Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “EFFICIENCY”

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 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Hybrid Thermally Efficient Core (HyTEC) Project Overview

Goal: - The Hybrid Thermally Efficient Core (HyTEC) Project will accelerate the development of the next generation small-core turbofan engine technologies with improvements in efficiency, durability, performance, hybridization, and sustainability in order to meet the next Entry into Service (EIS) single aisle aircraft expected in the 2030’s. Objectives: - Achieve 5-10% fuel burn reduction versus 2020 best in class. - Achieve up to 20% power extraction (4 times current state of the art) at altitude to optimize propulsion system performance and enable hybridization. - Demonstrate the effective and efficient operability of high blend (>80%) Sustainable Aviation Fuels (SAFs) in 2030s EIS combustors.

Tony Nerone↗
NASA NTRS2024

Hybrid Thermally Efficient Core (HyTEC) HyTEC Phase 1 – Advanced Aerodynamics Final Report

The objective of the Hybrid Thermally Efficient Core (HyTEC) – Advanced High Pressure Turbine (HPT) Aerodynamics project is to develop technology for a compact core that contributes to significant fuel burn reductions of 5-10% over current generation technologies. To accomplish this, the HPT is incorporating a range of aerodynamic features and technologies to improve component efficiency and provide favorable systems level trades. In particular, this project explored low solidity airfoils, advanced tip treatments, platform contouring, and advanced ceramic matrix composite (CMC) Stage 2 Nozzle (S2N) airfoils to eliminate the need for post throat cooling in a compact core environment. The maturation of these technology areas is expected to provide a significant improvement in component efficiencies, and consequently reductions in fuel burn, over the current state of the art (SoA). To mature these technologies to Technology Readiness Level (TRL) 4, a test campaign was performed that consisted of four tests at three facilities. TRL 3 testing was performed in the CW22 linear cascade at NASA Glenn for blade and nozzle technologies, TRL 4 nozzle testing was performed at GE Aerospace (GEA) Test Cell A8, and TRL 4 blade testing was performed at the Notre Dame Turbomachinery Laboratory (NDTL) using the Transonic Research Turbine (TRT) rig. Low solidity was successfully demonstrated to a TRL 4 level. Low solidity nozzles showed benefits in line with pre-project expectations, while low solidity blades were shown to have an aerodynamic penalty. Crucially, this program only considered the aerodynamic losses, and systems trades such as reductions in cooling flows are expected to continue to make low solidity blades a net positive. By successfully quantifying the aerodynamic performance in this project, these trades can be conducted to determine where in the engine architecture low solidity blades will contribute positively to system operation. Platform contouring was demonstrated to a TRL 4 level, with performance in line with the lower end of the pre-project expected range. Advanced tip treatments performance levels were indeterminate, showing the expected improvements to flow physics but with a performance level confounded by several rig issues including whirl mode induced variation in tip clearance. The elimination of post-throat cooling on the S2N was successfully demonstrated to provide a performance benefit, however that benefit was approximately half the level that was expected in pre-project predictions. Overall, the technology maturation plan for HyTEC Phase 1 was successful, bringing the suite of technologies to TRL 4.

High pressure turbine↗
NASA NTRSDate not supplied

High Efficiency Megawatt Motor Stator Thermal Performance

Enabling single aisle electric aircraft propulsion requires power dense, megawatt scale, high efficiency electric machines. To that end NASA has been developing the High Efficiency Megawatt Motor (HEMM) 1.46 MW (16kW/kg), 98% efficient electric machine. The success of this effort is highly dependent on the stator’s thermal (cooling) design. The design to date has been based upon computation fluid dynamic and finite element analysis models that have been validated with testing of stator sub sections that replicate expected thermal conditions. However, the test to validate the model can only be so accurate without fully representing the full geometry and components of the stator. A full HEMM stator has been fabricated, potted, and installed in a housing complete with vacuum tube. This apparatus was used to validate the full thermal environment of HEMM and act as a final validation of the stator design before fully fabricating the machine. This paper discusses the modeling and test results from this penultimate HEMM stator build.

