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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A tool for assessing demand side management and operating strategies for isolated microgrids

Globally, power system operators are exploring ways to leverage the capabilities of smart meters to implement fine-grained demand side management (DSM). Here this paper presents a new simulation tool to evaluate operating strategies for smart-meter-enabled (SME) islanded microgrids being advanced for sustainable rural electrification in emerging economies. Based on MATLAB/Simulink, the tool's component-level models of small microgrids can be easily configured. Alternative rule-based operating strategies are implemented with controllable supply and storage components as well as other components driven by external factors (e.g., weather and time of day). To account for the wide range of possible operating conditions in real-world applications, statistical metrics can be evaluated using Monte Carlo (MC) methods based on user-defined, time-dependent probability distributions for demands, supplies, and environmental variables. Features of the tool are demonstrated with case studies for a representative microgrid in rural Rwanda.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Unsupervised multimodal fusion of in-process sensor data for advanced manufacturing process monitoring

Effective monitoring of manufacturing processes is crucial for maintaining product quality and operational efficiency. Modern manufacturing environments often generate vast amounts of complementary multimodal data, including visual imagery from various perspectives and resolutions, hyperspectral data, and machine health monitoring information such as actuator positions, accelerometer readings, and temperature measurements. However, fusing and interpreting this complex, high-dimensional data presents significant challenges, particularly when labeled datasets are unavailable or impractical to obtain. This paper presents a novel approach to multimodal sensor data fusion in manufacturing processes, inspired by the Contrastive Language-Image Pre-training (CLIP) model. We leverage contrastive learning techniques to correlate different data modalities without the need for labeled data, overcoming limitations of traditional supervised machine learning methods in manufacturing contexts. Our proposed method demonstrates the ability to handle and learn encoders for five distinct modalities: visual imagery, audio signals, laser position (x and y coordinates), and laser power measurements. By compressing these high-dimensional datasets into low-dimensional representational spaces, our approach facilitates downstream tasks such as process control, anomaly detection, and quality assurance. The unsupervised nature of our method makes it broadly applicable across various manufacturing domains, where large volumes of unlabeled sensor data are common. We evaluate the effectiveness of our approach through a series of experiments, demonstrating its potential to enhance process monitoring capabilities in advanced manufacturing systems. This research contributes to the field of smart manufacturing by providing a flexible, scalable framework for multimodal data fusion that can adapt to diverse manufacturing environments and sensor configurations. The proposed method paves the way for more robust, data-driven decision-making in complex manufacturing processes.

Contrastive Learning↗
DOE OSTI2021

A rigorous physics-based enhanced parameter estimation (EPE) methodology for calibration of building energy simulations

Buildings rarely perform as designed/simulated and there are numerous tangible benefits if this gap is reconciled. A new scientifically rigorous yet pragmatic methodology for calibrating building energy simulations - called Enhanced Parameter Estimation (EPE) - is proposed that allows physically relevant parameter estimation rather than a blind force-fit to energy use data. Starting with a rapidly created simulation model, calibration is performed in two stages: (a) building shell calibration with the HVAC system replaced by an ideal system that meets the loads (b) HVAC system calibration with the building shell and all internal loads replaced by a box with only process loads. In the first stage, EPE identifies a small number of high-level heat flows in the energy balance, calculates them with specifically tailored individual driving functions, introduces physically significant parameters to best accomplish energy balance, and, estimates the parameters and their uncertainty bounds. Calibration is thus done with corrective heat flows without any arbitrary tuning of input parameters. Calibration accuracy is enhanced by machine learning of the residual errors. The EPE methodology is demonstrated by means of: a synthetic building and an actual 75,000 sq. ft. building in Pennsylvania. Future work needed for widespread application is discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1993

Optical beam forming techniques for phased array antennas

Three optical beam forming techniques are identified as applicable to large spaceborne phased array antennas. They are 1) the fiber replacement of conventional RF phased array distribution and control components, 2) spatial beam forming, and 3) optical beam splitting techniques. Two novel optical beam forming approaches, i.e., the spatial beam forming with a 'smart pixel' spatial light modulator (SLM) and the optical beam splitting approaches are conceived with integrated quasi-optical components. Also presented are the transmit and receive array architectures with the new SLM.

