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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Dislocation model of nucleation and development of slip bands and their effect on service life of structural materials subject to cyclic loading

Most of the destructions of machine parts are of fatigue character. Under cyclic loading, the surface layer, in which hardening–softening processes rapidly occur, is formed almost at once after its beginning. The interaction of plastic-deformation traces with each other and with other structural elements, such as grains, results in the formation of a characteristic microstructure of the machine-part surface subject to cyclic loadings. The character of accumulation of slip bands and their shape (narrow, wide, twisting, and broken) depends on the conditions under which (under what factors) the cyclic loading occurs. The fatigue-resistance index expressed in terms of the slope of left portion of the fatigue curve linearized in logarithmic coordinates also depends on the set of relevant factors. The dependence of the surface damageability on the fatigue resistance index makes it possible to implement the method of predicting the fatigue curve by the description of the factors acting on a detail or construction. The position of the inflection point on the curve in the highcycle fatigue region (the endurance limit and the number of loading cycles, the ordinate and abscissa of the inflection point on the fatigue curve, respectively) also depends on the set of relevant factors. In combination with the previously obtained value of the slope of the left portion of the curve in the high-cycle fatigue region, this makes it possible to construct an a priori fatigue curve, thus reducing the scope of required fatigue tests and, hence, high expenses because of their long duration and high cost. The scope of tests upon using the developed method of prediction may be reduced to a minimum of one or two samples at the predicted level of the endurance limit.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Cross-Categorical Transfer Learning based Composite Load Protection Modeling

Protection equipment is used to prevent damage to induction motor loads by isolating them from power systems in the event of severe faults. Modeling the response of induction motor loads and their protection is vital for power system planning and operation, especially in understanding system's dynamic performance and stability after a fault occurs. Induction motors are usually equipped with several types of protection with different operation mechanisms, making it challenging to develop adequate yet not overly complex protection models and determine their parameters for aggregate induction motor models. This paper proposes a novel cross-categorical transfer learning based framework to determine protection model parameters for aggregate induction motor loads in commercial buildings. Introducing a mathematical abstraction, the task of determining a suitable set of parameters for the protection model in composite load models is formulated as a combination of feature extraction using transferable layers, followed by affine operations through non-transferable layers applied on the previous extracted features. Numerical results are provided to illustrate the application of the framework.

transfer learning, Stacked Autoencoder, Composite ↗
DOE OSTI2016

Safety envelope for load tolerance of structural element design based on multi-stage testing

Structural elements, such as stiffened panels and lap joints, are basic components of aircraft structures. For aircraft structural design, designers select predesigned elements satisfying the design load requirement based on their load-carrying capabilities. Therefore, estimation of safety envelope of structural elements for load tolerances would be a good investment for design purpose. In this article, a method of estimating safety envelope is presented using probabilistic classification, which can estimate a specific level of failure probability under both aleatory and epistemic uncertainties. An important contribution of this article is that the calculation uncertainty is reflected in building a safety envelope using Gaussian process, and the effect of element test data on reducing the calculation uncertainty is incorporated by updating the Gaussian process model with the element test data. It is shown that even one element test can significantly reduce the calculation uncertainty due to lacking knowledge of actual physics, so that conservativeness in a safety envelope is significantly reduced. The proposed approach was demonstrated with a cantilever beam example, which represents a structural element. The example shows that calculation uncertainty provides about 93% conservativeness against the uncertainty due to a few element tests. As a result, it is shown that even a single element test can increase the load tolerance modeled with the safety envelope by 20%.

42 ENGINEERING↗
DOE OSTI2022

Building Load Control Using Distributionally Robust Chance-Constrained Programs with Right-Hand Side Uncertainty and the Risk-Adjustable Variants

