Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “consumption potential”

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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A deep decarbonization framework for the United States economy – a sector, sub-sector, and end-use based approach

Achieving the United States' target of net-zero greenhouse gas emissions by 2050 will require technological transformations and energy sector mitigation. To understand the role of dynamically evolving technologies, identify synergies and dissonance and the effect of allocating limited low-carbon biomass resources in decarbonizing the U.S. economy, we developed the Decarbonization Scenario Analysis Model. A Life Cycle Assessment based approach is implemented considering the U.S. economy as the functional unit, to estimate greenhouse gas mitigation potential for projected energy demand based on several sector-level and cross-sectoral decarbonization pathways. Direct and supply-chain emissions are accounted, resulting from changes in patterns of energy generation and consumption, technology breakthroughs, and reductions in fugitive emissions over time at the granularity of economic sectors, sub-sectors, and end-use. Decarbonization strategies are implemented over a reference case developed using Energy Information Administration (EIA AEO) projection of economic activities for 2020–2050. Based on the considered scenarios, 80–90% economy-wide decarbonization relative to the 2020 reference case is projected. Electrification, low-carbon fuels, and reduction of fugitive emissions play the most significant role to decarbonization. The majority of the remaining emissions are accounted to the supply-chain and end-use emissions from natural gas and diesel fossil-based fuels in heavy duty transportation and heavy industries, highlighting the need for developing low-carbon and carbon-negative alternatives to mitigate those fossil-based carbon emissions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Spatial Impacts of Electric Vehicle Charging on Power Grid Stability: A Downtown Atlanta Case Study

The rapid increase in electric vehicle (EV) charging demand poses a potential risk to power grid stability, particularly as the spatial distribution of this demand remains underexplored. Existing research often focuses on technical optimization models while overlooking the geographic and human dynamics that affect energy consumption. This study addresses this gap by incorporating mobility data to estimate both building energy use and EV charging demand while also considering geographic factors for a better understanding of grid load. Using agent-based simulations and the Open-Source Distribution System Simulator, the study evaluates the effect of various EV penetration scenarios on grid voltage and unbalance. The results show that, although voltage remains within acceptable limits at lower EV penetration rates, significant voltage drop and unbalance occur as EV penetration exceeds 40%, particularly in residential areas with high charging demand. This study offers a framework for integrating spatial analysis and mobility data in power network simulations, providing insights for future EV infrastructure planning.

Pan, Melrose [ORNL] (ORCID:000000031627448X)↗
DOE OSTI2020

2019 Hyperion 5313A and 5119A Infrasound Sensor Type Approval Evaluation

Sandia National Laboratories has tested and evaluated two variations of a new model of infrasound sensor, the Hyperion 5313A and 5119A. The purpose of this infrasound sensor evaluation is to measure the performance characteristics in such areas as power consumption, sensitivity, full scale, self-noise, dynamic range, response, passband, sensitivity variation due to changes in static pressure and temperature, and sensitivity to vertical acceleration. The Hyperion infrasound sensors are being evaluated for potential use in the International Monitoring System (IMS) of the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Federal Aviation Administration Vertiport Electrical Infrastructure Study

In this detailed analysis, the authors assess the charging infrastructure needed for the deployment of advanced air mobility involving electrified vertical take-off and landing technologies. The report covers four research areas: (1) Identifying charging infrastructure requirements for existing facilities based on flight operational parameters, potential use cases, charging strategy, and other constraints. (2) Assessing sites on power availability to meet charging demand, the impact on grid infrastructure, potential hazards, and cybersecurity needs, and using technoeconomic analysis to identify opportunities for onsite distributed energy resources, primarily solar photovoltaics and battery energy storage systems. (3) Calculating greenhouse gas emission based on total energy consumption attributable to each site. (4) Analyzing the job and economic development impact for sites adopting new infrastructure.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Design of a Meso-Scale Test of a Fracture Thermal Energy Storage (FTES) System

