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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 1,027 records · Page 57

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NASA NTRS2000

Fracture Tests of Etched Components Using a Focused Ion Beam Machine

Many optical MEMS device designs involve large arrays of thin (0.5 to 1 micron components subjected to high stresses due to cyclic loading. These devices are fabricated from a variety of materials, and the properties strongly depend on size and processing. Our objective is to develop standard and convenient test methods that can be used to measure the properties of large numbers of witness samples, for every device we build. In this work we explore a variety of fracture test configurations for 0.5 micron thick silicon nitride membranes machined using the Reactive Ion Etching (RIE) process. Testing was completed using an FEI 620 dual focused ion beam milling machine. Static loads were applied using a probe. and dynamic loads were applied through a piezo-electric stack mounted at the base of the probe. Results from the tests are presented and compared, and application for predicting fracture probability of large arrays of devices are considered.

Kuhn, Jonathan, L.↗

NASA NTRS2004

Thermal Performance of Capillary Pumped Loops Onboard Terra Spacecraft

The Terra spacecraft is the flagship of NASA's Earth Science Enterprise. It provides global data on the state of atmosphere, land and oceans, as well as their interactions with solar radiation and one another. Three Terra instruments utilize Capillary Pumped Heat Transport System (CPHTS) for temperature control: Each CPHTS, consisting of two capillary pumped loops (CPLs) and several heat pipes and electrical heaters, is designed for instrument heat loads ranging from 25W to 264W. The working fluid is ammonia. Since the launch of the Terra spacecraft, each CPHTS has been providing a stable interface temperature specified by the instrument under all modes of spacecraft and instrument operations. The ability to change the CPHTS operating temperature upon demand while in service has also extended the useful life of one instrument. This paper describes the design and on-orbit performance of the CPHTS thermal systems.

Ku, Jentung↗

NASA NTRS2006

Developmental Considerations on the Free-Piston Stirling Power Convertor for Use in Space

Free-piston Stirling power conversion has been considered a candidate for radioisotope power systems for space for more than a decade. Prior to the free-piston Stirling architecture, systems were designed with kinematic Stirling engines with rotary alternators to convert heat to electricity. These systems were proposed with lightly loaded linkages to achieve the necessary life. When the free-piston configuration was initially proposed, it was thought to be attractive due to the relatively high conversion efficiency, acceptable mass, and the potential for long life and high reliability. These features have consistently been recognized by teams that have studied technology options for radioisotope power systems. Since free-piston Stirling power conversion was first considered for space power applications, there have been major advances in three general areas of development: demonstration of life and reliability, the success achieved by Stirling cryocoolers in flight, and the overall developmental maturity of the technology for both flight and terrestrial applications. Based on these advances, free-piston Stirling convertors are currently being developed for a number of terrestrial applications. They commonly operate with the power, efficiency, life, and reliability as intended, and much of the development now centers on system integration. This paper will summarize the accomplishments of free-piston Stirling power conversion technology over the past decade, review the status, and discuss the challenges that remain.

Schreiber, Jeffrey G.↗

NASA NTRS2007

Developmental Considerations on the Free-piston Stirling Power Convertor for Use in Space

Schreiber, Jeffrey G.↗

NASA NTRS1981

Reciprocating piston pump system with screw drive

A pump system of the reciprocating piston type is described, which facilitates direct motor drive and cylinder sealing. A threaded middle potion of the piston is engaged by a nut connected to rotate with the rotor of an electric motor, in a manner that minimizes loading on the rotor by the use of a coupling that transmits torque to the nut but permits it to shift axially and radially with respect to the rotor. The nut has a threaded hydrostatic bearing for engaging the threaded piston portion, with an oil-carrying groove in the nut being interrupted. A fluid emitting seal located at the entrance to each cylinder, can serve to center the piston within the cylinder, wash the piston, and to aid in sealing. The piston can have a long stroke to diameter ratio to minimize reciprocations and wear on valves at high pressures. The voltage applied to the motor can be reversed prior to the piston reaching the end of its stroke, to permit pressure on the piston to aid in reversing the motor.

