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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Li-ion cells for terrestrial robots

SAFT prismatic wound 5 Ahr MP series cells were evaluated for potential application in a lithium ion battery designed for Tactical Mobile Robots (TMR). In order to satisfy battery design requirements, a 10 Ahr battery containing two parallel 8-cell strings was proposed. The proposed battery has a weight and volume of approximately 3.2kg and 1.6 liters, respectively. Cell qualification procedures include initial characterization, followed by charge/discharge cycling at 100% DOD with intermittent EIS measurements at various state of charge. Certain cells were also subjected to extreme operational temperatures for worst-case analysis. Excellent specific energy (>130 Whr/kg) was obtained with initial characterization cycles. Even at abusive thermal conditions, the cell capacity fade was less than Ahr after 300 cycles. Rate characterization showed good cell discharge behavior with minimal decrease in capacity. At various state of charge, impedance measurements suggest that the cathode play a more significant role in capacity. At various state of charge impedance measurements suggest that the cathode play a more significant role in capacity fade than the anode.

robots↗
DOE OSTI2022

Adaptive Fault Detection Based on Neural Networks and Multiple Sampling Points for Distribution Networks and Microgrids

Smart networks such as microgrid (MG) and active distribution networks (ADN) have been recently playing an important role in power system operation. The design and implementation of appropriate protection systems for such networks must be addressed, which imposes new technical challenges. This paper presents the implementation and validation aspects of an adaptive fault detection strategy based on neural networks (NNs) and multiple sampling points for ADN and MG. The solution is implemented on an edge device. Artificial NNs are used to derive a data-driven model that uses only local measurements to detect fault states of the network without the need for communication infrastructure. Multiple sampling points are used to derive a data-driven model, which allows the generalization considering the implementation in physical systems. The adaptive fault detector model is implemented on a Jetson Nano system, which is a single-board computer (SBC) with a small Graphic Processing Unit (GPU) intended to run machine learning loads at the edge. The proposed method is tested in a physical, real-life, low-voltage network located at Universidad del Norte, Colombia. This testing network is based on the IEEE-13 Node Test Feeder scaled down to 220 V. The validation in a simulation environment shows the accuracy and dependability above 99.6%, while the real-time tests show the accuracy and dependability of 95.5% and 100%, respectively. Without hard-to-derive parameters, the easy-to-implement embedded model highlights the potential for real-life applications.

42 ENGINEERING↗
DOE OSTI2024

Deep Generative Models in Energy System Applications: Review, Challenges, and Future Directions

In recent years, with the advent of mature machine learning products like ChatGPT, Stable Diffusion, and Sora, the world has witnessed tremendous changes driven by the rapid development of generative artificial intelligence (GAI). Beyond applications in text, speech, image, and video creation, deep generative models (DGMs) underpinning these cutting-edge technologies have also been employed by domain researchers to address scientific and engineering challenges. This paper aims to fill a gap in the research community by providing a systematic review of how DGMs have been utilized in energy system applications. After introducing four most popular DGMs, we review and categorize 196 research articles into five focus areas: data generation, forecasting, situational awareness, modeling, and optimal decision-making. Through this classification, we uncover trends in how DGMs are employed for each type of problem, highlighting GAI techniques that contribute to breakthroughs over traditional methods. We discuss limitations in existing literature, engineering challenges, and propose future directions, all tailored to the unique nature of problems in energy system engineering. Our goal is to offer insights for energy system domain researchers, providing a comprehensive view of existing studies and potential future opportunities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

A low-complexity non-intrusive approach to predict the energy demand of buildings over short-term horizons

Reliable, non-intrusive, short-term (of up to 12 hours ahead) prediction of a building's energy demand is a critical component of intelligent energy management applications. A number of such approaches have been proposed over time, utilizing various statistical and, more recently, machine learning techniques, such as decision trees, neural networks and support vector machines. Importantly, all of these works barely outperform simple seasonal auto-regressive integrated moving average models, while their complexity is significantly higher. Here, we propose a novel low-complexity non-intrusive approach that improves the predictive accuracy of the state-of-the-art by up to ~10%. The backbone of our approach is a K-nearest neighbours search method, that exploits the demand pattern of the most similar historical days, and incorporates appropriate time-series pre-processing and easing. In the context of this work, we evaluate our approach against state-of-the-art methods and provide insights on their performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Deep Reinforcement Learning for Autonomous Water Heater Control