This paper will present the characterization, scaling, and design of an intermediate-scale field test of a fracture thermal energy storage system (FTES). Seasonal storage of thermal energy has the potential to both significantly reduce the total energy requirements for heating and cooling of buildings, but also allow for the flexibility to store thermal energy from intermittent sources. With approximately half of global energy consumption currently being used for heating and cooling, this represents an important path to reducing greenhouse gas (GHG) emissions. The concept of FTES is to drill two or more wells into a low permeability formation, generally at a depth of less than a few hundred meters, and then generate hydraulic fractures to create flow paths for water to circulate between the wells. Hot or cold thermal energy can then be stored in the surrounding rock mass by circulating hot or cold water through the fractures, which will heat or cool the rock mass. To recover the stored energy, ambient temperature water can be then circulated through the fractures, which will then be heated or cooled by the rock mass. Fractures inherently have a very large ratio of surface area to volume. This allows for very high heat fluxes to and from the rock mass to be achieved despite the relatively low thermal conductivity of most geologic formations. Because large fractures can be made with low-cost equipment and with only inexpensive and environmentally safe materials such as water and sand, the cost to construct even large FTES systems is expected to be quite low. This paper will present what the performance requirements, size, and operating conditions of a full-scale system to operate a commercial building. The paper will describe how these full-scale system characteristics will be used as a design basis for an intermediate-scale FTES test to be conducted at the Sanford Underground Research Facility (SURF) in Lead, SD.

Burghardt, Jeffrey A.↗
DOE OSTI2024

Equitable Energy Metrics for Integration into Building Performance Standard Tracking Platforms: Preprint

Building Performance Standards (BPS) are being adopted globally and in the United States of America, where 14 different states and jurisdictions have a policy in place and many others are under development (Department of Energy (DOE) 2023). Accurate and equitable data sources are essential to make informed decisions about focusing investment on upgrading buildings to meet jurisdictional goals. There have been multiple new tools developed related to Energy Equity and Environmental Justice (EEEJ) and the resulting datasets need to be integrated into large building port-folios for quick access and better scalability. Integrating EEEJ data in a user-friendly format can help decision makers more quickly assess impacts and analyze the multitude of potentially significant metrics for which there is not yet consensus. In the U.S. and Canada, many BPS ordinances rely primarily on ENERGY STAR Portfolio Manager (ESPM) to capture building characteristics and energy and water consumption data. These datasets can then be imported into city-specific building tracking tools like the Standard Energy Efficiency Data Platform (SEED). Crucially, BPS decision makers require an efficient means of identifying buildings in priority communities to effectively allocate resources and funding. This process must integrate seamlessly with existing jurisdictional toolsets for optimal utility. This paper will demonstrate, for the case of Washington D.C.'s (the District) data, a workflow that provides actionable data for building upgrade investment prioritization in disadvantaged communities.

BPS↗
DOE OSTI2023

ComStock Reference Documentation (V.1)

The commercial building sector stock model, or ComStock™, is a highly granular, bottom-up model that uses multiple data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual sub-hourly energy consumption of the commercial building stock across the United States. ComStock asks and answers two questions: how is energy used in the U.S. building stock and what are the impact of energy saving technologies. Specifically, ComStock identifies where energy is being consumed geographically, in what building types and end uses, and at what times of day. Simultaneously, it identifies the impact of efficiency measures: how much energy do efficiency measures save; where, or in what use cases do measures save energy; when, or at what time of day do savings occur; and which building stock segments have the biggest savings potential. This document contains the methodology and assumptions behind ComStock and serves as a guide to its use.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Exploring the cost and emissions impacts, feasibility and scalability of battery electric ships

The United States’ greenhouse gas (GHG) emissions reduction goals, along with targets set by the International Maritime Organization, create an opportunity for battery electric shipping. In this study, we model life-cycle costs and GHG emissions from shipping electrification, leveraging ship activity datasets from across the United States in 2021. We estimate that retrofitting 6,323 domestic ships under 1,000 gross tonnage to battery electric vessels would reduce US domestic shipping GHG emissions by up to 73% by 2035 from 2022 levels. By 2035, electrifying up to 85% of these ships could become cost effective versus internal combustion engine ships if they cover 99% of annual trips and charge from a deeply decarbonized grid. We find that charging demands from electrifying these ships could be concentrated at just 20 of 150 major ports nationwide. This study demonstrates that retrofitting to battery electric vessels has economic potential and could significantly accelerate GHG emission reductions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Achieving Integrated Daylighting and Electric Lighting Systems: Current State of the Art and Needed Research