Wu, Te-Kao↗
DOE OSTI2022

Protoplast-Based Transient Expression and Gene Editing in Shrub Willow ( Salix purpurea L .)

Shrub willows (Salix section Vetrix) are grown as a bioenergy crop in multiple countries and as ornamentals across the northern hemisphere. To facilitate the breeding and genetic advancement of shrub willow, there is a strong interest in the characterization and functional validation of genes involved in plant growth and biomass production. While protocols for shoot regeneration in tissue culture and production of stably transformed lines have greatly advanced this research in the closely related genus Populus, a lack of efficient methods for regeneration and transformation has stymied similar advancements in willow functional genomics. Moreover, transient expression assays in willow have been limited to callus tissue and hairy root systems. Here we report an efficient method for protoplast isolation from S. purpurea leaf tissue, along with transient overexpression and CRISPR-Cas9 mediated mutations. This is the first such report of transient gene expression in Salix protoplasts as well as the first application of CRISPR technology in this genus. These new capabilities pave the way for future functional genomics studies in this important bioenergy and ornamental crop.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Dynamic Tracking of NiFe Smart Catalysts using In Situ X-Ray Absorption Spectroscopy for the Dry Methane Reforming Reaction

The exsolution of nanoparticles from perovskite precursors has been explored as a route to synthesize catalysts with sinter or coke resistance. The characteristics of these exsolved nanoparticles are highly dynamic depending on the redox nature of the environment to which they are subjected. To develop their properties for thermo- and electrocatalytic applications, it is necessary to track the states and behavior of exsolved catalysts with in situ and ex situ characterization. In this study, we conduct in situ X-ray absorption spectroscopy (XAS) along with ex situ scanning transmission electron microscopy high-angle annular dark-field (STEM-HAADF) and energy-dispersive X-ray spectroscopy analysis of the parent perovskite oxide precursor, LaFe 0.8 Ni 0.2 O 3 , as its structure forms bimetallic NiFe nanoparticles and evolves in oxidative, reductive, and dry methane reforming environments. We develop a theory that NiFe exsolution is a function of the reduction potential where LaFe 0.8 Ni 0.2 O 3 transforms to NiFe alloy supported on LaO x -LaFeO x . The Ni starts to exsolve at 268 °C, while most Fe exsolves at 700 °C. During dry methane reforming conditions, most of the Fe is oxidized by CO 2 during the reaction and re-enters the perovskite as LaFeO 3 , while Ni remains on the surface as nanoparticles in the metallic state. During the oxidative regeneration phase, most of the Fe re-enters the bulk perovskite phase, while Ni is partially regenerated with a small percentage oxidized to large NiO nanoparticles. Finally, this study sheds light on the exsolution and regeneration of bimetallic alloy nanoparticles and the influence of the reaction conditions on their catalyst performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe)

Recent proliferation of distributed energy sources in distribution or sub-transmission systems necessitates close monitoring of these three-phase power grids which typically operate under unbalanced loading conditions. Unlike the transmission systems where the network equations are commonly based on the positive sequence component models, a detailed three phase model will have to be used in implementing network applications for these systems. In the specific case of the state estimator, where measurement and parameter errors may bias the solution, bad data and parameter error detection algorithms should also be incorporated. Implementing the state estimator and error detection algorithms for three-phase systems impose additional computational burden and modifications to the state estimation code. This paper proposes a practical solution to avoid these issues by using synchronized phasor measurements and modal decoupling. The previously developed parameter error detection algorithm based on the normalized Lagrange multipliers (NLM) test is applied to the measurements independently in each mode in parallel, not only saving CPU time but also avoiding new code development for a three-phase estimator. Different parameter error scenarios are created and tested to verify the effectiveness of the proposed error detection approach.