Electric water heaters represent 14% of the electricity consumption in residential buildings. An average household in the United States (U.S.) spends about USD 400–600 (0.45 ¢/L–0.68 ¢/L) on water heating every year. In this context, water heaters are often considered as a valuable asset for Demand Response (DR) and building energy management system (BEMS) applications. To this end, this study proposes a model-free deep reinforcement learning (RL) approach that aims to minimize the electricity cost of a water heater under a time-of-use (TOU) electricity pricing policy by only using standard DR commands. In this approach, a set of RL agents, with different look ahead periods, were trained using the deep Q-networks (DQN) algorithm and their performance was tested on an unseen pair of price and hot water usage profiles. The testing results showed that the RL agents can help save electricity cost in the range of 19% to 35% compared to the baseline operation without causing any discomfort to end users. Additionally, the RL agents outperformed rule-based and model predictive control (MPC)-based controllers and achieved comparable performance to optimization-based control.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Integrated Transmission-and-Distribution System Modeling of Power Systems: State-of-the-Art and Future Research Directions

Integrated transmission-and-distribution (T&D) modeling is a new and developing method for simulating power systems. Interest in integrated T&D modeling is driven by the changes taking place in power systems worldwide that are resulting in more decentralized power systems with increasingly high levels of distributed energy resources. Additionally, the increasing role of the hitherto passive energy consumer in the management and operation of power systems requires more capable and detailed integrated T&D modeling to understand the interactions between T&D systems. Although integrated T&D modeling has not yet found widespread commercial application, its potential for changing the decades-old power system modeling approaches has led to several research efforts in the last few years that tried to (i) develop algorithms and software for steady-state and dynamic modeling of power systems and (ii) demonstrate the advantages of this modeling approach compared with traditional, separated T&D system modeling. In this paper, we provide a review of integrated T&D modeling research efforts and the methods employed for steady-state and dynamic modeling of power systems. We also discuss our current research in integrated T&D modeling and the potential directions for future research. This paper should be useful for power systems researchers and industry members because it will provide them with a critical summary of current research efforts and the potential topics where research efforts are needed to further advance and demonstrate the utility of integrated T&D modeling.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2013

Li-Ion Electrolytes with Improved Safety and Tolerance to High-Voltage Systems

Given that lithium-ion (Li-ion) technology is the most viable rechargeable energy storage device for near-term applications, effort has been devoted to improving the safety characteristics of this system. Therefore, extensive effort has been devoted to developing nonflammable electrolytes to reduce the flammability of the cells/battery. A number of promising electrolytes have been developed incorporating flame-retardant additives, and have been shown to have good performance in a number of systems. However, these electrolyte formulations did not perform well when utilizing carbonaceous anodes with the high-voltage materials. Thus, further development was required to improve the compatibility. A number of Li-ion battery electrolyte formulations containing a flame-retardant additive [i.e., triphenyl phosphate (TPP)] were developed and demonstrated in high-voltage systems. These electrolytes include: (1) formulations that incorporate varying concentrations of the flame-retardant additive (from 5 to 15%), (2) the use of mono-fluoroethylene carbonate (FEC) as a co-solvent, and (3) the use of LiBOB as an electrolyte additive intended to improve the compatibility with high-voltage systems. Thus, improved safety has been provided without loss of performance in the high-voltage, high-energy system.

Smart, Marshall C.↗
DOE OSTI2020

Can Polyelectrolyte Mechanical Properties be Directly Modulated by an Electric Field? A Molecular Dynamics Study

Multifunctionality in polymers facilitates their application in emerging technologies. Electrical fields are a preferred stimulus because of the speed and ease of application to bulk polymers. While a wide range of electrically triggered actuators are developed, and electrically controlled adhesion between gels is demonstrated, modification of bulk mechanical properties via electrical stimuli remains elusive. Polymers with covalently incorporated ionic charge (polyelectrolytes) should be well suited to achieving this goal since the mechanical properties depend on electrostatic interactions and these charges are intrinsically susceptible to electric fields. Molecular dynamics simulations are utilized here to investigate whether electric fields can modulate the mechanical properties of polyelectrolytes and to understand the governing mechanisms. Mechanical property modulation by electric field is found to be sensitive to the charge distribution—charges must be tightly attached to the polymer backbone, and responsivity is greater if a single backbone contains both positive and negative charges. The dominant mechanisms are reorientation and stretching of the polymer chains, which also elongate the ionic clusters to maintain strong electrostatic interactions throughout deformation. Furthermore, these insights are critical for future experimental realization of polymers with electric field regulated mechanical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Benchmarking blockchain-based gene-drug interaction data sharing methods: A case study from the iDASH 2019 secure genome analysis competition blockchain track