This paper presents the results of a multi-disciplinary scoping study, the goals of which were to see the seamless integration and application of light in buildings, regardless of source, that is purposely modulated to illuminate surfaces and designed in a way that is comfortable, healthy, pleasing, cost effective, and energy efficient. The scoping study was performed in order to set the stage for transforming the design and realization of lighting systems integration (daylight and electric). This, in turn, will support achieving the the U.S. Department of Energy’s (DOE) Building Technologies Office (BTO) long-term energy savings goals. Holistic lighting systems of the future should include components that are adaptable to change, resilient to disruption, and robust. The system of codes, standards, guidelines, and contracts employed to design and implement lighting systems should be structured to help them to flourish, rather than being barriers to realization. Finally, the research thrusts and mechanisms should be engaged with these goals in mind. While integrated lighting systems may reduce lighting energy use in buildings, a broader web of non-energy impacts affecting occupant’s overall health, comfort, and satisfaction may also guide technology investment goals when the entire lighting systems lifecycle is considered. Daylighting systems are separated from electric lighting systems, and both are characteristically detached from other systems such as safety, security, communications, and information systems. Being disconnected from the inputs and outputs of other building systems precludes the ability to acquire and utilize information about occupation, status of systems, and interior and exterior environmental conditions. The outcome of this separation is that the standard building is not fulfilling the potential for creating dynamic and holistic lighting for building occupants.

Davis, Robert G.↗
DOE OSTI2020

Considerations for Medium-Term Load Forecasting in Morocco

There are many factors that determine how demand for electricity may change over time. Medium-term load forecasting is a subset of load forecasting that focuses on the next year. This presentation summarizes analysis performed by NREL on medium-term load forecasting performed for the Moroccan energy system. This analysis includes hourly regressions and load clustering. This work also describes potential next steps that can be implemented by ONEE to improve this medium-term load forecasting.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Impacts of Thawing Permafrost on Residential Infrastructure: Results and Resources

Permafrost underlies approximately 20% of the landmass in the Northern Hemisphere. Inevitably human infrastructure has been and will be built on permafrost; however, due to climate change, the permafrost in many regions has begun to thaw. Using past reports and surveys as guidance, a survey was conducted to track the effects of permafrost thaw on housing infrastructure in the community of Point Lay, Alaska. The Cold Climate Housing Research Center, Inc. and the National Renewable Energy Lab conducted a literature review and interviews to document community issues from thawing permafrost and identify potential mitigation strategies for existing and new infrastructure. Researchers also identified strategies for individual homeowners to inspect their foundations for current issues or anticipate future ones. This poster will cover the results from the survey on the effects of permafrost thawing to Point Lay and include permafrost basics, common concerns from thawing permafrost, steps to identify permafrost sites and visible signs of permafrost degradation, and potential mitigation strategies that may be beneficial to Alaskans and increase resilience in the Arctic.

Alaska↗
DOE OSTI2023

Machine Learning for Advanced Building Construction

High-efficiency retrofits can play a key role in reducing carbon emissions associated with buildings if processes can be scaled-up to reduce cost, time, and disruption. Here we demonstrate an artificial intelligence/computer vision (AI/CV)-enabled framework for converting exterior build scans and dimensional data directly into manufacturing and installation specifications for overclad panels. In our workflow point clouds associated with LiDAR-scanned buildings are segmented into a facade feature space, vectorized features are extracted using an iterative random-sampling consensus algorithm, and from this representation an optimal panel design plan satisfying manufacturing constraints is generated. This system and the corresponding construction process is demonstrated on a test facade structure constructed at the National Renewable Energy Laboratory (NREL). We also include a brief summary of a techno-economic study designed to estimate the potential energy and cost impact of this new system.

