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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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118 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Spinoff 2013

Topics covered include: Innovative Software Tools Measure Behavioral Alertness; Miniaturized, Portable Sensors Monitor Metabolic Health; Patient Simulators Train Emergency Caregivers; Solar Refrigerators Store Life-Saving Vaccines; Monitors Enable Medication Management in Patients' Homes; Handheld Diagnostic Device Delivers Quick Medical Readings; Experiments Result in Safer, Spin-Resistant Aircraft; Interfaces Visualize Data for Airline Safety, Efficiency; Data Mining Tools Make Flights Safer, More Efficient; NASA Standards Inform Comfortable Car Seats; Heat Shield Paves the Way for Commercial Space; Air Systems Provide Life Support to Miners; Coatings Preserve Metal, Stone, Tile, and Concrete; Robots Spur Software That Lends a Hand; Cloud-Based Data Sharing Connects Emergency Managers; Catalytic Converters Maintain Air Quality in Mines; NASA-Enhanced Water Bottles Filter Water on the Go; Brainwave Monitoring Software Improves Distracted Minds; Thermal Materials Protect Priceless, Personal Keepsakes; Home Air Purifiers Eradicate Harmful Pathogens; Thermal Materials Drive Professional Apparel Line; Radiant Barriers Save Energy in Buildings; Open Source Initiative Powers Real-Time Data Streams; Shuttle Engine Designs Revolutionize Solar Power; Procedure-Authoring Tool Improves Safety on Oil Rigs; Satellite Data Aid Monitoring of Nation's Forests; Mars Technologies Spawn Durable Wind Turbines; Programs Visualize Earth and Space for Interactive Education; Processor Units Reduce Satellite Construction Costs; Software Accelerates Computing Time for Complex Math; Simulation Tools Prevent Signal Interference on Spacecraft; Software Simplifies the Sharing of Numerical Models; Virtual Machine Language Controls Remote Devices; Micro-Accelerometers Monitor Equipment Health; Reactors Save Energy, Costs for Hydrogen Production; Cameras Monitor Spacecraft Integrity to Prevent Failures; Testing Devices Garner Data on Insulation Performance; Smart Sensors Gather Information for Machine Diagnostics; Oxygen Sensors Monitor Bioreactors and Ensure Health and Safety; Vision Algorithms Catch Defects in Screen Displays; and Deformable Mirrors Capture Exoplanet Data, Reflect Lasers.

Source record↗
DOE OSTI2022

Tunable White Light for Elders (TWLITE): A Protocol Demonstrating Feasibility and Acceptability for Deployment, Remote Data Collection, and Analysis of a Home-Based Lighting Intervention in Older Adults

Sleep disturbances are common in older adults and may contribute to disease progression in certain populations (e.g., Alzheimer’s disease). Light therapy is a simple and cost-effective intervention to improve sleep. Primary barriers to light therapy are: (1) poor acceptability of the use of devices, and (2) inflexibility of current devices to deliver beyond a fixed light spectrum and throughout the entirety of the day. However, dynamic, tunable lighting integrated into the native home lighting system can potentially overcome these limitations. Herein, we describe our protocol to implement a whole-home tunable lighting system installed throughout the homes of healthy older adults already enrolled in an existing study with embedded home assessment platforms (Oregon Center for Aging & Technology—ORCATECH). Within ORCATECH, continuous data on room location, activity, sleep, and general health parameters are collected at a minute-to-minute resolution over years of participation. This single-arm longitudinal protocol collected participants’ light usage in addition to ORCATECH outcome measures over a several month period before and after light installation. The protocol was implemented with four subjects living in three ORCATECH homes. Technical/usability challenges and feasibility/acceptability outcomes were explored. The successful implementation of our protocol supports the feasibility of implementing and integrating tunable whole-home lighting systems into an automated home-based assessment platform for continuous data collection of outcome variables, including long-term sleep measures. Challenges and iterative approaches are discussed. This protocol will inform the implementation of future clinical intervention trials using light therapy in patients at risk for developing Alzheimer’s disease and related conditions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Scalable Unit Commitment with Security Constrained AC Power Flow via ADMM and Hybrid Modeling Strategies

This research introduces a more efficient way to optimize power grid operations, breaking the problem into manageable steps and using advanced mathematical techniques to speed up calculations. By incorporating smart heuristics, improved preprocessing, and contingency analysis, the approach allows operators to make better decisions faster. These innovations enhance our understanding of how to optimize energy generation, making it possible to anticipate failures before they happen, reduce system costs, and improve overall grid performance. Ultimately, this research helps bridge the gap between theoretical models and real-world applications, paving the way for a smarter, more resilient power grid. This research directly benefits the public by making electricity more affordable, reliable, and sustainable. By improving how power grids schedule and distribute electricity, the project helps energy providers reduce operational costs, which can lead to lower electricity prices for consumers. Additionally, the ability to predict and prevent power system failures enhances grid reliability, reducing the likelihood of blackouts that can disrupt homes, businesses, and critical infrastructure such as hospitals. From an environmental perspective, optimizing power generation reduces energy waste and lowers carbon emissions, contributing to cleaner air and a more sustainable energy system. Furthermore, with extreme weather events becoming more frequent, these advancements make the power grid more resilient, ensuring communities are better prepared for emergencies and natural disasters. By strengthening the nation's energy infrastructure, this research plays a crucial role in improving economic stability, public safety, and environmental sustainability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Physical, socio-psychological, and behavioural determinants of household energy consumption in the UK