Blockchain distributed ledger technology is just starting to be adopted in genomics and healthcare applications. Despite its increased prevalence in biomedical research applications, skepticism regarding the practicality of blockchain technology for real-world problems is still strong and there are few implementations beyond proof-of-concept. We focus on benchmarking blockchain strategies applied to distributed methods for sharing records of gene-drug interactions. We expect this type of sharing will expedite personalized medicine. We generated gene-drug interaction test datasets using the Clinical Pharmacogenetics Implementation Consortium (CPIC) resource. We developed three blockchain-based methods to share patient records on gene-drug interactions: Query Index, Index Everything, and Dual-Scenario Indexing. We achieved a runtime of about 60 s for importing 4,000 gene-drug interaction records from four sites, and about 0.5 s for a data retrieval query. Our results demonstrated that it is feasible to leverage blockchain as a new platform to share data among institutions.

60 APPLIED LIFE SCIENCES↗
NASA NTRSDate not supplied

Harnessing Artificial Intelligence for Medical Diagnosis and Treatment During Space Exploration Missions

From May 8th to June 9th, 2023, I had the opportunity to participate in an experiential learning experience at Johnson Space Center in Houston, TX with Exploration Medical Capability (ExMC), an element of the NASA Human Research Program. During this research experience, I was not only able to work on the above titled research project, but also gain an immense exposure to the field of aerospace medicine, make numerous connections within the field, tour NASA facilities, as well as travel to the Aerospace Medical Association Annual Conference (AsMA) in New Orleans. To briefly introduce my project, it is well understood that the medical capabilities available to crew medical officers (CMOs) on the International Space Station will be different than the capabilities available and needed during deep space exploration missions to the Moon, Mars, and beyond. Ground support is particularly limited due to distance, communication delays (or lack of communication), and lack of resupply. Therefore, to support medical care by CMOs on these missions, robust clinical decision support systems (CDSSs) must be designed. The recent publication and public launch of generative artificial intelligence (AI) tools based upon large language models (LLM) such as ChatGPT provides the opportunity to create a smart assistant for onboard triage, diagnosis, and treatment of medical conditions. Ultimately, the overall purpose of the project was to research what AI tools currently exist or are in development, and to see how they might be implemented onboard during exploration class spaceflights of the future. The ExMC element is actively developing several tools to be used in preparation for and during deep space exploration missions. One of those tools, known as IMPACT, is a probabilistic risk assessment model which can be used to propose a desired medical system (based on mass and volume) and suggest the clinical outcomes likely to occur for a design reference mission (DRM). The group recently presented the IMPACT model and a DRM of interest titled “Modified Long Duration Lunar Orbital and Lunar Surface” (mLDLOLS) at the recent AsMA conference. The mLDLOLS mock mission is a 9 month and 6-day deep space exploration mission consisting of time in Moon’s orbit (3 months on the Gateway space station), on the lunar surface (3 months within habitat), and another 3 months on Gateway before return to Earth. For this DRM, IMPACT ultimately outlined a preferred medical system that was then associated with medical conditions considered to be most likely based on frequency, most likely to cause astronaut task time loss (TTL), most likely to cause return to definitive care (RTDC), and most likely cause loss of crew life (LOCL). IMPACT also highlighted the medical capabilities/skills that would be required to care for those medical conditions, such as performing a history of present illness or musculoskeletal exam with ultrasound. The primary objective of the project was to perform a survey of the AI tools and systems applicable to the conditions outlined for the proposed mLDLOLS mission. Using PubMed (including most relevant MeSH terms) and Google Scholar, we then created a robust annotated bibliography organized by condition. The 56-page and over 500 reference annotated bibliography was subsequently used to create a review outline that would become the basis for drafting of a future publication. For the review outline, we took those medical conditions researched within the annotated bibliography (condition-based approach) and deployed a systems-based approach, combining those medical conditions and related tools into ten categories. These categories included general/all-purpose CDSSs, tools to diagnose or manage respiratory, dermatologic, neurologic, auditory and vestibular, ophthalmic, musculoskeletal, infection-associated, and gynecologic conditions, as well as tools that could be deployed in the setting of trauma/emergency. With the completion of the 30-page outline, we then began drafting the review paper. To conclude the research experience, I presented the findings from our survey to the ExMC Clinical and Science team. With these objectives, I ultimately learned about the number of AI tools that exist today to assist medical professionals with the triage, diagnosis, and management of several medical conditions. These tools can span from chatbot assistants to help triage knee pain to vision transformer models that can identify ophthalmic conditions based on ocular surface images captured with a cell phone. We also highlighted the current gaps that exist in the literature alongside the advancements that are needed to make the desired CDSS for deep space exploration missions. With this experience, I certainly confirmed an existing career goal and identified several additional skills needed to become an aerospace medical doctor including knowledge of critical care in an extreme medicine setting, aerospace engineering and human integration systems, artificial intelligence, machine learning, and risk models. I also identified numerous transferable skills for this career goal including the basic knowledge of medicine (MD), deployment of the scientific method for critical thought about new scientific questions (PhD), review of published literature, including creating an annotated bibliography (PhD), as well as detailed scientific writing (PhD). The results of my research will likely guide the design of an all-encompassing onboard medical assistant for use during deep space exploration missions of the future. I plan on sharing the outcomes from this experience with my peers at a student seminar in the Fall semester on August 30th. During the seminar, I will detail the project, my experience at NASA and AsMA, as well as offer best practice guidelines for students entertaining similar experiences or careers. In conclusion, I would like to thank the WVU School of Medicine, Research and Graduate Education office, as well as NASA ExMC for the unwavering support of this life-changing experience.

