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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

The role of machine learning in scientific workflows

Machine learning (ML) is being applied in a number of everyday contexts from image recognition, to natural language processing, to autonomous vehicles, to product recommendation. In the science realm, ML is being used for medical diagnosis, new materials development, smart agriculture, DNA classification, and many others. In this article, we describe the opportunities of using ML in the area of scientific workflow management. Scientific workflows are key to today’s computational science, enabling the definition and execution of complex applications in heterogeneous and often distributed environments. We describe the challenges of composing and executing scientific workflows and identify opportunities for applying ML techniques to meet these challenges by enhancing the current workflow management system capabilities. We foresee that as the ML field progresses, the automation provided by workflow management systems will greatly increase and result in significant improvements in scientific productivity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Intelligent Partitioning based Fully Parallel AC Security-Constrained Optimal Power Flow

Today’s power grid is becoming more diverse and integrated with high-level distributed energy resources and smart control technologies that is creating a new set of grid management challenges in terms of large-scale, nonlinear, and non-convex problem modeling, complex and time-consuming computation, as well as difficult uncertainty handling. This project focused on solving a challenging multi-period security-constrained generation scheduling problem, which is of great importance for maximizing the social welfare of real-time dispatch, day-ahead market, as well as weekly planning of power systems. Our developed software explored parallel optimization algorithms for complex and realistic power system models, and develop fast, efficient, and robust grid optimization solutions on the high-performance computing platform that will enable increased grid economics, flexibility, resilience, as well as energy security in the United States.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2015

Damage Detection and Verification System (DDVS) for In-Situ Health Monitoring

Project presentation for Game Changing Program Smart Book Release. Detection and Verification System (DDVS) expands the Flat Surface Damage Detection System (FSDDS) sensory panels damage detection capabilities and includes an autonomous inspection capability utilizing cameras and dynamic computer vision algorithms to verify system health. Objectives of this formulation task are to establish the concept of operations, formulate the system requirements for a potential ISS flight experiment, and develop a preliminary design of an autonomous inspection capability system that will be demonstrated as a proof-of-concept ground based damage detection and inspection system.

Damage detection↗
NASA NTRSDate not supplied

An Autonomous sUAS Operating in UTM TCL4+ and STEReO Fire Scenario

This study presents a sUAS payload point design that enables autonomous BVLOS flightin UTM TCL4+ urban environments and STEReO fire responses. The payload components include an onboard computer, 360 deg LIDAR, range finder altimeter, downward-facing monocular camera, forward-facing thermal and visible light dual camera, vehicle-to-vehicle radio modem, and Li-ion smart battery. The components are mounted on an enclosed structural frame that was designed in-house. Placing the autonomy components onboard leverages the advantages of sUAS over manned aircraft such as low-cost, quick response time, and increased scalability. Autonomous capabilities include object and fire detection, V2V communication, embedded processing, and SLAM. Data processing is conducted on-board the aircraft to eliminate the dependency on a ground station downlink. The payload is evaluated in both software simulation as well as flight tests.

Autonomous UAS↗
NASA NTRSDate not supplied

Onboard Autonomous Trajectory Planning for Mars Power Descent

In recent years, there has been an increasing interest in space-qualified processors such as multi-core central processing units and graphics processing units that can withstand the adverse effects of space radiation. These processors can allow parallel programming to perform tasks that typically demand high computational power. One can study guidance schemes that can take advantage of these currently developing processors and provide more robust guidance. Software for Multi-model Autonomous Real-time Trajectories (SMART) guidance can identify robust trajectories by running an onboard Monte Carlo analysis. SMART guidance can take advantage of knowledge updates obtained from the onboard sensors, allowing it to consider the off-nominal cases that it would not typically encounter during the offline trajectory analysis. This work uses the SMART guidance for the powered divert at Mars simulation in Program to Optimize and Simulated Trajectories- II.

Pardha Sai Chadalavada↗
NASA NTRSDate not supplied

Onboard Autonomous Trajectory Planning for Mars Power Descent

In recent years, there has been an increasing interest in space-qualified processors such as multi-core central processing units and graphics processing units that can withstand the adverse effects of space radiation. These processors can allow parallel programming to perform tasks that typically demand high computational power. One can study guidance schemes that can take advantage of these currently developing processors and provide more robust guidance. Software for Multi-model Autonomous Real-time Trajectories (SMART) guidance can identify robust trajectories by running an onboard Monte Carlo analysis. SMART guidance can take advantage of knowledge updates obtained from the onboard sensors, allowing it to consider the off-nominal cases that it would not typically encounter during the offline trajectory analysis. This work uses the SMART guidance for the powered divert at Mars simulation in Program to Optimize and Simulated Trajectories- II.