Khalili, Ramtin↗
DOE OSTI2020

The good, the bad, and the ugly: Data-driven load profile discord identification in a large building portfolio

Reducing the overall energy consumption and associated greenhouse gas emissions in the building sector is essential for meeting our future sustainability goals. Recently, smart energy metering facilities have been deployed to enable monitoring of energy consumption data with hourly or subhourly temporal resolution. This unprecedented data collection has created various opportunities for advanced data analytics involving load profiles (e.g., building energy benchmarking programs, building-to-grid integration, and calibration of urban-scale energy models). These applications often need preprocessing steps to detect daily load profile discords, such as: 1) outliers due to system malfunctions (the bad) and 2) irregular energy consumption patterns, such as those resulting from holidays (the ugly) compared to normal consumption patterns (the good). However, current preprocessing methods predominantly focus on filtering using statistical threshold values, which fail to capture the contextual discords of daily profiles. In addition, discord detection algorithms in building research are often aimed at finding individual building-level discords, which are not suitable at a large scale. Thus, here, we develop a method for automated load profile discord identification (ALDI) in a large portfolio of buildings (more than 100 buildings). Specifically, ALDI 1) uses the matrix profile (MP) method to quantify the similarities of daily subsequences in time series meter data, 2) compares daily MP values with typical-day MP distributions using the Kolmogorov-Smirnov test, and 3) identifies daily load profile discords in a large building portfolio. We evaluate ALDI using the metering data of both an academic campus and a residential neighborhood. Our results demonstrate that ALDI efficiently discovers measurement errors by system malfunctions and low energy consumption days in the academic campus portfolio, and it detects unique load shape patterns likely driven by occupant behavior and extreme weather conditions in the residential neighborhood.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1988

Systems integration for the Kennedy Space Center (KSC) Robotics Applications Development Laboratory (RADL)

A laboratory for developing robotics technology for hazardous and repetitive Shuttle and payload processing activities is discussed. An overview of the computer hardware and software responsible for integrating the laboratory systems is given. The center's anthropomorphic robot is placed on a track allowing it to be moved to different stations. Various aspects of the laboratory equipment are described, including industrial robot arm control, smart systems integration, the supervisory computer, programmable process controller, real-time tracking controller, image processing hardware, and control display graphics. Topics of research include: automated loading and unloading of hypergolics for space vehicles and payloads; the use of mobile robotics for security, fire fighting, and hazardous spill operations; nondestructive testing for SRB joint and seal verification; Shuttle Orbiter radiator damage inspection; and Orbiter contour measurements. The possibility of expanding the laboratory in the future is examined.

Davis, V. Leon↗
DOE OSTI2023

Hydropower Cybersecurity Value-at-Risk Framework

Hydropower remains one of the strongest forms of renewable energy generation methods. It is crucial to address the increasing risks associated with the rapid digitization. The push towards decarbonization also factors in the need to ensure security and resilience for grid-connected renewable energy resources. This report summarizes the U.S. Department of Energy's Water Power Technologies Office's effort to develop a cybersecurity valuation methodology that assists hydropower stakeholders in assessing risks associated with plan operations and gathers valuation guidance through a web-based application. The Hydropower Cybersecurity Value-at-Risk Framework delivers a platform for industry members to perform self-assessments and make informed decisions on their cybersecurity investments.