Aggregation of heating, ventilation, and air conditioning (HVAC) loads can provide reserves to absorb volatile renewable energy, especially solar photo-voltaic (PV) generation. In this paper, we decide HVAC control schedules under uncertain PV generation, using a distributionally robust chance-constrained (DRCC) building load control model under two typical ambiguity sets: the moment-based and Wasserstein ambiguity sets. We derive mixed integer linear programming (MILP) reformulations for DRCC problems under both sets. Especially, for the Wasserstein ambiguity set, we use the right-hand side (RHS) uncertainty to derive a more compact MILP reformulation than the commonly known MILP reformulations with big-M constants. All the results also apply to general individual chance constraints with RHS uncertainty. Furthermore, we propose an adjustable chance-constrained variant to achieve tradeoff between the operational risk and costs. We derive MILP reformulations under the Wasserstein ambiguity set and second-order conic programming (SOCP) reformulations under the moment-based set. Using real-world data, we conduct computational studies to demonstrate the efficiency of the solution approaches and the effectiveness of the solutions. Summary of Contribution: The problem studied in this paper is motivated by a building load control problem that uses the aggregation of heating, ventilation, and air conditioning (HVAC) loads as flexible reserves to absorb uncertain solar photovoltaic (PV) generation. The problem is formulated as distributionally robust chance-constrained (DRCC) programs with right-hand side (RHS) uncertainty. In addition, we propose a risk-adjustable variant of the DRCC programs, where the risk level, instead of being predetermined, is treated as a decision variable. The paper aims to provide tractable reformulations and solution algorithms for both the (general) DRCC and the (general) adjustable DRCC models with RHS uncertainty.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Review of Residential Low-Load HVAC Systems

In support of the U.S. Department of Energy’s (DOE’s) Building America Program, Pacific Northwest National Laboratory (PNNL) conducted an investigation to inventory commercially available HVAC technologies that are being installed in low-load homes. The first step in this investigation was to conduct a review of published literature to identify low-load HVAC technologies available in the United States and abroad, and document the findings of existing case studies that have evaluated the performance of the identified technologies. This report presents the findings of the literature review, identifies gaps in the literature or technical understanding that must be addressed before low-load HVAC technologies can be fully evaluated, and introduces PNNL’s planned research and analysis for this project to address identified gaps and potential future work on residential low-load HVAC systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Field Trial of a Low-Cost, Distributed Plug Load Monitoring System

Researchers have struggled to inventory and characterize the energy use profiles of the ever-growing category of so-called miscellaneous electric loads (MELs) because plug-load monitoring is cost-prohibitive to the researcher and intrusive to the homeowner. However, these data represent a crucial missing link to our understanding of how homes use energy, and we cannot control what we do not understand. Detailed energy use profiles would enable the nascent automated home energy management (AHEM) industry to develop effective control algorithms that target consumer electronics and other plug loads. If utility and other efficiency programs are to incent AHEM devices, they need large-scale datasets that provide statistically meaningful justification of their investments by quantifying the aggregate energy savings achievable. To address this need, we have investigated a variety of plug-load measuring devices available commercially and tested them in the laboratory to identify the most promising candidates for field applications. The scope of this report centers around the lessons learned from a field validation of one proof-of-concept system, called Smartenit (formerly SimpleHomeNet). The system was evaluated based on the rate of successful data queries, reliability over a period of days to weeks, and accuracy. This system offers good overall performance when deployed with up to ten end nodes in a residential environment, although deployment with more nodes and in a commercial environment is much less robust. We conclude that the current system is useful in selected field research projects, with the recommendation that system behavior is observed over time.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Miscellaneous and Electronic Loads Energy Efficiency Opportunities for Commercial Buildings: A Collaborative Study by the United States and India

This report documents the technical evaluation of a collaborative research, development, and demonstration (RD&D) project that aims to address energy efficiency of Miscellaneous and Electronic Loads (MELs) (referred to as plug loads interchangeably in this report) using load monitoring and control devices. The goal s of this project are to identify and provide energy efficiency and building technologies to exemplary information technology (IT) office buildings, and to assist in transforming markets via technical assistance and engagement of Indian and U.S. stakeholders. This report describes the results of technology evaluation and United States – India collaboration between the Lawrence Berkeley National Laboratory (LBNL), Infosys Technologies Limited (India), and Smartenit, Inc. (U.S.) to address plug - load efficiency. The conclusions and recommendations focus on the larger benefits of such technologies and their impacts on both U.S. and Indian stakeholders.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Field Trial of a Low-Cost, Distributed Plug Load Monitoring System