Ryan A. Lacinski↗
NASA NTRS2007

Performance of Low Temperature Electrolytes in Experimental and Prototype Li-Ion Cells

Due to their attractive properties and proven success, Li-ion batteries have become identified as the battery chemistry of choice for a number of future NASA missions. A number of these applications would be greatly benefited by improved performance of Li-ion technology over a wider operating temperature range, especially at low temperatures, such as future ESMD missions. In many cases, these technology improvements may be mission enabling, and at the very least mission enhancing. In addition to aerospace applications, the DoE has interest in developing advanced Li-ion batteries that can operate over a wide temperature range to enable terrestrial HEV applications. Thus, our focus at JPL in recent years has been to extend the operating temperature range of Li-ion batteries, especially at low temperatures. To accomplish this, the main focus of the research has been devoted to developing improved lithium-ion conducting electrolytes. In the present paper, we would like to present some of the results we have obtained with ethylene carbonate-based electrolytes optimized for low temperature in experimental MCMB-LiNixCo1_x0 2 cells. In addition to obtaining discharge and charge rate performance data at various temperatures, electrochemical measurements were performed on individual electrodes (made possible by the incorporation of Li reference electrodes), including EIS, linear polarization and Tafel polarization measurements. The combination of techniques enables the elucidation of various trends associated with electrolyte composition. In addition to investigating the behavior in experimental cells, the performance of many promising low temperature electrolytes was demonstrated in large capacity, aerospace quality Li-ion prototype cells. These cells were subjected to a number of performance tests, including discharge rate characterization, charge rate characterization, cycle life performance at various temperatures, and power characterization tests.

Li-ion batteries↗
DOE OSTI2024

Durability enhancement of all-solid-state electrochromic devices by adjusting the charge density ratio between electrochromic and counter electrode layers

Here, owing to an increase in global warming, smart-window devices based on charge-balanced electrochromic devices (ECDs), which exhibit high potential to increase the thermal efficiency of buildings, have gained prominence. However, studies on the fabrication and cycling stability of charge-balanced ECDs are scarce. In this study, WO 3 and NiO x films were deposited on indium-tin-oxide (ITO)-coated glass substrates by reactive direct-current magnetron sputtering, and the deposition time was varied to control the thickness and charge density of the thin films. Subsequently, the NiO x /ITO/glass and WO 3 /ITO/glass substrates were laminated with a Li-based polymeric electrolyte to fabricate all-solid-state ECDs comprising electrochromic (EC) and counter-electrode (CE) layers in charge-density ratios of 12.6, 6.4, 2.3, and 1.1. Changes in the electrochromic properties, device-layer microstructure, crystal structure, and elemental composition of the as-constructed ECDs before and after degradation were investigated to understand the influence of the charge-density ratio of the EC and CE layers on the long-term durability of ECDs. Increasing the charge-density ratio decreased the cycling stability of the device owing to changes in the microstructure and crystal structure of the NiO x layer in the microstructural deep-trap sites. Among all the ECDs, those comprising EC and CE layers with similar charge densities showed the most stable optical modulation and highest long-term durability. Finally, based on the aforementioned results, a degradation mechanism for charge-imbalanced all-solid-state ECDs was proposed. This study is expected to open new frontiers in designing optimal-performance electrochemical devices with a wide variety of potential applications.