electric machine↗
DOE OSTI2020

Quantitative Understanding and Implementation of Screen Printed p+ Poly-Si/Oxide Passivated Contact to Enhance the Efficiency of p-PERC Cells

This paper reports on the modeling, optimization and implementation of p-TOPCon (tunnel oxide passivated contacts) on the rear side of a PERC to enhance its efficiency. Local Al-BSF of a traditional PERC was replaced by p+ polySi/oxide passivated contact composed of ~15Å thick chemically grown tunnel oxide, capped with 120-250nm thick p+ poly-Si layer grown by LPCVD. Process optimization resulted in full area unmetallized saturated current density (Jo) of ~ 5fA/cm2 for planar surface, nearly independent of poly-Si thickness in the range. Metallized J0 showed an increase with decreased poly-Si thickness and was found to be 9.6 and ~25fA/cm2 for 250nm and 120 nm polySi, respectively, with 4.6% direct metal-Si contact fraction, suitable for bifacial cells. A 21.4% efficient baseline PERC cell with local BSF was fabricated and analyzed to extract the rear side saturation current density (J0b’) of 66fA/cm2. Model calculations showed that by replacing this local BSF with 250nm TopCon developed in the study showed some Voc enhancement of 7mV, consistent with the observed Voc increase of 10mV. Model calculations also reveal that a more advanced LBSF PERC with better bulk lifetime and emitter saturation current density can extends its potential gain up to 0.4% in cell efficiency from the integration of p-TOPCon.

14 SOLAR ENERGY↗
DOE OSTI2020

Operation of internal combustion engine with improved fuel efficiency

A process of operating a spark-ignited internal combustion engine (SI-ICE) with improved fuel efficiency and reduced emissions including under steady state and under lean-operating conditions at high overall air to fuel (AFR) ratios. A first supply of high octane hydrocarbon fuel, such as gasoline or natural gas, and a first supply of oxidant are fed to a fuel reformer to produce a gaseous reformate with a reforming efficiency of greater than 75 percent relative to equilibrium. The gaseous reformate is mixed with a second supply of oxidant, after which the resulting reformate blended oxidant is fed with a second supply of high octane hydrocarbon fuel to the SI-ICE for combustion. Steady state fuel efficiency is improved by more than 3 percent, when the reformate comprises from greater than about 1 to less than about 18 percent of the total volume of reformate blended oxidant fed to the engine.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Efficient Distance-based Global Sensitivity Analysis for Terrestrial Ecosystem Modeling

Sensitivity analysis in terrestrial ecosystem modeling is important for understanding controlling processes, guiding model development, and targeting new observations to reduce parameter and prediction uncertainty. Complex and computationally expensive terrestrial ecosystem models (TEM) limit the number of ensemble simulations, requiring sophisticated and efficient methods to analyze sensitivities of multiple model responses to different types of parameter uncertainties. In this study, we propose a distance-based global sensitivity analysis (DGSA) method. DGSA first classifies model response samples into a small set of discrete classes and then calculates the distance between parameter frequency distributions in different classes to measure the parameter sensitivity. The principle is that, if the parameter distribution is the same in each class, then the model response is insensitive to the parameter, while a large difference in the distributions indicates the parameter is influential to the response. Built on this idea, DGSA can be applied to analyze sensitivity of a single and a group of responses to different kinds of parameter uncertainties including continuous, discrete and even stochastic. Besides the main-effect sensitivity from a single parameter, DGSA can also quantify the sensitivity from parameter interactions. Additionally, DGSA is computationally efficient which can use a small number of model evaluations to obtain an accurate and statistically significant result. We applied DGSA to two TEMs, one having eight parameters and three kinds of model responses, and the other having 47 parameters and a long-period response. We demonstrated that DGSA can be used for sensitivity problems with multiple responses and high-dimensional parameters efficiently.