Researchers have struggled to inventory and characterize the energy use profiles of the ever-growing category of so-called miscellaneous electric loads (MELs) because plug-load monitoring is cost-prohibitive to the researcher and intrusive to the homeowner. However, these data represent a crucial missing link to understanding how homes use energy. Detailed energy use profiles would enable the nascent automated home energy management (AHEM) industry to develop effective control algorithms that target consumer electronics and other plug loads. If utility and other efficiency programs are to incent AHEM devices, they need large-scale datasets that provide statistically meaningful justification of their investments by quantifying the aggregate energy savings achievable. To address this need, NREL researchers investigated a variety of plug-load measuring devices available commercially and tested them in the laboratory to identify the most promising candidates for field applications. This report centers around the lessons learned from a field validation of one proof-of-concept system, called Smartenit (formerly SimpleHomeNet). The system was evaluated based on the rate of successful data queries, reliability over a period of days to weeks, and accuracy. This system offers good overall performance when deployed with up to 10 end nodes in a residential environment, although deployment with more nodes and in a commercial environment is much less robust. NREL concludes that the current system is useful in selected field research projects, with the recommendation that system behavior is observed over time.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Implementation of Substructure Flexibility and Member-Level Load Capabilities for Floating Offshore Wind Turbines in OpenFAST

OpenFAST is an open-source, physics-based engineering tool applicable to the load analysis of land-based and offshore wind turbines, including floating offshore wind turbines. The substructure for a floating wind turbine has historically been modeled in OpenFAST as a rigid body with hydrodynamic loads lumped at a point, which enabled the tool to predict the global response of the floating substructure but not the structural loads within its individual members. This limitation is an impediment to designing floating substructures - especially newer designs that are more streamlined, flexible, and cost-effective. This paper presents the development of new functionality in OpenFAST to model floating substructure flexibility and member-level loads, as well as the concepts and mathematical background needed to understand and apply it correctly.

17 WIND ENERGY↗
DOE OSTI2021

Up-Tower Investigation of Main Bearing Cage Slip and Loads

This paper described the operational conditions of an SRB in the main bearing position of a three-point mount wind turbine drivetrain. A commercial wind turbine was instrumented to measure load characteristics on the outer ring of the bearing, which were used to examine the roller load characteristics qualitatively and the cage slip quantitatively in a range of operational states. Further, a simple analytic model estimated the bearing loads and was used as input conditions to a three-dimensional finite element model. The finite element roller load results were compared to the measurements and contact stresses were also described.

17 WIND ENERGY↗
DOE OSTI2025

ComStock Measure Documentation: Ideal Thermal Air Loads

This study provides hypothetical thermal heating and cooling loads for ComStock models representing the U.S. commercial building stock. This measure scenario removes all HVAC models from the baseline ComStock building model and instead uses "ideal air" to meet loads. "Ideal air" can be thought of as an HVAC unit that mixes air at the zone exhaust condition with the specified amount of outdoor air, and then adds or removes heat and moisture at 100% efficiency to produce a supply air stream at the specified conditions. The resulting ideal thermal loads are represented under the "district" fuel type for both heating and cooling and can be found in both annual and timeseries results in the ComStock public dataset. This measure scenario does not represent any real technology or improvement, but rather, serves as a resource for thermal heating and cooling loads for buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Large Load Management and Grid Planning

This presentation will cover these topics, followed by a discussion and Q&A: Grid impacts of load growth of the current bulk power system, a review of recent trends and events related to large load integration, what might these new large loads look like, what are options for reducing costs and timelines of integration, and working toward a framework for identifying hot spots for efficiently interconnecting large loads.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Advanced Load Forecasting

This presentation presents information about electric utility load forecasting in the U.S. It provides an overview of load forecasting and describes the current state of the industry. Current load forecasting challenges, opportunities, and interests are presented, including feedback from a 2024 workshop on Integrated Distribution System Planning. The presentation also describes a variety of NREL tools and capabilities that support utility load forecasting efforts. This was presented as part of NREL's Utility Planning Resources for Energy Transition Webinar Series.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