Perkins, Gerald S.↗

NASA NTRS2016

Mechanical Model Development for Composite Structural Supercapacitors

Novel composite structural supercapacitor concepts have recently been developed as a means both to store electrical charge and to provide modest mechanical load carrying capability. Double-layer composite supercapacitors are often fabricated by impregnating a woven carbon fiber fabric, which serves as the electrodes, with a structural polymer electrolyte. Polypropylene or a glass fabric is often used as the separator material. Recent research has been primarily limited to evaluating these composites experimentally. In this study, mechanical models based on the Multiscale Generalized Method of Cells (MSGMC) were developed and used to calculate the shear and tensile properties and response of two composite structural supercapacitors from the literature. The modeling approach was first validated against traditional composite laminate data. MSGMC models for composite supercapacitors were developed, and accurate elastic shear/tensile properties were obtained. It is envisioned that further development of the models presented in this work will facilitate the design of composite components for aerospace and automotive applications and can be used to screen candidate constituent materials for inclusion in future composite structural supercapacitor concepts.

Micromechanics↗

NASA NTRS2017

A Piezoelectric Passive Wireless Sensor for Monitoring Strain

Interest in passive wireless sensing has grown over the past few decades to meet demands in structural health monitoring.(Deivasigamani et al., 2013; Wilson and Juarez, 2014) This work describes a passive wireless sensor for monitoring strain, which does not have an embedded battery or chip. Without an embedded battery, the passive wireless sensor has the potential to maintain its functionality over long periods in remote/harsh environments. This work also focuses on monitoring small strain (less than 1000 micro-ɛ). The wireless sensing system includes a reader unit, a coil-like transponder, and a sensing unit. It operates in the Megahertz (MHz) frequency range, which allows for a few centimeters of separation between the reader and sensing unit during measurements. The sensing unit is a strain-sensitive piezoelectric resonator that maximizes the energy efficiency at the resonance frequency, so it converts nanoscale mechanical variations to detectable differences in electrical signal. In response to an external loading, the piezoelectric sensor breaks from its original electromechanical equilibrium, and the resonant frequency shifts as the system reaches a new balanced equilibrium. In this work, the fixture of the sensing unit is a small, sticker-like package that converts the surface strain of a test material to measurable shifts in resonant frequencies. Furthermore, electromechanical modeling provides a lumped-parameter model of the system to describe and predict the measured wireless signals of the sensor. Detailed characterization demonstrates how this wireless sensor has resolution comparable to that of conventional wired strain sensors for monitoring small strain.

Zou, Xiyue↗

NASA NTRSDate not supplied

Human System Risk Changes in 2021

The Human System Risk Board (HSRB) has the overall responsibility for tracking the evolution of the top ~30 human system risks that it has identified to be associated with human spaceflight. As part of this process, the Board is charged with maintaining a consistent, integrated process to mitigate those risks, and developing evidence-based risk posture recommendations. Risks are re-evaluated in a Continuous Risk Management (CRM) process. This session will summarize the risk posture changes that have occurred in the last year and what high level research, performance, and epidemiologic data have informed those changes. Human System Risks updated in 2021 include: Dynamic Loads, Sensorimotor, EVA, Crew Egress, Behavioral Medicine, Electrical Shock, Human System Integration Architecture (HSIA), Toxic Exposure, Bone Fracture, Cardiovascular, Medical Conditions, Renal Stone, CO2 Exposure, and Pharmacology.

Mary Van Baalen↗

NASA NTRSDate not supplied

Development of an Adaptive Droop Control Method for Interconnected Lunar DC Microgrids Using Power Hardware-in-the-Loop

NASA’s Artemis Program outlines the need for a habitat capable of sustaining human life as well as mining and producing raw materials on the lunar surface. This mission is viewed as a means towards deeper space exploration, with plans for reaching Mars and beyond. Human presence on the moon is not possible without the ability to generate and distribute energy, namely electricity, through a network of energy sources, loads, and power converters called a microgrid. Multiple microgrids can be deployed on the moon based on location and need. Separate microgrids will require interconnection to increase resiliency and reliability given the mission’s high criticality. A method for adaptive control over power converters connecting two dc microgrids is proposed. A simulation is modeled after the lunar power system with two approaches to power converter droop control, allowing for a more flexible and adaptive microgrid architecture. Further experiments are conducted using the control methods in a power hardware-in-the-loop test environment to study the performance of hardware converter control used in this application.