13 HYDRO ENERGY↗
NASA NTRS2017

Lighting Automation - Flying an Earthlike Habitat

Currently, spacecraft lighting systems are not demonstrating innovations in automation due to perceived costs in designing circuitry for the communication and automation of lights. The majority of spacecraft lighting systems employ lamps or zone specific manual switches and dimmers. This type of 'hardwired' solution does not easily convert to automation. With advances in solid state lighting, the potential to enhance a spacecraft habitat is lost if the communication and automation problem is not tackled. If we are to build long duration environments, which provide earth-like habitats, minimize crew time, and optimize spacecraft power reserves, innovation in lighting automation is a must. This project researched the use of the DMX512 communication protocol originally developed for high channel count lighting systems. DMX512 is an internationally governed, industry-accepted, lighting communication protocol with wide industry support. The lighting industry markets a wealth of hardware and software that utilizes DMX512, and there may be incentive to space certify the system. Our goal in this research is to enable the development of automated spacecraft habitats for long duration missions. To transform how spacecraft lighting environments are automated, our project conducted a variety of tests to determine a potential scope of capability. We investigated utilization and application of an industry accepted lighting control protocol, DMX512 by showcasing how the lighting system could help conserve power, assist with lighting countermeasures, and utilize spatial body tracking. We hope evaluation and the demonstrations we built will inspire other NASA engineers, architects and researchers to consider employing DMX512 "smart lighting" capabilities into their system architecture. By using DMX512 we will prove the 'wheel' does not need to be reinvented in terms of smart lighting and future spacecraft can use a standard lighting protocol to produce an effective, optimized and potentially earthlike habitat.

Clark, Tori A.↗
NASA NTRS2017

Lighting Automation Flying an Earthlike Habitat

Currently, spacecraft lighting systems are not demonstrating innovations in automation due to perceived costs in designing circuitry for the communication and automation of lights. The majority of spacecraft lighting systems employ lamps or zone specific manual switches and dimmers. This type of 'hardwired' solution does not easily convert to automation. With advances in solid state lighting, the potential to enhance a spacecraft habitat is lost if the communication and automation problem is not tackled. If we are to build long duration environments, which provide earth-like habitats, minimize crew time, and optimize spacecraft power reserves, innovation in lighting automation is a must. This project researched the use of the DMX512 communication protocol originally developed for high channel count lighting systems. DMX512 is an internationally governed, industry-accepted, lighting communication protocol with wide industry support. The lighting industry markets a wealth of hardware and software that utilizes DMX512, and there may be incentive to space certify the system. Our goal in this research is to enable the development of automated spacecraft habitats for long duration missions. To transform how spacecraft lighting environments are automated, our project conducted a variety of tests to determine a potential scope of capability. We investigated utilization and application of an industry accepted lighting control protocol, DMX512 by showcasing how the lighting system could help conserve power, assist with lighting countermeasures, and utilize spatial body tracking. We hope evaluation and the demonstrations we built will inspire other NASA engineers, architects and researchers to consider employing DMX512 "smart lighting" capabilities into their system architecture. By using DMX512 we will prove the 'wheel' does not need to be reinvented in terms of smart lighting and future spacecraft can use a standard lighting protocol to produce an effective, optimized and potentially earthlike habitat.

Clark, Toni A.↗
DOE OSTI2021

Chapter 6 - Polymer and composites additive manufacturing: material extrusion processes

This chapter focuses on material extrusion additive manufacturing (AM) processes for polymers and composite materials. Different extrusion AM platforms, along with their operating mechanism concepts, processing capabilities, and limitations, are discussed here. This chapter also covers state-of-the-art developments in new areas such as hybrid systems, integrated systems, and automation, which facilitate the integration of extrusion-based AM processes into smart manufacturing or Industry 4.0. Following this, a comprehensive discussion on materials development, criteria for successful printing of different materials (thermoplastics, thermosets, and their composites), key factors influencing printing, and material-related challenges in extrusion AM is presented. Finally, a brief overview of current and future potential applications of material extrusion AM technology is provided.