ComStock Measure Documentation: Lighting Control for Load Shedding

This report describes the modeling methodology for a single end-use savings shape measure - lighting control for load shedding - and briefly introduces key results. The lighting control for load shedding measure applies lighting dimming control to reduce the lighting load during the building's electricity peak window every weekday. The measure takes daily peak load schedule inputs generated by the method "Dispatch Schedule Generation" described in the "Supplemental Documentation: Dispatch Schedule Generation for Demand Flexibility Measures" to determine the start and end times of the predicted peak window, and then adjusts the lighting dimming level by a percentage reduction from the original schedules during the peak window to reduce the peak demand. The measure is applicable to (large, medium and small) offices, warehouses, and primary and secondary schools, which correspond to approximately 68% of the stock floor area of commercial buildings in ComStock analysis. The measure demonstrates 2%-7% daily peak demand reduction performance for applicable buildings, and 0.43% total site energy savings (0 trillion British thermal units [TBtu]) for the U.S. commercial building stock modeled in ComStock.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Quantifying the Effect of Economic Development Zones on Electrical Load Growth in Kentucky [Slides]

The Kentucky Energy and Environment Cabinet has recently undertaken a comprehensive effort to map and catalog potential economic development sites across the state. The purpose of this technical assistance is to quantify the potential impact of developing designated sites on Kentucky's electricity load growth, providing insights at both state and county level considering the next 10 years. This analysis should explicitly incorporate and address key project uncertainties by developing various load growth scenarios that account for development scale, site specificity, and sector variability. The need for a site-specific analysis comes from the understanding that conventional econometric (top-down) load forecasting models cannot sufficiently isolate or predict the discrete load increases resulting from the development of these unique and targeted economic sites.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Digital Assurance for Grid Reliability in the Era of Large Load Growth

The rapid expansion of large electric loads is reshaping the operational and regulatory landscape of the U.S. electric grid. These facilities are reaching new scales of expansion, now exceeding a gigawatt per site, and their highly sensitive, digitally driven behaviors introduce new reliability risks. Recent grid events, including large load losses following routine transmission disturbances, highlight the consequences of limited ride-through capability, inconsistent protection settings, inadequate modeling, and lack of behind-the-meter visibility. Parallels to earlier integration challenges of new grid technologies suggest that the grid’s existing processes, standards, and interconnection frameworks are no longer adequate for emerging large loads. This brief synthesizes lessons from the evolution of inverter-based resource regulation and applies them to large-load integration. It identifies critical gaps in modeling accuracy, interconnection processes, performance standards, and compliance mechanisms. Technical recommendations emphasize advanced monitoring, improved modeling, coordinated communication protocols, modernized substations, and structured behind-the-meter control schemes. Collectively, these measures provide a roadmap to maintain bulk power system reliability while enabling the continued growth of large, electrified digital infrastructure.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

The Role of the U.S. Electric Distribution System in Serving Data Center and Other Large Loads

The rapid expansion of data centers in the United States is reshaping how the electric distribution system must plan for and accommodate large load interconnections. This report evaluates the role of the distribution grid in serving these loads, from small edge facilities to hyperscale campuses. Using national datasets, utility filings, and industry studies, we assess demand growth, reliability requirements, interconnection thresholds, and infrastructure needs at substations and feeders. The analysis highlights the mismatch between fast data center development timelines and slower utility planning and construction cycles, as well as strategies such as phased energization, on-site generation, hosting capacity maps, and structured interconnection frameworks. While focused on data centers, the insights also apply to other high-density loads such as advanced manufacturing, hydrogen production, and electrified transportation. The report concludes with approaches to align planning processes, transparency tools, and regulatory frameworks so utilities can manage new large loads in ways that support a reliable and resilient grid.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Particle Swarm Optimization of Dynamic Load Model Parameters in Large Systems

This paper considers two dynamic load models that are widely used in industry to account for induction motor behavior: CMLD and CLOD. These models must be parametrized for the specific utility system in a general way so that they can be used in planning studies and provide a conservative but realistic representation of load behavior. This study considers a measurement-based approach to tuning both models. The load modeling study compares the response of the tuned models to generic candidate models using historical events. This study considers one area-based subsystem to simplify the modeling approach and reduce the number of models required for simulations. Additionally, because dynamic load models often produce similar results for different sets of parameters, a sensitivity study was conducted to assess the parameter impacts on the voltage response. The sensitivity study covers the parameters that are tuned using event measurements. The process to estimate the parameters uses the particle-swarm optimization algorithm. Overall, the performance of the tuned model more accurately captures recovery voltage, delayed recovery, and settling voltage than its predecessor models while not being overly tuned so that it remains general for peak summer conditions.

dynamic load modeling↗