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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 289 records · Page 16

Understanding and Improving Energy Efficiency of Regional Mobility Systems Leveraging System-Level Data

Increased congestion required urban Americans to travel 6.8 billion hours more and purchase 3.1 billion gallons of fuel for a congestion cost of $\$$153 billion, according to the 2019 Urban Mobility Report. How to effectively manage the regional mobility system and improve the energy efficiency presents a big challenge to public agencies. Recent years have witnessed massive multi-jurisdictional multi-modal system-level data from various sources, which provides an unprecedented opportunity to improve the mobility system and its energy efficiency. However, implications of system-level data for mobility and energy efficiency are unclear. Those system-level data sets are siloed, spatially and temporally sparse, biased, not unified, and lacking of insights for system management. Consequently, there is a real need to acquire, fuse, mine and learn from multi-source system-level data to prepare public agencies to deal more effectively with large-scale energy efficiency modeling, management and planning. This project proposes to intensively review inexpensive, replicable and openly-accessible data from multi-modal systems, develop a data-driven system-level modeling framework enabled and validated by data, identify the energy inefficiencies of mobility systems from infrastructure, vehicles, passenger systems, and quantify the benefits of system-level strategies to improve mobility/energy efficiency. In addition, this research develops models to effectively estimate energy consumption and emissions from various types of vehicles on the roadway networks, with high granularity and high fidelity. Traditional models often heavily rely on aggregated infrastructure or vehicle/passenger data, for example, the census survey, land-use, and traffic counts of one or several classes, which may lead to research gaps considering the emerging vehicle technologies. Those models do not contain individual vehicular information. We propose an integrated data-driven method that combines multiple network modeling components, featuring the utilization of state-wide vehicle registration data. The additional vehicle registration data improve the model performance, and produce high-resolution vehicle-specific estimates of emissions and network performance metrics. Two case studies on the Pittsburgh and Philadelphia regional network show that the proposed method can efficiently and effectively estimate the emissions of a large-scale network, and provide valuable information for evaluating common management strategies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Low Carbon Development Pathways for Cooling: Leveraging Kigali Amendment Across Residential Applications

Heating and cooling demand for space conditioning and refrigeration accounts for around a fifth of global final energy consumption. Climate change, urbanisation, and economic development have tripled electricity demand for cooling alone since the 1990s, with the majority coming from the use of inefficient cooling equipment, which burdens electricity grids, especially during the peak hours. It is imperative to address the energy required to provide cooling. The Kigali Amendment to the Montreal Protocol addresses these needs by setting ambitious global targets to phase down refrigerants with high global warming potential, while improving energy efficiency. Integrating energy efficiency and the refrigerant transition will contribute to economic security, well-being, energy access and security, and sustainability among the G20 countries.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Leveraging Computational Storage Devices in Campaign Storage [Slides]

Computational storage provides new ways of accelerating data-intensive applications. In-drive data management schemes matter (O_DIRECT, clustered index). Layer violation: “cheating” one filesystem may be possible; cheating multiple layers of filesystems is hard (FS internal load balancing, fail over, compression, concurrency control). The future directions include block-based acceleration to object-based acceleration.

97 MATHEMATICS AND COMPUTING↗

Leveraging the bioeconomy for carbon drawdown

Stringent climate change mitigation scenarios rely on large-scale drawdown of carbon dioxide from the atmosphere. Amongst drawdown technologies, bioenergy with carbon capture and sequestration (BECCS) has received considerable attention in the climate mitigation literature. Recently, attention has shifted further from a relatively narrow focus on BECCS to a broader focus on Biomass Carbon Removal and Storage (BiCRS). The concept of BiCRS has the potential to enable a future where the climate mitigation value of biomass resources is more valuable than the energy value, due to the potential to remove and sequester large quantities atmospheric CO 2 . This article provides a qualitative overview of prominent BiCRS technologies from which a set of the most promising technologies are assessed quantitively through life cycle assessment. There are numerous opportunities to incorporate carbon removal and management within the bioeconomy, but the majority of immediate carbon removal potential exists in four bioproducts: bioenergy, bioplastics, biochar, and wood products. We analyze the life cycle greenhouse gas emissions and disposition of sequestered carbon over 10,000 years for four bioproducts representative of each broader category: an advanced BECCS pathway, biopolyethylene, oriented strand board, and biochar soil amendment. We find that the BECCS pathway has the greatest magnitude and durability of CO 2 storage over all time horizons. However, non-BECCS pathways achieve 34–64% of the drawdown magnitude relative to BECCS and retain 55–67% of their initial drawdown over 100 years (central estimate). We identify three engineering strategies for enhancing carbon drawdown: reducing biomass supply chain emissions, maximizing carbon stored in long lived products, and extending the term of carbon storage. Finally, we highlight the need to characterize both the magnitude and permanence of carbon drawdown as a means for policymakers and technology develo pers to deploy limited biomass resources to maximize mitigation benefits.

09 BIOMASS FUELS↗

Commercial PACE Project Origination: Leverage Points for Growing the Project Pipeline

Greater use of Commercial Property Assessed Clean Energy (C-PACE) financing within communities where it is enabled will increase energy savings, drive economic development, and result in additional public benefits. Some states with active C-PACE programs have ramped up activity significantly while others have not achieved and sustained a high volume of transactions. This brief details C-PACE project origination trends, barriers, and market practices for state and local government C-PACE program sponsors looking to grow their C-PACE project pipeline.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Leveraging metal hydrides for strategic thermal energy control

Attributes of Sensible Heat Materials • Typically based on highly abundant and lowcost materials • Store thermal energy based on the heat capacity (or specific heat) of the material • Duration of thermal energy storage depends on how well the system is insulated • Has the lowest thermal energy storage density • Can be pumped as a fluid Attributes of Latent Heat Materials • Also based on highly abundant materials, but typically cost slightly more than sensible heat materials • Store thermal energy based on the heat of the phase change (i.e., heat of fusion) and the specific heat of the material • Duration of thermal energy storage depends on how well the system is insulated • Has a higher thermal energy storage density than sensible heat materials, but cannot be pumped as a fluid

WARD, PATRICK↗

Carbon Capture through Membranes - Leveraging Multiphysics Modeling, Dimensional Analysis and Machine Learning to Scale up and Optimize Devices and Processes for Decarbonization

We study the separation performance using membrane modules through dimensional analysis (DA). We formulate the main process equations to identify relevant dimensionless numbers inherent in the physics. In particular, we identify that the critical step in the separation process is mass transfer through the selective layer. Remarkably, the dimensionless feed flow (DFfeed) emerges as a crucial factor in describing this process. Not only does DFfeed directly appear in the governing equations, but it also holds a physical significance associated with the time scales for the mass transfer across the feed side and through the selective layer. Regarding the output performance variables, we consider the recovery, stage cut, productivity and purity. In this context, we profit from experimental data and CFD simulations to evaluate the separation performance of the modules when varying the input flowrate, the scale of the module, and the CO2 permeance. These datasets enable us to establish correlations between performance metrics and the dimensionless feed flow (DFfeed). Using simple power functions of DFfeed, we obtain R2 coefficients exceeding 0.99, indicating the accuracy of the correlations built in the present work. In the future, we wish to use DA to understand key transport mechanisms, predict and control module performance, and challenge the universality of these findings by testing various gas separations across different membrane modules beyond our case study.

Pedrozo, Hector A.↗