Lu, Dan↗
DOE OSTI2020

Optimal Efficiency and Operational Cost Savings: A Framework for Automated Rooftop PV Placement

Residential energy consumers are charged based on a utility rate structure, such as net metering or feed-in tariff. To lower consumers' electricity bills, expensive batteries are deployed to reduce the electricity fed from the grid during peak hours. However, strategic photovoltaic (PV) panel placement enables the reduction of operational energy cost while considering the spatial feasibility and efficiency for hosting rooftop PV. In this paper, we present a framework to automatically identify the optimal location of rooftop PV panels on residential buildings. Our framework integrates multiple workflows, including energy and environmental simulation, parametric modeling, and optimization to identify the ideal location of PV panels to balance the demand and supply at a building and community scale. These workflows are linked using the Grasshopper plug-in for Rhinoceros CAD software. The framework includes two different workflows, each satisfying a target for optimal PV placement: (a) maximizing PV panel efficiency, where users aim to maximize energy generation, and (b) minimizing operational energy cost, where "best'' panels are selected considering utility rates for operational energy cost. Our framework is demonstrated in a residential community in Fort Collins, Colorado, to generate the optimal PV placement for each of the two aforementioned targets. Results from the two workflows are compared to illustrate the effect of PV location and orientation on solar energy production efficiency and operational energy cost. The developed workflows are introduced as tools within the Grasshopper plug-in to investigate the solar potential of rooftop PV panels while taking into account factors such as contextual shading, utility rate structures, and buildings' energy demand profiles.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Use of novel refractory design and installation techniques for improved energy efficiency in iron and steel and other energy intensive industries

This paper describes the planned work to be performed under a United States Department of Energy funded project to bring together the key players necessary to develop and deploy new technology which could increase the thermal efficiency of the steel industry as well as other energy intensive industries. It is hoped that such improvements in energy efficiency will reduce the overall energy and environmental footprint of domestic industry, as well as provide economic benefit to the individual companies. The described project brings together a vertically integrated collaborative team consisting of the end user (U.S. Steel), material producers/suppliers (Allied Mineral Products and Reno Refractories), raw material suppliers (American Metallurgical Services, Minerals Manufacturing), and research organizations (Oak Ridge National Laboratory, National Energy Technology Laboratory and University of Alabama-Birmingham) with the objective of designing and producing new refractory materials based on novel aggregates, improved particle packing, and engineered surface texture. In addition, the recycling and use of spent refractory materials will be investigated and a novel installation technique will be developed taking advantage of new additive manufacturing technology and existing refractory shotcrete technology. It is hoped that the combination of these new technologies will allow for the improvement of the energy, environmental, and economic efficiency of the steel industry while also reducing the environmental footprint of the refractory and steel industries. Additionally, the developed technology is expected to be applicable to other energy intensive industries such as cement, glass, pulp and paper, and non-ferrous metals processing.

Hemrick, James↗
DOE OSTI2021

Efficient Automated Driving Strategies Leveraging Anticipation and Optimal Control

Automated vehicles and advanced driver assistance systems bring computation, sensing, and communication technologies that exceed human abilities in some ways. For example, automated vehicles may sense a panorama all at once, do not suffer from human impairments and distractions, and could wirelessly communicate precise data with neighboring vehicles. Prototype and commercial deployments have demonstrated the capability to relieve human operators of some driving tasks up to and including fully autonomous taxi rides in some areas. The ultimate impact of this technology’s large-scale market penetration on energy efficiency remains unclear, with potential negative factors like road use by empty vehicles competing with positive ones like automatic eco-driving. Fundamentally enabled by historic and look-ahead data, this dissertation addresses the use of automated driving and driver assistance to optimize vehicle motion for energy efficiency. Facets of this problem include car following, co-optimized acceleration and lane change planning, and collaborative multi-agent guidance. Optimal control, especially model predictive control, is used extensively to improve energy efficiency while maintaining safe and timely driving via constraints. Techniques including chance constraints and mixed integer programming help overcome uncertainty and non-convexity challenges. Extensions of these techniques to tractor trailers on sloping roads are provided by making use of linear parameter-varying models. To approach the wheel-input energy eco-driving problem over generally shaped sloping roads with the computational potential for closed-loop implementation, a linear programming formulation is constructed. Distributed and collaborative techniques that enable connected and automated vehicles to accommodate their neighbors in traffic are also explored and compared to centralized control. Using simulations and vehicle-in-the-loop car following experiments, the proposed algorithms are benchmarked against others that do not make use of look-ahead information.