14 SOLAR ENERGY↗
NASA NTRS2022

Review of Solar Energetic Particle Models

Solar Energetic Particle (SEP) events are interesting from a scientific perspective as they are the product of a broad set of physical processes from the corona out through the extent of the heliosphere, and provide insight into processes of particle acceleration and transport that are widely applicable in astrophysics. From the operations perspective, SEP events pose a radiation hazard for aviation, electronics in space, and human space exploration, in particular for missions outside of the Earth’s protective magnetosphere including to the Moon and Mars. Thus, it is critical to improve the scientific understanding of SEP events and use this understanding to develop and improve SEP forecasting capabilities to support operations. Many SEP models exist or are in development using a wide variety of approaches and with differing goals. These include computationally intensive physics-based models, fast and light empirical models, machine learning-based models, and mixed-model approaches. The aim of this paper is to summarize all of the SEP models currently developed in the scientific community, including a description of model approach, inputs and outputs, free parameters, and any published validations or comparisons with data.

Kathryn Whitman↗
DOE OSTI2020

Evaluating the Adaptability of Reinforcement Learning Based HVAC Control for Residential Houses

Intelligent Heating, Ventilation, and Air Conditioning (HVAC) control using deep reinforcement learning (DRL) has recently gained a lot of attention due to its ability to optimally control the complex behavior of the HVAC system. However, more exploration is needed on understanding the adaptability challenges that the DRL agent could face during the deployment phase. Using online learning for such applications is not realistic due to the long learning period and likely poor comfort control during the learning process. Alternatively, DRL can be pre-trained using a building model prior to deployment. However, developing an accurate building model for every house and deploying a pre-trained DRL model for HVAC control would not be cost-effective. In this study, we focus on evaluating the ability of DRL-based HVAC control to provide cost savings when pre-trained on one building model and deployed on different house models with varying user comforts. We observed around 30% of cost reduction by pre-trained model over baseline when validated in a simulation environment and achieved up to 21% cost reduction when deployed in the real house. This finding provides experimental evidence that the pre-trained DRL has the potential to adapt to different house environments and comfort settings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗
NASA NTRS2011

Kinematics and Kinetics of Squat and Deadlift Exercises with Varying Stance Widths

The primary motion of squat and deadlift exercise involves flexion and extension of the hips, knees, and ankles, but each exercise can be performed with variations in stance width. These variations may result in differing kinematics and ground reaction forces (GRF), which may in turn affect joint loading. PURPOSE: The purpose of this investigation was to compare ankle, knee, and hip kinematics and kinetics of normal squat (NS), wide-stance squat (WS), normal deadlift (ND), and sumo deadlift (SD). We hypothesized that hip joint kinematics and work at each joint would differ between exercise variations. METHODS: Six subjects (3 m/3 f; 70.0 plus or minus 13.7 kg; 168 plus or minus 9.9 cm) performed each lift in normal gravity on the ground-based version of the Advanced Resistive Exercise Device (ARED) used on the International Space Station. The ARED provided resistance with a combination vacuum tube/flywheel mechanism designed to replicate the gravitational and inertial forces of free weights. Subjects completed each lift with their 10-repetition maximum load. Kinematic data were collected at 250 Hz by a 12-camera motion-capture system (Smart-D, BTS Bioengineering, Milan, Italy), and GRF data were collected at 1000 Hz with independent force platforms for each leg (Model 9261, Kistler Instruments AG, Winterhur, Switzerland). All data were captured simultaneously on a single workstation. The right leg of a single lift for each motion was analyzed. Modeling software (OpenSim 2.2.0, Simbios, Palo Alto, CA) determined joint kinematics and net positive and negative work at each lower extremity joint. Total work was found as the sum of work across all joints and was normalized by system mass. Effect sizes and their 95% confidence intervals were computed between conditions. RESULTS: Peak GRF were similar for each lift. There were no differences between conditions in hip flexion range of motion (ROM). For hip adduction ROM, there were no differences between the NS, WS, and SD. However, hip adduction ROM was greater during the NS and SD than during the ND. Hip rotation ROM was greater during the WS than during the NS and SD, and was greater during the SD than during the ND. For knee and ankle flexion ROM, the ND, WS, and SD were not different, but ROM was greater during the NS than the ND and greater during the WS than the SD. Total eccentric work was greater during the WS than the SD. Otherwise, there were no differences in eccentric or concentric work between conditions. CONCLUSIONS: Although squat and deadlift exercises consist of similar motions, there are kinematic differences between them that depend on stance width. Total eccentric and concentric work are similar for different lifts, but differing kinematics may require activation of different musculature for each variation. With respect to each condition, in the ND the ROM of each joint tended to be less, and the WS tended to trade knee motion for hip motion. PRACTICAL APPLICATIONS: Knowledge of differences in kinematics and kinetics between different squat and deadlift variations is important for coaches and rehabilitation personnel to understand when prescribing exercise. Our results suggest that each variation of the squat and deadlift should be considered a separate exercise that may induce different long-term training effects.