Determining which attitudes and behaviours predict household energy consumption can help accelerate the low-carbon energy transition. Conventional approaches in this domain are limited, often relying on survey methods that produce data on individuals’ motivations and self-reported activities without pairing these with actual energy consumption records, which are particularly hard to collect for large, nationally representative samples. This challenge precludes the development of empirical evidence on which attitudes and behaviours influence patterns of energy consumption, thus limiting the extent to which these can inform energy interventions or conservation programs. This study demonstrates a novel methodology for estimating energy consumption in the absence of actual energy records by using a large, publicly available data set of energy consumption in the UK. We develop a predictive model using the Smart Energy Research Laboratory (SERL) data portal (with records from nearly 13,000 UK households) and then use this model to predict energy consumption (both electric and gas) for a sample of 1,000 UK householders for which we separately collect over 200 variables relating to climate change attitudes and practices. Our approach uses a set of over 50 independent variables that are shared between the data sets, allowing us to train a model on the SERL data and use it to analyse the relationship between energy consumption and the opinions, motivations, and daily practices of survey respondents. Results show that electricity consumption is influenced by a broader range of factors compared to gas. Household energy use is best explained by physical dwelling characteristics, socio-demographic variables, and certain behavioural and attitudinal measures. Notably, pro-environmental attitudes, frugality, and conscientiousness correlate with lower energy use, while income and consumerism are linked to higher consumption. We discuss how these findings can inform efforts to decarbonise home energy use in the UK.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Natural Gas Community of the Future (Final Report)

Nicor Gas, a subsidiary of Southern Company Gas and its parent company Southern Company, is developing the concept of the Carbon-neutral, Affordable, Resilient, and Equitable Community ("CARE Community") to address the challenges of accessibility and affordability of grid-interactive efficient buildings in historically disadvantaged communities. The CARE Community is a new construction net-zero energy and carbon neutral residential neighborhood consisting of 50 homes with electricity and natural gas services in South Suburban Chicago, built as low-income affordable housing. The National Renewable Energy Laboratory (NREL) is assisting Southern Company to explore how energy efficiency, renewable technologies, and the reliability and resilience of natural gas can be combined and optimized in an islandable energy system as part of a broader effort to understand the role natural gas plays in future communities integrated with renewable energy and improved energy efficiency. The CARE Community will demonstrate how energy efficiency, distributed energy resources (DERs), and advanced controls can be combined with existing natural gas infrastructure to serve historically disadvantaged communities in a cold climate with low energy cost for affordable housing programs and enhanced resilience to withstand extreme weather. Homes will be a part of an islandable energy system, integrating multiple DER technologies such as solar panels, natural gas fuel cells, reciprocating natural gas engines, and battery storage. The CARE Community will provide a replicable template that affordable housing developers and energy companies can adopt throughout the United States. In this report, we present the design and modeling of the community and potential approaches for integrating DERs. We analyze and discuss annual simulations under normal operating conditions and week-long simulations under electric power grid outage conditions.

03 NATURAL GAS↗
NASA NTRS2013

Surface Navigation Using Optimized Waypoints and Particle Swarm Optimization

The design priority for manned space exploration missions is almost always placed on human safety. Proposed manned surface exploration tasks (lunar, asteroid sample returns, Mars) have the possibility of astronauts traveling several kilometers away from a home base. Deviations from preplanned paths are expected while exploring. In a time-critical emergency situation, there is a need to develop an optimal home base return path. The return path may or may not be similar to the outbound path, and what defines optimal may change with, and even within, each mission. A novel path planning algorithm and prototype program was developed using biologically inspired particle swarm optimization (PSO) that generates an optimal path of traversal while avoiding obstacles. Applications include emergency path planning on lunar, Martian, and/or asteroid surfaces, generating multiple scenarios for outbound missions, Earth-based search and rescue, as well as human manual traversal and/or path integration into robotic control systems. The strategy allows for a changing environment, and can be re-tasked at will and run in real-time situations. Given a random extraterrestrial planetary or small body surface position, the goal was to find the fastest (or shortest) path to an arbitrary position such as a safe zone or geographic objective, subject to possibly varying constraints. The problem requires a workable solution 100% of the time, though it does not require the absolute theoretical optimum. Obstacles should be avoided, but if they cannot be, then the algorithm needs to be smart enough to recognize this and deal with it. With some modifications, it works with non-stationary error topologies as well.