Kishore, Vidya↗
DOE OSTI2023

Ab initio study of tungsten-based alloys under fusion power-plant conditions

Tungsten (W) is considered a leading candidate for structural and functional materials in future fusion energy devices. The most attractive properties of tungsten for magnetic and inertial fusion energy reactors are its high melting point, high thermal conductivity, low sputtering yield, and low long-term disposal radioactive footprint. However, tungsten also presents a very low fracture toughness, primarily associated with intergranular failure and bulk plasticity, limiting its applications. In recent years, several families of tungsten-based alloys have been explored to overcome the aforementioned limitations of pure tungsten. These include tungsten-based high-entropy alloys (W-HEAs) and tungsten-based Self-passivating Metal Alloys with Reduced Thermo-oxidation or “SMART alloys” (W-SAs). Given their proximity to the plasma, it is crucial to understand how the exposure of these candidate plasma-facing materials (PFMs) to the neutron fluxes expected in fusion reactors impacts their material behavior over time. In this work, we present a computational approach that combines inventory codes and first-principles DFT electronic structure calculations to understand the behavior of transmuting tungsten-based PFMs. In particular, we calculate the changes in the chemical composition, production uncertainties, the elastic and ductility properties, and the density of states for five tungsten-based PFMs when exposed to EU-DEMO fusion first wall conditions for ten years.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

High Precision, High Frequency Printed Antennas

An emerging trend in advanced manufacturing is printed electronics and sensors. The ability to print customized electronics and sensors integrated into functional packages is a growing need within a variety of growing markets such as smart manufacturing, internet of things (IoT), and the small satellite industry. Both Oak Ridge National Laboratory (ORNL) and the MITRE Corporation have seedling research efforts evaluating the potential for future printed electronic systems. High frequency, wide-bandwidth phased array antennas (i.e. >45 GHz) open the door to new applications. However, such sensors require currently prohibitively small feature sizes for commercial 3D printing technologies along with increasing challenges with connecting the driving electronics to such features. An additional finding with related advanced manufacturing challenges is the rapid production of 3D additive connectors for integration with commercial printed circuit boards (PCBs), primarily for advanced in-circuit inspection techniques. This work is developing additive manufacturing processes for producing connected and conductive fine scale 3D features. The primary focus was on aerosol-jet printing (AJP), which has a small minimum resolution (<50 µm) but is traditionally printed flat with small height/width aspect ratios <<1, and developing controls to enable fully 3D, high aspect ratio, and unsupported features. In Phase 1 of this effort, baselines of process performance were characterized, and test coupons produced for both ultra-high frequency antennas and microstructures to support reverse engineering of PCBs. In Phase 2, these efforts will be extended for system demonstration of ultra-high frequency antenna arrays, as well as reverse engineering circuitry for dense PCBs.

42 ENGINEERING↗
NASA NTRS1996

Layerwise Finite Elements for Smart Piezoceramic Composite Plates in Thermal Environments

Analytical formulations are presented which account for the coupled mechanical, electrical, and thermal response of piezoelectric composite laminates and plate structures. A layerwise theory is formulated with the inherent capability to explicitly model the active and sensory response of piezoelectric composite plates having arbitrary laminate configurations in thermal environments. Finite element equations are derived and implemented for a bilinear 4-noded plate element. Application cases demonstrate the capability to manage thermally induced bending and twisting deformations in symmetric and antisymmetric composite plates with piezoelectric actuators, and show the corresponding electrical response of distributed piezoelectric sensors. Finally, the resultant stresses in the thermal piezoelectric composite laminates are investigated.

Saravanos, Dimitris A.↗
NASA NTRS2010

Smart Sensors Assess Structural Health

NASA frequently inspects launch vehicles, fuel tanks, and other components for structural damage. To perform quick evaluation and monitoring, the Agency pursues the development of structural health monitoring systems. In 2001, Acellent Technologies Inc., of Sunnyvale, California, received Small Business Innovation Research (SBIR) funding from Marshall Space Flight Center to develop a hybrid Stanford Multi-Actuator Receiver Transduction (SMART) Layer for aerospace vehicles and structures. As a result, Acellent expanded the technology's capability and now sells it to aerospace and automotive companies; construction, energy, and utility companies; and the defense, space, transportation, and energy industries for structural condition monitoring, damage detection, crack growth monitoring, and other applications.

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