Dollar, Robert Austin↗
DOE OSTI2022

Model Predictive Control for a Grid-interactive Efficient Thermal Storage-integrated Heat Pump System

Building heating and cooling systems can be used to overcome the mismatch between the intermittent supply of renewable power and the fluctuating demand for electricity. A novel underground thermal energy storage integrated with a dual-source heat pump has been proposed to mitigate the mismatch while meeting the thermal demand of buildings efficiently. Conventional thermostat control with heuristic rules cannot provide intelligent decisions to maximize the thermal efficiency and flexibility of the proposed system. Advanced control strategies like model predictive control (MPC) have provided a new paradigm for grid-interactive efficient building operation with the advancement of computation and sensing. This study developed an MPC for the proposed system to provide grid service for Demand Side Management and minimize the operating cost of building owners. A control-oriented dynamic model of the proposed system has been developed. Given an objective function and proper constraints, an optimization problem is formulated to determine the optimal control strategy of the system. Dynamic Programming is adopted to solve the optimization problem. A rule-based control (RBC) is also developed to achieve similar goals. Short-term simulations are conducted to compare the system performance resulting from the two controls. The simulation results indicate that the MPC performs more intelligently than the RBC in charging thermal energy storage and selecting heat pump sources by taking advantage of the predicted cooling demands of the building and the performance of the integrated system. As a result, the MPC could save energy and reduce operating costs compared with the RBC. A case study shows that, for a 3-day operation, the MPC saves 36.9% energy and reduces 38.5% operating cost compared with the RBC.

Shi, Liang↗
DOE OSTI2022

Carnot Analysis of Heat Pump Drying: Ideal Efficiency and Dry Time

Drying processes are important in appliances and in industry, and clothes drying accounts for approximately 3% of residential primary energy consumption in the US. Globally, heat pump tumble dryers (HPD) are increasing their market share against the ubiquitous electric resistance tumble dryer (ERD). In this work, efficiency and dry time limits are defined for ideal HPDs, for both closed air cycle (unvented) and open air cycle (vented). These limits are compared with the limits for ERD. The traditional Carnot efficiency limit for an ideal heat pump, operating between a hot and a cold thermal reservoir, does not apply directly to clothes dryers. One reason dryers require a novel analysis is the presence of additional degrees of freedom, since the hot and cold temperatures are floating, unfixed by ambient conditions. Furthermore, dryers can operate in a closed or open air cycle, and each requires a different analysis. In the closed (unvented) case, the hot and cold temperatures are coupled to each other; while in the open (vented) case, the hot and cold temperatures are both independent free variables. This paper provides an analysis of the fundamental efficiency limits of ERDs and HPDs, which can inform the design and performance limits of evaporative drying technology.

Gluesenkamp, Kyle↗
DOE OSTI2022

Efficiency and Capacity Performance of a Stirling-Cycle Water-to-Water Heat Pump

The performance of a 10 kW (2.8 ton) heat pump has been modeled in preparation for evaluation in a controlled-atmosphere psychrometric facility. The heat pump uses an electrically driven Stirling engine with nitrogen as a working fluid. The appropriate standards for testing are ANSI/AHRI/ASHRAE ISO Standard 13256-2:1998 (RA 2012), Water-Source Heat Pumps—Testing and Rating for Performance—Part 2: Water-to-Water and Brine-to-Water Heat Pumps. The heating and cooling efficiency and capacity of the device has been modeled at different hot and cold sink temperatures spanning a wide range of possible operating conditions. The heat pump was designed for a seasonal efficiency energy ratio (SEER) of 22. The high efficiency of this product coupled with the use of nitrogen as a working fluid makes it an important tool for the decarbonization of residential, commercial, and industrial HVAC&R applications.