Autonomous Planning↗
DOE OSTI2020

Interstate-24 MOTION: Closing the Loop on Smart Mobility

We introduce the I-24 Mobility Technology Interstate Observation Network (MOTION), a transportation cyber-physical systems testbed under development in Tennessee. It consists of a six-mile freeway segment instrumented with 400 4K resolution cameras, processed by a real-time compute system to enable continuous performance monitoring of freeway traffic. The testbed is being developed to support next generation connected and autonomous vehicle technologies and advanced traffic management. When complete, the testbed will be the longest continuously observed freeway segment in the world. This article introduces the testbed, discusses the core design choices, and outlines the preliminary work conducted to support the design.

Gloudemans, Derek↗
DOE OSTI2019

City-Wide Eco-Routing Navigation Considering Vehicular Communication Impacts

Intelligent Transportation Systems (ITSs) utilize Vehicular Ad-hoc Networks (VANETs) to collect, disseminate, and share data with the Traffic Management Center (TMC) and different actuators. Consequently, packet drop and delay in VANETs can significantly impact ITS performance. Feedback-based eco-routing (FB-ECO) is a promising ITS technology, which is expected to reduce vehicle fuel/energy consumption and pollutant emissions by routing drivers through the most environmentally friendly routes. To compute these routes, the FB-ECO utilizes VANET communication to update link costs in real-time, based on the experiences of other vehicles in the system. In this paper, we study the impact of vehicular communication on FB-ECO navigation performance in a large-scale real network with realistic calibrated traffic demand data. We conduct this study at different market penetration rates and different congestion levels. We start by conducting a sensitivity analysis of the market penetration rate on the FB-ECO system performance, and its network-wide impacts considering ideal communication. Subsequently, we study the impact of the communication network on system performance for different market penetration levels, considering the communication system. The results demonstrate that, for market penetration levels less than 30%, the eco-routing system performs adequately in both the ideal and realistic communication scenarios. It also shows that, for realistic communication, increasing the market penetration rate results in a network-wide degradation of the system performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1989

Remote-Manipulator Hand With Data-Processing Ability

A "smart" hand for remote manipulator not only senses forces acting on it and detects presence of objects in immediate vicinity but also processes sensory data and controls its gripping claws. Hand reduces computational load on control computer of manipulator system. Includes wrist body and two opposing jaws with sets of claws that mesh with each other. Jaws of hand open as wide as 8.8 cm. Brushless dc motor operates claws through bevel-gear drive train and pair of ball screws. Maximum grip force 540 N, or about 120 lb.

Bejczy, Antal K.↗
NASA NTRS2013

Damage Detection Response Characteristics of Open Circuit Resonant (SansEC) Sensors

The capability to assess the current or future state of the health of an aircraft to improve safety, availability, and reliability while reducing maintenance costs has been a continuous goal for decades. Many companies, commercial entities, and academic institutions have become interested in Integrated Vehicle Health Management (IVHM) and a growing effort of research into "smart" vehicle sensing systems has emerged. Methods to detect damage to aircraft materials and structures have historically relied on visual inspection during pre-flight or post-flight operations by flight and ground crews. More quantitative non-destructive investigations with various instruments and sensors have traditionally been performed when the aircraft is out of operational service during major scheduled maintenance. Through the use of reliable sensors coupled with data monitoring, data mining, and data analysis techniques, the health state of a vehicle can be detected in-situ. NASA Langley Research Center (LaRC) is developing a composite aircraft skin damage detection method and system based on open circuit SansEC (Sans Electric Connection) sensor technology. Composite materials are increasingly used in modern aircraft for reducing weight, improving fuel efficiency, and enhancing the overall design, performance, and manufacturability of airborne vehicles. Materials such as fiberglass reinforced composites (FRC) and carbon-fiber-reinforced polymers (CFRP) are being used to great advantage in airframes, wings, engine nacelles, turbine blades, fairings, fuselage structures, empennage structures, control surfaces and aircraft skins. SansEC sensor technology is a new technical framework for designing, powering, and interrogating sensors to detect various types of damage in composite materials. The source cause of the in-service damage (lightning strike, impact damage, material fatigue, etc.) to the aircraft composite is not relevant. The sensor will detect damage independent of the cause. Damage in composite material is generally associated with a localized change in material permittivity and/or conductivity. These changes are sensed using SansEC. The unique electrical signatures (amplitude, frequency, bandwidth, and phase) are used for damage detection and diagnosis. An operational system and method would incorporate a SansEC sensor array on select areas of the aircraft exterior surfaces to form a "Smart skin" sensing surface. In this paper a new method and system for aircraft in-situ damage detection and diagnosis is presented. Experimental test results on seeded fault damage coupons and computational modeling simulation results are presented. NASA LaRC has demonstrated with individual sensors that SansEC sensors can be effectively used for in-situ composite damage detection of delamination, voids, fractures, and rips. Keywords: Damage Detection, Composites, Integrated Vehicle Health Monitoring (IVHM), Aviation Safety, SansEC Sensors