dc microgrid↗

DOE OSTI2022

Designing the PR100 Study: Puerto Rico Grid Resilience and Transition to 100% Renewable Energy

Puerto Rico has committed to meeting its electricity needs with 100% renewable energy by 2050, along with realizing interim goals of 40% by 2025, 60% by 2040, the phaseout of coal-fired generation by 2028, and a 30% improvement in energy efficiency by 2040 as established in Act 17. [1] To meet these goals and support widespread end-use electrification, the territory must explore how renewable energy and other generation technologies can be developed with energy storage, distributed generation, distribution control, electric vehicles, and energy efficient and responsive loads in each of Puerto Rico's cities and communities. To support Puerto Rico in reaching its renewable energy goals; help ensure energy system resilience against future extreme weather events; improve energy justice; and provide inputs to LUMA Energy's walk, jog, and run approach in its coordinated planning roadmap, the U.S. Department of Energy, National Renewable Energy Laboratory, Argonne National Laboratory, Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, Pacific Northwest National Laboratory and Sandia National Laboratories propose to evaluate 100% renewable energy pathways through an integrated analysis process. This talk will present steps in designing a two-year study entitled Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy (PR100). [1] U.S. Energy Information Administration (EIA). 2020. Puerto Rico Territory Energy Profile.

100% renewable energy↗

DOE OSTI2023

Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100)

ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Spatiotemporal Super-Resolution with Generative Machine Learning for Creating Renewable Energy Resource Data Under Climate Change Scenarios

As we plan for a future with higher penetrations of renewables and increasing electrification, it becomes more important to understand how the electricity grid will operate under a variety of weather events. We must also consider that the weather our future grid will experience will be different and possibly more extreme than the historical weather that we have extensive data for. We can use data from global climate models (GCMs) to help understand how our climate may change over the next several decades, but there is often a significant gap between the low-resolution GCM data and the high-resolution weather data required to study power systems under specific weather events. Therefore, our objective in this work is to develop tools that can bridge this gap by using low-resolution GCM data to create realistic high-resolution weather datasets that can be used to study renewable energy generation and electricity demand. To accomplish this objective, we have developed a set of generative machine learning models that can rapidly downscale GCM daily average output data at an approximate grid resolution of 100km to hourly data at an approximate 4 km grid resolution. The models can be used to create high resolution data from nearly any GCM included in the Coupled Model Intercomparison Project (CMIP) Phase 5 or 6. Our methods include all datasets regularly used to study the integration of wind and solar power plants as well as changes in electricity demand due to heating and cooling loads. These models and datasets enable power systems modelers to study climate change-influenced weather events and their impact on the grid. We have downscaled and validated wind, solar, temperature, and humidity data with very promising results. The generative machine learning methods are computationally efficient and produce data that has similar statistical characteristics to current state-of-the-art historical datasets. We have trained initial generative models and produced an initial dataset collectively referred to as Sup3rCC: Super-Resolved Renewable Energy Resource Data with Climate Change Impacts. The data covers a (mostly) historical period from 2015-2025 and a future period from 2050-2059. We have also taken hypothetical high-electrification load data and scaled the heating and cooling loads with respect to the 2050-2059 high-resolution Sup3rCC meteorology. The results show how future levels of renewable energy generation and electrified load may be impacted by climate change, setting the stage for capacity expansion models to consider a dynamic climate through model years.

climate change↗

DOE OSTI2023

Carbon Mitigation Potential of Heat Pump Integrated with Thermal Storage for Grid-Interactive Residential Buildings

Residential buildings’ heating and cooling loads are associated with significant carbon emissions and peak electricity demand. Phase change material (PCM) based thermal energy storage (TES) can be used for space heating and cooling by embedding into the heat pump equipment. Past work on TES integrated with heat pumps (HP) has demonstrated significant load shifting and economic benefits. However, the potential for TES to reduce carbon emissions has not been widely explored. This study evaluates carbon mitigation potential of an ice-based TES coupled to HP (HP-TES) based on a simple rule-based control strategy accounting for electric grid emissions data. A vapor compression HP model using Engineering Equation Solver (EES). The modeled HP-TES system for single-family residential building demonstrates decreased carbon emissions with reduced peak utility cost.