Kowalski, Steve↗
DOE OSTI2022

Quantifying the Value of Grid-Interactive Efficient Buildings through Field Study

Quantifying the annual energy impacts of efficient technologies in commercial buildings has been well established by the building science field. As we move toward enabling grid-interactive efficient buildings (GEB) targeting flexible building operation and carbon reduction, quantification methods to evaluate time-sensitive peak load and emissions impact are much less defined. A number of national laboratories are working to field validate four different GEB software solutions that provide the capability to control multiple building end-use systems in multiple load flexibility modes (i.e., energy efficiency, load shed, load shift, and possible load modulation at the second to sub-second level). To guide the laboratory leads in effective measurement and verification (M&V) practices, two of the laboratories collaborated to define metrics to quantify the impacts of flexible load control on building demand, utility costs, carbon emissions, facility management, and occupant comfort. This paper summarizes the proposed metrics to quantify peak load and emission impacts in the field, decision parameters, approaches to accurately conduct M&V, lessons learned, and outstanding needs and next steps.

Langner, Rois↗
DOE OSTI2022

The Industrial Efficiency and Decarbonization Office

The Industrial Efficiency and Decarbonization Office (IEDO) supports innovation technologies and the adoption of practices to enable the industrial sector to cost-effectively reduce greenhouse gas (GHG) emissions. IEDO and its programs are critical to putting the Nation on a pathway to reduce CO2 emissions by 50% by 2030 when compared to 2005 levels, and to achieve net-zero carbon emissions by 2050. With 30% of primary energy-related emissions attributable to the industrial sector, IEDO builds upon a foundation of energy efficiency as a decarbonization pathway to include process electrification, use of low carbon fuels and feedstocks, and carbon capture to meet industrial emissions reductions targets. IEDO provides planning, management, and direction necessary for a balanced national program of research, development, demonstration, technical assistance, and workforce development to drive energy, materials and production efficiency, and decarbonization across the industrial sector.

Energy-Intensive Industries, Cross-Sector Technolo↗
DOE OSTI2022

Work Smarter, Not Harder: Improving Energy Efficiency and Safety through Smarter Ventilation: Preprint

Ventilation is a key component to maintaining healthy, safe indoor air quality. Especially important in laboratories, ventilation is the first line of defense against airborne hazards produced during research activities. Though a vital component, laboratory ventilation systems are often victim to ineffective operation, posing a risk to the most important asset - the researchers. Furthermore, system inefficiencies can lead to up to 50% wasted energy. To improve both energy efficiency and safety in laboratories, we present the Smart Labs Toolkit - a resource developed by the U.S. Department of Energy Federal Energy Management Program and the International Institute for Sustainable Laboratories that guides laboratory stakeholders through a straight-forward, holistic approach to achieve dynamic, high-performance laboratories. Smart Labs enable safe and efficient world class science to occur in laboratories through high-performance methods. A Smart Labs program employs a combination of physical, administrative, and management techniques to assess, optimize, and manage high performance laboratories. We will focus on a central component of the Smart Labs approach - the Laboratory Ventilation Risk Assessment, a systematic process for identifying risk due to airborne hazards to inform the operation of dynamic ventilation that optimizes safety and efficiency. Case studies of organizations who have successfully implemented Smart Labs ventilation management programs will also be shared. In learning ventilation strategies successful in critical laboratory environments, learn the tools and resources needed to successfully manage energy in any building through smarter, safer ventilation.

buildings↗
DOE OSTI2022

The Chilling Effects of Administrative Burden on Efficiency Policy Uptake: Examining the Case of Federal ESAs