DeWitt, John K.↗
NASA NTRS2004

RFID and Memory Devices Fabricated Integrally on Substrates

Electronic identification devices containing radio-frequency identification (RFID) circuits and antennas would be fabricated integrally with the objects to be identified, according to a proposal. That is to say, the objects to be identified would serve as substrates for the deposition and patterning of the materials of the devices used to identify them, and each identification device would be bonded to the identified object at the molecular level. Vacuum arc vapor deposition (VAVD) is the NASA derived process for depositing layers of material on the substrate. This proposal stands in contrast to the current practice of fabricating RFID and/or memory devices as wafer-based, self-contained integrated-circuit chips that are subsequently embedded in or attached to plastic cards to make smart account-information cards and identification badges. If one relies on such a chip to store data on the history of an object to be tracked and the chip falls off or out of the object, then one loses both the historical data and the means to track the object and verify its identity electronically. Also, in contrast is the manufacturing philosophy in use today to make many memory devices. Today s methods involve many subtractive processes such as etching. This proposal only uses additive methods, building RFID and memory devices from the substrate up in thin layers. VAVD is capable of spraying silicon, copper, and other materials commonly used in electronic devices. The VAVD process sprays most metals and some ceramics. The material being sprayed has a very strong bond with the substrate, whether that substrate is metal, ceramic, or even wood, rock, glass, PVC, or paper. An object to be tagged with an identification device according to the proposal must be compatible with a vacuum deposition process. Temperature is seldom an issue as the substrate rarely reaches 150 F (66 C) during the deposition process. A portion of the surface of the object would be designated as a substrate for the deposition of the device. By use of a vacuum arc vapor deposition apparatus, a thin electrically insulating film would first be deposited on the substrate. Subsequent layers of materials would then be deposited and patterned by use of known integrated-circuit fabrication techniques. The total thickness of the deposited layers could be much less than the 100- m thickness of the thinnest state-of-the-art self-contained microchips. Such a thin deposit could be readily concealed by simply painting over it. Both large vacuum chambers for production runs and portable hand-held devices for in situ applications are available.

Schramm, Harry F.↗
DOE OSTI2021

Enabling Realistic Communications Evaluations for ADMS

Increasing penetration levels of inverter-based distributed energy resources (DERs) in distribution systems are creating challenges in system operation. Currently, wired or proprietary wireless communications are used by advanced distribution management systems (ADMS) to detect the state of the system and control the DERs for optimal operation. Wireless communications are an alternative solution that can enable connectivity between the dispersed assets used in distribution system applications. As demand for the seamless integration of distributed energy resources (DERs) continues to increase, proper networking and communications systems are becoming important to support the DER infrastructure. This report summarizes validation of a private wireless LTE network in a laboratory environment. The purpose of this work is to 1) demonstrate the effectiveness of private wireless LTE communication for grid applications and 2) provide a means of evaluating latency and overall performance of wireless communication in grid applications. First, private wireless LTE communication was validated in a direct transfer trip relaying scenario as an example of one-way communications using grid equipment. This study provided a baseline understanding of the variation in latency for seven different kinds of wireless scenarios shown in Figure A below. As expected, weak (attenuated) wireless signal-based communication yielded the widest ranges in latency. When higher priority was set for the trip signal communication, this resulted in lower latency in communication timing. In the final phase of this project, the private wireless LTE network was validated using two-way communications in an advanced distribution management system (ADMS) testbed which was developed in the ESIF at NREL. The purpose of this was to study the impact of wireless communication on grid performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