Birge, Brian↗
NASA NTRS2023

Electronic Nose Development and Preliminary Human Breath Testing for Rapid, Non-Invasive COVID-19 Detection

We adapted an existing, spaceflight-proven, robust “electronic nose” (E-Nose) that uses an array of electrical resistivity-based nanosensors mimicking aspects of mammalian olfaction to conduct on-site, rapid screening for COVID-19 infection by measuring the pattern of sensor responses to volatile organic compounds (VOCs) in exhaled human breath. We built and tested multiple copies of a hand-held prototype E-Nose sensor system, composed of 64 chemically sensitive nanomaterial sensing elements tailored to COVID-19 VOC detection; data acquisition electronics; a smart tablet with software (App) for sensor control, data acquisition and display; and a sampling fixture to capture exhaled breath samples and deliver them to the sensor array inside the E-Nose. The sensing elements detect the combination of VOCs typical in breath at parts-per-billion (ppb) levels, with repeatability of 0.02% and reproducibility of 1.2%; the measurement electronics in the E-Nose provide measurement accuracy and signal-to-noise ratios comparable to benchtop instrumentation. Preliminary clinical testing at Stanford Medicine with 63 participants, their COVID-19-positive or COVID-19-negative status determined by concomitant RT-PCR, discriminated between these two categories of human breath with a 79% correct identification rate using “leave-one-out” training-and-analysis methods. Analyzing the E-Nose response in conjunction with body temperature and other non-invasive symptom screening using advanced machine learning methods, with a much larger database of responses from a wider swath of the population, is expected to provide more accurate on-the-spot answers. Additional clinical testing, design refinement, and a mass manufacturing approach are the main steps toward deploying this technology to rapidly screen for active infection in clinics and hospitals, public and commercial venues, or at home.

COVID-19↗
DOE OSTI2025

Data Quality Assessment of Optiwatt Vehicle Telematics Data

In October 2024, the Idaho National Laboratory (INL) received data from Optiwatt (Compass Global, Inc.) describing the driving and charging behavior of electric vehicle (EV) drivers. The data shared had been collected from approximately 10,000 vehicles and included vehicle specifications, driving information like odometer readings at the beginning and end of origin-destination pairs (i.e., trips with identification of home for trip start and end for Tesla vehicles), and charging information such as charging energy consumed per charge session and if the charge occurred at home. The vehicle data were provided from 9 EV makes and 18 EV models, with production years ranging from 2012–2024, but more than 9,500 of the vehicles were Tesla EVs. The data includes more than six million trips and more than three million charging events that occurred between June 2023 to Aug 2024 and collected from California and the Eastern United States. The purpose of this report is to review the quality of the data received from Optiwatt and the feedback INL received from Optiwatt after data concerns were shared with them.

33 - ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Statistical Estimation of EV Driver Charging Behavior and Influential Factors

INL received data collected via telematics from battery electric vehicles (BEVs), and these vehicles were owned by retail customers who had entered into a telematics user agreement. The goal of analyzing these data was to develop mathematical models to characterize how different sets of BEV drivers use charging infrastructure at home and away from home (i.e., public charging) and quantify how various factors influence BEV drivers’ decision to charge and use available infrastructure. The data used in this analysis are unique because they provide real world BEV driving and charging behavior at the individual driving and parking event level. In this study we seek to leverage this data to quantify BEV charging and driving metrics to help inform models that predict quantities like the specific times when loads are imposed on the electrical grid due to BEV charging. Most models that have been developed to predict electrical grid load due to BEV charging, use simulations of BEV driving events and rely on assumptions such as every vehicle charges every night. Using a statistical modelling framework, we seek to investigate BEV charging behavior and quantitatively assess these common assumptions of BEV charging behavior.

33 - ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Modeling and Analysis of a Heat Pump Clothes Dryer with Thermal Energy Storage

Clothes drying is an energy-intensive process that causes significant electricity consumption and carbon emissions in the US. Approximately 83% of Households in the US own a tumble clothes dryer at home and 80% of dryers are electrical resistance dryers with low energy efficiency. Heat pump technology makes it possible for highly efficient and clean drying. Additionally, the ventless design of heat pump clothes dryers (HPCD) provides more installation flexibility. HPCD involves three primary mediums: wet clothes, a closed air loop, and a refrigerant circuit. The evaporator is used to dehumidify the wet air and the condenser is used to re-heat the dry air. One of the critical technological barriers to HPCD market penetration is its long drying time, primarily due to the relatively low discharging temperature and the slow response during the warm-up period. In this study, the thermal energy storage (TES) technology is adopted to address this challenge by providing pre-heating of air prior to the condenser to increase the operating temperature of the process air. The heat pump will charge the phase change material (PCM) in the TES device with heating energy during clothes washing and the PCM will discharge the stored heat to facilitate air heating during clothes drying. To analyze the optimal design and potential for energy saving and drying time reduction, a mathematical model of the HPCD system was developed. The HPCD is a highly dynamic system with a coupled heat and mass transfer and heat pumping cycle. This paper provides solutions to simulate the transient behavior of the system while maintaining low computational cost. The modeling result indicates reduced energy consumption and drying time by integrating TES with HPCD, as compared to electrical resistance dryers. The study can provide significant insights into improving building flexibility with TES and smart appliances.

Liu, Xiaoli↗