Utilizing policies and programs which incentivize energy efficiency or on-site renewables is difficult. The challenges and costs associated with researching these policies, interacting with their providers, and ensuring regulatory compliance can be collectively referred to as administrative burden. To better understand the impact of administrative burden on energy efficiency policies, we investigated the administrative burden associated with energy sales arrangements (ESA). ESAs are a contracting vehicle related to energy savings performance contracts where an energy services company designs and constructs a renewable energy system at a federal site, transferring ownership of those generating assets to the site after a 20-year term. We conducted a series of in-depth interviews with a variety of relevant ESA stakeholders, including federal project managers, subject matter experts, and energy service companies. We then augmented these interviews with a review of the relevant literature. This research indicated that the current level of administrative burden decreases the adoption of renewable energy through ESAs by the federal government by raising upfront costs, depressing project attempts due to complexity, and introducing delays and challenges in successfully implemented projects. This chilling effect is especially pronounced in new policy vehicles and with inexperienced implementers. Findings from the specific case of ESAs can be generalized to other types of energy policy including efficiency programs. Policy makers decrease the efficacy of initiatives through increased administrative burden, and these effects will be most pronounced in programs with novel design or targeted at unfamiliar audiences.

Newkirk, Alex↗
DOE OSTI2022

Climate Impact on CO2 Capture Efficiency and Levelized Cost of Liquid solvent-based DAC (Direct Air Capture) System

The transition towards net-zero emission poses economic, technical, and political challenges for the commercial-scale deployment of CO2 removal technologies by 2050. The opportunities for large-scale deployment will largely depend on the distinctive conditions found in the different locations of the world such as energy cost, carbon intensity of energy source, construction, transportation, and weather conditions. In this work, we focus on one of the promising negative emission technology, DAC (Direct Air Capture), and its response to different weather conditions. This work presents two potential operation scenarios: (i) natural gas standalone, (ii) grid electricity connected DAC plant. For the first time, we investigated the influence of temperature and RH (relative humidity) of the air on liquid-based DAC system and its response to carbon capture efficiency and levelized cost of carbon capture with operational sensitivity analysis. It is observed that the overall energy demand decreases from 11.1 to 8.3 GJ/ton-CO2 as the CO2 capture rate increases from 40 to 85%. We observed that a CO2 capture rate of 75% is only possible above 17°C even at 90% RH and this drops tremendously at lower temperatures. It is also observed that water evaporation in the air contactor is highest at dry and low RH as expected. The sensitivity analysis showed that weather conditions are insensitive to CO2 capture efficiency for the liquid-solvent based DAC plant for both scenarios. In addition, higher CO2 capture efficiency is achievable from lower upstream methane emissions and carbon intensity of grid electricity (for grid-connected scenario). Lastly, the levelized cost of natural gas standalone scenario varies from 239.7 to 408.8 $/t-CO2 is sensitive to temperature conditions more than relative humidity and compared to electricity grid-connected scenario, from 265.3 to 440.1 $/t-CO2.

An, Keju↗
DOE OSTI2023

Efficient Network Partitioning: Application for Decentralized State Estimation in Power Distribution Grids: Preprint

Increase in the proliferation of DERs requires real-time situational awareness for efficient grid operations. State estimation plays an important role for real time control and management of the power grid. As the sensing infrastructure grows, aggregating and handling high volumes of data at a centralized location is extremely difficult. To address this challenge, this paper first proposes a novel and efficient hierarchical spectral clustering-based network partition algorithm followed by a decentralized compressive sensing (DCS) based state estimation. The applicability of the proposed network partitioning algorithm is tested on IEEE-123 bus, IEEE-8500 node, and a 6204-node distribution network. The results shows that the proposed approach efficiently divides the network into multiple sub-networks with the minimum edge connections among the neighbors. Then, we perform DCS-based state estimation on the 6204-node distribution network after dividing the network into 18 optimal partitions. Simulation results show that DCS-based state estimation recovers the system states with high accuracy and low complexity.

ADMM↗