build scans↗
DOE OSTI2024

Data-driven Quasi-static Surrogate Models for Nuclear-powered Integrated Energy Systems

The integration of nuclear power into energy systems presents a promising avenue to address the growing global energy demands while minimizing greenhouse gas emissions. In this paper, we introduce a data-driven quasi-static surrogate model for nuclear-powered Integrated Energy Systems (IES) that comprises various components, including a small modular reactor (SMR), steam manifold, balance of plant (BOP), high-temperature steam electrolysis (HTSE), and district heating (DH) system. Traditional physics-based models for these components often entail significant computational resource and time consumption, necessitating the development of efficient surrogate models. The development of a complete surrogate model for the IES involves the creation of individual surrogate models for each component, leveraging machine learning techniques and simulated data. These isolated surrogate models are subsequently integrated, enabling a holistic view of the IES and reducing the computational burden associated with detailed physics-based simulations. This paper outlines the development process, validation, and the performance evaluation of the surrogate models. The exceptional performance, with low root-mean-squared errors and R-squared scores of at least 99.8% across all individual surrogate models, underscores their accuracy and practical applicability. These results demonstrate the potential of these models to expedite the analysis of nuclear-powered IES, offering insights that can shape future research and development efforts.

08 HYDROGEN↗
DOE OSTI2024

Performance Restoration of Iron Electrodes by Polarity Reversal after Long-Term Surface Fouling in Wastewater Electrocoagulation

Iron electrocoagulation (Fe-EC) performance often declines with time, producing lower contaminant removal efficiencies and higher energy requirements due to formation of a fouling layer on the electrodes. Here, we investigate the formation of the fouling layer and the effectiveness of polarity reversal to restore the Fe-EC performance. A thin, porous iron oxide layer initially forms on the anode, thickening into a dense, over 150-μm thick crystalline layer after extended operation. This fouling layer restricts dissolution and diffusion of Fe ions into the bulk solution, thus increasing the anode potential required to maintain a desired electrical current and decreasing Faradaic efficiency. Polarity reversal applied when performance decline is observed effectively removes the fouling layer, thereby restoring Faradaic and contaminant removal efficiencies and decreasing energy consumption. Our findings suggest that gas generation at the cathode surface after polarity reversal causes removal of the fouling layer. This study enhances the current understanding of fouling-layer formation in Fe-EC and offers a practical approach, involving polarity reversal, to maintain electrode reactivity and optimal Fe-EC performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A domain wall-magnetic tunnel junction artificial synapse with notched geometry for accurate and efficient training of deep neural networks

Inspired by the parallelism and efficiency of the brain, several candidates for artificial synapse devices have been developed for neuromorphic computing, yet a nonlinear and asymmetric synaptic response curve precludes their use for backpropagation, the foundation of modern supervised learning. Spintronic devices—which benefit from high endurance, low power consumption, low latency, and CMOS compatibility—are a promising technology for memory, and domain-wall magnetic tunnel junction (DW-MTJ) devices have been shown to implement synaptic functions such as long-term potentiation and spike-timing dependent plasticity. In this work, we propose a notched DW-MTJ synapse as a candidate for supervised learning. Using micromagnetic simulations at room temperature, we show that notched synapses ensure the non-volatility of the synaptic weight and allow for highly linear, symmetric, and reproducible weight updates using either spin transfer torque (STT) or spin–orbit torque (SOT) mechanisms of DW propagation. We use lookup tables constructed from micromagnetics simulations to model the training of neural networks built with DW-MTJ synapses on both the MNIST and Fashion-MNIST image classification tasks. Accounting for thermal noise and realistic process variations, the DW-MTJ devices achieve classification accuracy close to ideal floating-point updates using both STT and SOT devices at room temperature and at 400 K. Our work establishes the basis for a magnetic artificial synapse that can eventually lead to hardware neural networks with fully spintronic matrix operations implementing machine learning.