Dudley, Kenneth L.↗
DOE OSTI2026

Designing resilient IoT and Edge Computing with federated tinyML

The rapid growth of the Internet of Things (IoT) and Edge Computing (EC) has brought significant conveniences to modern society but has also greatly expanded the cyber attack surfaces, particularly as these technologies are being increasingly integrated into critical systems such as power grids, healthcare, and smart homes. Here, to improve IoT/EC’s cybersecurity posture, we leveraged Artificial Intelligence (AI) and Machine Learning (ML) by employing tinyML to monitor voluminous IoT data for cyber threats while addressing devices’ resource constraints, and utilizing Federated Learning (FL) to share local detection knowledge across the system while preserving privacy. Building on our three-layer architecture combining tinyML and FL to enhance autonomous cyber attack detection, this paper demonstrated that the architecture improves detection accuracy, reduces resource consumption, and enables lightweight, secure IoT device monitoring. These results were validated using the public N-BaIoT dataset as well as real IoT network traffic data collected under multiple attack scenarios from our testbeds. Additionally, we introduced an enhanced FL methodology with a novel preprocessing stage, including federated feature selection and global preprocessor construction, to address IoT/EC data heterogeneity. We developed a physical IoT testbed for attack simulations and data collection, implemented a tinyML-powered detector for realistic model validation, and also built a virtual testbed for scalable evaluations of FL models across diverse network environments.

Cognitive cyber↗
DOE OSTI2022

Quantum computing in power systems

Electric power systems provide the backbone of modern industrial societies. Enabling scalable grid analytics is the keystone to successfully operating large transmission and distribution systems. However, today's power systems are suffering from ever-increasing computational burdens in sustaining the expanding communities and deep integration of renewable energy resources, as well as managing huge volumes of data accordingly. These unprecedented challenges call for transformative analytics to support the resilient operations of power systems. Recently, the explosive growth of quantum computing techniques has ignited new hopes of revolutionizing power system computations. Quantum computing harnesses quantum mechanisms to solve traditionally intractable computational problems, which may lead to ultra-scalable and efficient power grid analytics. This paper reviews the newly emerging application of quantum computing techniques in power systems. We present a comprehensive overview of existing quantum-engineered power analytics from different operation perspectives, including static analysis, transient analysis, stochastic analysis, optimization, stability, and control. We thoroughly discuss the related quantum algorithms, their benefits and limitations, hardware implementations, and recommended practices. We also review the quantum networking techniques to ensure secure communication of power systems in the quantum era. Finally, we discuss challenges and future research directions. This paper will hopefully stimulate increasing attention to the development of quantum-engineered smart grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

