with the support of the U.S. Department of Energy (DOE) and other federal agencies. R&D GREET is a life cycle analysis (LCA) model, structured to systematically examine the energy and environmental effects of a wide variety of transportation fuels and vehicle technologies in all transportation sub-sectors (i.e., road, air, marine, and rail) and other end-use sectors, and energy technology systems. Argonne has expanded and updated the model in many areas in R&D GREET 2025. This report provides a summary of the expansions and updates. R&D GREET is designed as an attributional LCA model, but specific consequential effects for certain pathways are included by default when they are scientifically important and/or highly policy relevant. For example, two major consequential elements – induced land use change (ILUC) for biofuels and avoided emissions for certain RNG-based pathways – are implemented by default in R&D GREET because they are highly relevant to our user base and crucial for a comprehensive evaluation of the environmental effects of these technologies. In a future version of R&D GREET, these consequential elements for biofuels and RNG could be more clearly distinguished from core attributional results. We will consider adding a highly visible toggle that would allow users to turn off or adjust these consequential impacts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

U.S. Geothermal District Heating Systems and Funding Data

This dataset contains detailed information on geothermal district heating (GDH) systems across the United States, including technical specifications, costs, energy usage, and funding sources. Data includes system details such as state, site, location, operational years, temperature, flow rate, capacity, energy use, load factor, costs (original, updated, and operational), funding sources, employment impact, and project status. Additionally included are contributions to GDH systems, including federal, state, and local grants, as well as loans from agencies such as USDA and USDOE. This dataset serves as a resource for analyzing the economic and technical landscape of geothermal district heating in the United States.

15 GEOTHERMAL ENERGY↗

Lab Homes

This dataset includes processed data from the Lab Homes (LH) Test Facility located on the PNNL campus in Richland, WA. This a set of 2 identical homes that allow for the side-by-side comparison/performance evaluation of different technologies under the same weather at any given time. The dataset spans December 6, 2021 to December 27, 2021 and represents a series of tests performed; calibration, set-point excitation, pre-heating, free-floating and warm up. The measurements correspond to whole building electrical power, HVAC energy use, water heating, appliances and lighting, as well as space temperatures, space humidity, window glass surface temperatures, through glass solar radiation, and meterological data from an onsite meteorological weather station. In addition to the measurements, a metadata .json file, a .ttl file to visualize the data as per BRICK schema, and a detailed .pdf description of the dataset are also provided.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Summary of Expansions and Updates in R&D GREET ® 2024

The research and development (R&D) version of Greenhouse gases, Regulated Emissions, and Energy use in Technologies (GREET ® ) model, or R&D GREET, is developed by Argonne National Laboratory (Argonne) with the support of the U.S. Department of Energy (DOE) and other federal agencies. R&D GREET is a life cycle analysis (LCA) model, structured to systematically examine the energy and environmental effects of a wide variety of transportation fuels and vehicle technologies in major transportation sectors (i.e., road, air, marine, and rail) and other end-use sectors, and energy technology systems. Argonne has expanded and updated the model in various areas in R&D GREET 2024.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