42 ENGINEERING↗
DOE OSTI2024

Platform for Remote Deployment and Training for Enhanced Building Operation Practices (Building Re-Tuning and On-going Commissioning)

While a building’s energy usage is driven largely by its design and use, building operator behavior has a strong influence on its energy consumption. This project developed and piloted a specific, data-driven coaching methodology to help operators understand how they can adjust operations and/or affect no/low-cost repairs or upgrades to their specific building HVAC systems to reduce energy consumption. Named BuildingCoach, the operational optimization method used is based on the Building Re-tuning approach developed by the Pacific Northwest National Laboratory. A building operations analytics market has matured over the past decade, though its potential to affect energy-saving changes has not been fully realized. Training operators to understand the methods for operational optimization with the explicit approach of using building-system performance data is hypothesized to create a more effective, longer lasting result in building energy efficiency, and this strategy is the fundamental premise of this project. With the support of an Industry Advisory Board, the project succeeded in developing materials and recruiting for and delivering three pilot cohorts. Deliverables included twenty-two self-paced training modules (accessed via a Learning Management System) and a web-based platform that includes access to real-time building system data and a repository for building system documentation. The project set out to have 100 participants from 50 buildings in three pilot cohorts. In the end, there were 28 participants from 17 buildings, i.e., a significant shortfall. The first two pilot cohorts had only two buildings in each, and this was partially due to difficulties in deploying the Building Operator Coaching Solution (“the BOCS”), which is technology that extracts the data from the controls network and presents it as prescribed for coaching. In the third cohort, the project team deployed the BOCS successfully to 13 buildings, the methodology was piloted as intended, and numerous opportunities for optimization were identified. The BuildingCoach business plan charts a path to an economically sustainable effort. However, even with a licensing model captured in the final version of the business plan, the scalability is still limited to keeping less than 1,000 buildings affected by 2033. Even so, there are unexplored paths to greater scalability that are being considered. CUNY BPL is working to perpetuate and grow the use of BuildingCoach. As of this writing, about twenty buildings have either been connected or will be connected with operators coached / to be coached in the NYC municipal portfolio, twelve buildings across four campuses in NY State will use BuildingCoach, a NY upstate county wishes for six or seven buildings to participate with the support of funding from NYSERDA, and others have also expressed interest. In the decades to come, there will be an increasing percentage of large and mid-sized buildings that incorporate automated system optimization (ASO), and the building operators’ role will shift to spend more time on maintenance and monitoring. Meanwhile, programs such as BuildingCoach will play a critical role in optimizing operations. And, regardless of the emergence of ASO, operators will still need to understand how their systems operate so that they can monitor them properly. Within that context, BuildingCoach is an important step towards operators’ understanding of efficient building system operations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

A high efficiency rooftop air conditioning system using multi-speed compressors

This study delineates a meticulous exploration of technologies to enhance the energy efficiency of rooftop air conditioning units, employing the DOE/ORNL heat pump design model for comprehensive engineering design and optimization. A baseline rooftop air conditioning unit, featuring a 13 ton (45.7 kW) cooling capacity and a 17.9 integrated energy efficiency ratio, served as the point of departure for substantive efficiency enhancements. Key modifications included the consolidation of two refrigerant circuits into one, integrating three parallel 2-stage (dual-speed) compressors, fan replacements with high-efficiency substitutes. Notably, a lower global warming potential refrigerant, R452B, was evaluated as a substitute for R-410A, demonstrating better performance in the lab prototype. Further, the achieved measured integrated energy efficiency ratio of 21.4 in the lab prototype surpassed the baseline integrated energy efficiency ratio. Comparative evaluations between R410A and R452B indicated heightened efficiency with the latter, showcasing a lab-demonstrated integrated energy efficiency ratio of 22.4 at the rated capacity of 13.8 ton (48.5 kW) and 23.9 integrated energy efficiency ratio at the rated capacity of 10 ton (35.2 kW). This research underscores the successful development of a rigorous, energy efficient rooftop air conditioning unit prototype with noteworthy environmental and economic implications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