An automated integrated web-based smart tool for open stope design

The Stability Graph is a widely used tool for the design of open stopes in underground mining. Many users of the Stability Graph still apply this design method manually. Although the manual approach has benefits, using multiple graphs and stability number computation charts for each stope surface is time-consuming, even for the experienced mining engineer. Current practice in the use of the method also limits data sharing. This paper presents a StopeSoft web-based tool for open stope stability prediction that is developed on the basis of the Stability Graph method and is available at openstope.com. StopeSoft incorporates flexibility in terms of Stability Graph options and incorporates additional critical factors often overlooked. As a web-based tool, StopeSoft encourages and makes data sharing possible globally, focused on expanding the database and improving the current limitations of the Stability Graph to provide practical, reliable solutions for mining engineers, consultants, and academics. The StopeSoft automated process facilitates the process of open stope stability prediction, saving time and minimizing potential human errors. Statistical treatment of the data accounts for the variability of input parameters to emphasize the probabilistic nature of the Stability Graph method. The probabilistic interpretation of the stability states of stope surfaces eliminates the false feeling of absolute stope performance based on its location on the Stability Graph , as implied by the deterministic approach.

58 GEOSCIENCES↗
DOE OSTI2019

Optical absorption induced by small polaron formation in transition metal oxides: The case of Co 3 O 4

Small polarons (SPs) are known to exist in most important transition metal oxides; however, the nature of small polaron formation remains enigmatic, and a fundamental understanding of how SPs impact the intrinsic electronic structure and optical properties of these materials is largely lacking. In this work, we employ first-principles calculations to investigate SP formation in Co 3 O 4 , a highly promising material for a wide range of emerging energy applications, and we resolve the conflicting findings that have been reported on the electronic structure of the system. We confirm that the intrinsic band gap of Co 3 O 4 is 1.6 eV, and we show that the formation of small hole polarons significantly influences the optical absorption spectra, leading to a 0.8 eV transition that is often misinterpreted as the band edge that defines the fundamental gap. In addition, we discuss how uniaxial strain can be utilized to probe the Jahn-Teller distortion of SP states and, in turn, effect their optical transitions. Beyond Co 3 O 4 , our study suggests a general roadmap for establishing a first-principles computational approach that can simultaneously achieve an accurate description of SP states, electronic band structure, and optical transitions of polaronic magnetic oxides.

36 MATERIALS SCIENCE↗
DOE OSTI2025

GreenThrift: Optimizing Carbon and Cost for Flexible Residential Loads

Reducing buildings’ carbon emissions is an important sustainability challenge. While scheduling flexible building loads has been previously used for a variety of grid and energy optimizations, carbon footprint reduction using such flexible loads poses new challenges since such methods need to balance both energy and carbon costs while also reducing user inconvenience from delaying such loads. This paper highlights the potential conflict between electricity prices and carbon emissions and the resulting trade-offs in carbon-aware and cost-aware load scheduling. To address this trade-off, we propose GreenThrift, a home automation system that leverages the scheduling capabilities of smart appliances and knowledge of future carbon intensity and cost to reduce both the carbon emissions and costs of flexible energy loads. At the heart of GreenThrift is an optimization technique that automatically computes schedules based on user configurations and preferences. We evaluate the effectiveness of GreenThrift using real-world carbon intensity data, electricity prices, and load traces from multiple locations and across different scenarios and objectives. Our results show that GreenThrift can replicate the offline optimal and retains 97% of the savings when optimizing the carbon emissions. Moreover, we show how GreenThrift can balance the conflict between carbon and cost and retain 95.3% and 85.5% of the potential carbon and cost savings, respectively.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2003

Structural Mechanics and Dynamics Branch

The 2002 annual report of the Structural Mechanics and Dynamics Branch reflects the majority of the work performed by the branch staff during the 2002 calendar year. Its purpose is to give a brief review of the branch s technical accomplishments. The Structural Mechanics and Dynamics Branch develops innovative computational tools, benchmark experimental data, and solutions to long-term barrier problems in the areas of propulsion aeroelasticity, active and passive damping, engine vibration control, rotor dynamics, magnetic suspension, structural mechanics, probabilistics, smart structures, engine system dynamics, and engine containment. Furthermore, the branch is developing a compact, nonpolluting, bearingless electric machine with electric power supplied by fuel cells for future "more electric" aircraft. An ultra-high-power-density machine that can generate projected power densities of 50 hp/lb or more, in comparison to conventional electric machines, which generate usually 0.2 hp/lb, is under development for application to electric drives for propulsive fans or propellers. In the future, propulsion and power systems will need to be lighter, to operate at higher temperatures, and to be more reliable in order to achieve higher performance and economic viability. The Structural Mechanics and Dynamics Branch is working to achieve these complex, challenging goals.

Stefko, George↗