Sultan, Sara↗

DOE OSTI2020

Peak Demand Savings from Efficiency: Opportunities and Practices [Slides]

Electricity systems are designed to meet peak demand - the maximum load during a specified period, typically in summer - even if that demand occurs only a few hours in a year. Yet most evaluations of electricity efficiency programs focus on reductions in annual energy use. However, these efficiency programs are also delivering peak demand savings at an affordable cost. A new study by the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) explores the program administrator (PA) cost - or the cost to implement an energy efficiency program to a utility or third party administrator - of saving peak demand through efficiency programs for electric utility customers. Berkeley Lab collected data on costs, annual energy savings, and peak demand savings for electricity efficiency programs for 52 utilities and other program administrators in 15 states between 2014 and 2018. The analysis focused on eight program types that represent 68% of the peak demand savings for the utilities and program administrators studied. The findings improve our understanding of which energy efficiency programs produce the most peak demand savings and their cost performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Promoting electrochemical rates by concurrent ionic-electronic conductivity enhancement in high mass loading cathode electrode

Enhancing the fast charging capacity of thick electrodes with high mass loading is imperative in expediting the widespread adoption of electric vehicles. Nonetheless, the insufficient charge transfer kinetics of thick electrodes hinder the movement of effective electrons and ions, hence diminishing capacity at high current rates. In this work, we applied sustainable and biodegradable cellulose nanocrystals (CNCs) as electrode additives. It is the first time to simultaneously improve the electronic conductivity by optimizing the carbon dispersion and establishing electron transfer networks, as well as boosting the ionic conductivity of electrodes by shortening the ion transfer pathway. Specifically, the LiNi 0.6 Mn 0.2 Co 0.2 O 2 electrodes incorporating 1% dual functional CNCs additive exhibit improved effective electrical conductivity from 0.11 to 0.16 S/m and risen effective ionic conductivity from 0.36 to 0.62 S/m, in comparison to counterpart electrodes without CNCs. Therefore, the 1% CNC electrode with a high mass loading of 27.0 mg/cm 2 delivers a discharge capacity of 128 mAh/g at 1 C, which is superior to that of the CNC-free electrodes (95 mAh/g). In short, this study presents a novel environmentally friendly, economically viable, and dual-functional electrode additive that enhances both electronic and ionic conductivities with the aim of facilitating the widespread adoption of fast-charging high mass loading electrodes.

25 ENERGY STORAGE↗

DOE OSTI2022

Black Swan Event Small-Sample Transfer Learning (BEST-L) and its Case Study on Electrical Power Prediction in COVID-19

The black swan event will usually cause a great impact on the normal operation of society. The scarcity of such events leads to a lack of relevant data and challenges in dealing with related problems. Different situations also make the traditional methods invalid. In this paper, a transfer learning framework and a convolutional neuron network are proposed to deal with the black swan small-sample events (BEST-L). Taking the COVID-19 as a typical black swan event, the BEST-L is utilized to achieve accurate mid-term load forecasting using the relationship between economy and electricity consumption. The experiment results show that the transfer learning model can effectively learn the basic knowledge about the relationship between the adopted input and output data and use a relatively small amount of data during the black swan event to improve the target areas' generalization. The approach and results can provide an effective approach to respond and react to sudden changes quickly and effectively in similar open problems.

black swan event↗

DOE OSTI2024

The Transactive Energy Network Template Metamodel

While transactive energy, which is defined as an allocation of electricity based on dynamically discovered values or prices, has been extensively studied, its uptake and use has been slow. This report describes a tool, the transactive network template, which should hasten the creation and uptake of transactive energy networks. Some basic principles of transactive energy are familiar from existing wholesale electricity markets. Locational prices are calculated today for zones within bulk electric transmission systems. Locational prices differ while accounting for the locational costs of electricity generation and the losses and constraints incurred when electricity is transmitted from generators and distributed to consumers. A transactive energy network might include these transmission zones. However, current research strives to apply transactive energy also in electricity distribution circuits, buildings, and even for individual generating and consuming devices. At the same time, researchers explore how to apply transactive energy in real time during increasingly shorter time intervals. Automated computational agents become necessary as transactive energy becomes applied to smaller circuit zones and at faster dynamic timescales. A transactive energy network is an example of a multi-agent system. Each zone in the network is represented by its transactive agent, which makes decisions for and acts on behalf of a business entity that is responsible for and manages one of the circuit regions. A transactive energy network is also an example of a decentralized, distributed control system. Control decisions and responsibilities are distributed among the network’s transactive agents. The transactive agents are independent; that is, there typically is no centralized authority or oversight function. Instead, transactive agents exchange transactive signals and thereby negotiate the prices and quantities of electricity that they will exchange. Initially, the circuit regions and responsibilities of transactive agents appear to be very dissimilar. Each circuit region may comprise transmission, distribution, or building-level circuits. Each has a unique position and electrical connectivity within the transactive energy network. Each possesses unique assets that either generate or consume electricity, and these (e.g., renewable energy generator, diesel generator, aggregate utility load, building load, space conditioning, refrigerator, etc.) may further differ in their price flexibility and in their strategies for responding to dynamic electricity prices. Given such diversity, an implementer’s first inclination might be to start from scratch to define all these devices and to engineer their seemingly unique interactions. Given that each implementer’s perspective may be narrow within a transactive energy network, it is unlikely that uniquely engineered systems would interact well. This is where the transactive network template is applicable. The transactive network template is a metamodel that has been developed to guide implementers as they configure their own transactive agent within a network of such agents. The object-oriented design of the transactive network template provides basic code object types that may be used and extended by implementers to represent each of the assets in their circuit region. These objects further facilitate the transactive agent’s necessary computations, which are divided among responsibilities to schedule power usage, balance electric supply and demand, and coordinate the exchange of electricity with the other transactive agents. This report addresses the conceptual transactive network template design. Implementers are directed to more formal design documents and reference implementations. A Python™-based1 reference implementation of the transactive network template has been coded, and three implementations have been configured to represent a national laboratory and two university campuses. Version 2 of the transactive node template generalizes the market class and its methods to facilitate multiple, and more diverse market coordination mechanisms than were facilitated by and demonstrated using Version 1. Version 3 includes new Appendix B, which addresses the designs of methods that would make dynamic prices track approved electricity rates. In the future, the author wishes to make the transactive network template more generally applicable to networks that require more accurate power flow. Development of the transactive network template is jointly funded by the U.S. Department of Energy (DOE) Energy Efficiency and Renewable Energy and the DOE Office of Electricity. In late 2015, one of the first projects to be funded by the DOE Grid Laboratory Modernization Laboratory Consortium was the Clean Energy and Transactive Campus project, led by Pacific Northwest National Laboratory. DOE funds were matched by an investment by the Washington Department of Commerce through its Clean Energy Fund. The transactive network template was developed to guide the implementation of transactive energy networks within this project’s scope.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Tri-level hybrid interval-stochastic optimal scheduling for flexible residential loads under GAN-assisted multiple uncertainties

Various building loads, such as heating, ventilation, and air conditioners (HVACs), electric water heaters (EWHs), and electric vehicles (EVs), can introduce opportunities for improving the flexibility of electricity consumption while satisfying the needs of building owners as well as benefiting the resilience of distribution system. To utilize such flexibility, a tri-level distribution market framework is established, including residential consumers, load aggregators (LAs), and the distribution system operator (DSO). In this work, the uncertainties from all three levels are considered. The random consumption behavior at the consumer level is modeled as a Gaussian noise that is also aggregated and transmitted to the LA level. The weather temperature in the LA level is forecasted as an interval, and the photovoltaic (PV) power in the market-clearing level is modeled by a set of power scenarios generated by Generative Adversarial Networks (GANs). Then, a hybrid interval-stochastic programming is proposed to transform the uncertain problems in the first two levels into deterministic ones. For real-time implementations, a rolling horizon optimization (RHO) scheme is employed to continuously optimize the power consumption based on the latest operating information. Finally, case studies on a modified IEEE 69-bus system validate the effectiveness of the proposed uncertainty modeling strategies and the RHO scheme.

24 POWER TRANSMISSION AND DISTRIBUTION↗