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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Lehigh University Industrial Assessment Center (Final Technical Report for the Period 2016 to 2021)

This is the final technical report summarizing the activities Industrial Assessment Center at Lehigh University sponsored by the Department of Energy for the period September 1, 2016 till September 30, 2021. During this period, the Industrial Assessment Center at Lehigh University was successful in training numerous energy engineers of the future, and helped many manufacturing plants in New Jersey and Eastern Pennsylvania. The center and its activities helped save a great deal of energy, related fuel costs and along the way mitigated tons of CO2 emissions. The report covers many of the numerical details related to the center activities. The Industrial Center at Lehigh University is one of the most successful ones and this is made evident by the statistics included as part of this report and best center award bestowed upon the center.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Student Programs Office Overview [Slides]

The Student Programs further the Laboratory’s goal of developing and mentoring the next generation of scientific, technical, and professional staff by supporting 2,000+ interns at all levels (high school, undergraduate, graduate, and postgraduate) along with 2,000+ mentors and 70 division student liaisons. The activities include internship promotion and external engagement, intern identification and sourcing, training and orientation, professional and career development, social and community engagement, and compliance.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Efficient First-Order Algorithms for Large-Scale, Non-Smooth Maximum Entropy Models with Application to Wildfire Science

Maximum entropy (MaxEnt) models are a class of statistical models that use the maximum entropy principle to estimate probability distributions from data. Due to the size of modern data sets, MaxEnt models need efficient optimization algorithms to scale well for big data applications. State-of-the-art algorithms for MaxEnt models, however, were not originally designed to handle big data sets; these algorithms either rely on technical devices that may yield unreliable numerical results, scale poorly, or require smoothness assumptions that many practical MaxEnt models lack. In this paper, we present novel optimization algorithms that overcome the shortcomings of state-of-the-art algorithms for training large-scale, non-smooth MaxEnt models. Our proposed first-order algorithms leverage the Kullback–Leibler divergence to train large-scale and non-smooth MaxEnt models efficiently. For MaxEnt models with discrete probability distribution of n elements built from samples, each containing m features, the stepsize parameter estimation and iterations in our algorithms scale on the order of O(mn) operations and can be trivially parallelized. Moreover, the strong ℓ1 convexity of the Kullback–Leibler divergence allows for larger stepsize parameters, thereby speeding up the convergence rate of our algorithms. To illustrate the efficiency of our novel algorithms, we consider the problem of estimating probabilities of fire occurrences as a function of ecological features in the Western US MTBS-Interagency wildfire data set. Our numerical results show that our algorithms outperform the state of the art by one order of magnitude and yield results that agree with physical models of wildfire occurrence and previous statistical analyses of wildfire drivers.

Physics↗
DOE OSTI2024

Emerging Threat Information Sharing and Analysis Center (ET-ISAC)

We successfully achieved all the goals outlined in this grant, culminating in a comprehensive training program conducted across three locations and a regional remote exercise. The training sessions took place from May 28-30, 2024, followed by the regional exercise on June 5, 2024.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Elucidating Biological Energy Transduction from Ammonia (Final Technical Report)

This report describes the proposed goals and the key scientific results obtained on the study of biological ammonia oxidation as part of DOE grant DE-SC0013997. In addition, this report lists articles published with support from this grant, presentations given to disseminate results obtained with support from this grant, and a list of junior scientists trained with support from this grant.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Professional Development for Technical Managers [Slides] (Rev. 1)

LANL is changing rapidly and requires a leadership development program in order to support the growing and changing workforce. Provide analysis and recommendations for a leadership development program for engineering services within ALDFO: 1) Attrition and churn are up; 2) Younger workforce--loss of organizational knowledge; 3) LANL is geographically isolated; 4) Leadership training is infrequent and one-size-fits-all.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
NASA NTRS2004

Innovative Imagery System for Enhanced Habitability Onboard ISS: Desired Features and Possible Hardware Applications

With the advent of the ISS and the experience of Russian, European, and US crewmembers on Mir, the importance of the psychological element in long duration missions is increasingly recognized. An integrated imagery system or Magic Window System could enhance the habitability, performance, and productivity for long term stays in space. Because this is type of system is a new concept for space, functional and technical requirements need to be determined. As part of a three-year project, the functional and technical requirements for an Imagery System onboard the International Space Station (ISS) have been explored. Valuable information was gathered from a survey completed by participants that had been in analog environments (remote/isolated) such as Antarctica, Aquarius, ISS crewmember debriefs, and crew support meetings to identify key functions desired for an integrated Magic Window System. Exercise and medical care activities were identified as areas that could benefit from such a system. It was determined that for exercise, it was worth exploring the concept of displaying a dynamic screen that changes as the crewmember's speed changes while showing physiological measures in a combined display. In terms of enhancing the interfaces for medical care activities, the Magic Window System could show video clips along side procedures for just-in-time training scenarios through a heads-up display. In addition, the portability, usability, and reliability were stressed as important considerations for an integrated system of technologies or Magic Window System. In addition, a review of state-of-the-art screens and other existing technologies such as tablet PCs and Personal Digital Assistants (PDAs) was conducted and contributed to defining technical requirements and feasibility of systems. Some heuristic evaluations of large displays and PDAs were conducted. Finally, feasibility for implementation onboard ISS has been considered. Currently, specific headset units are undergoing usability testing. The outcome of these activities will be valuable to determine the best candidates for an integrated system that could accommodate different needs depending on task.

Whitmore, Mihriban↗
DOE OSTI2023

Differentiable Quantum Programming with Unbounded Loops

The emergence of variational quantum applications has led to the development of automatic differentiation techniques in quantum computing. Existing work has formulated differentiable quantum programming with bounded loops, providing a framework for scalable gradient calculation by quantum means for training quantum variational applications. However, promising parameterized quantum applications, e.g., quantum walk and unitary implementation, cannot be trained in the existing framework due to the natural involvement of unbounded loops. To fill in the gap, we provide the first differentiable quantum programming framework with unbounded loops, including a newly designed differentiation rule, code transformation, and their correctness proof. Technically, we introduce a randomized estimator for derivatives to deal with the infinite sum in the differentiation of unbounded loops, whose applicability in classical and probabilistic programming is also discussed. We implement our framework with Python and Q# and demonstrate a reasonable sample efficiency. Through extensive case studies, we showcase an exciting application of our framework in automatically identifying close-to-optimal parameters for several parameterized quantum applications.

Computer Science↗
DOE OSTI2026

Asi Nuclear Energy Sensors Data Portal Chatbot And Data Structuring Tool

The Idaho National Laboratory (INL) is advancing the development of an AI-powered chatbot and data structuring tool specifically designed to accelerate data mining processes for sensor-related information and seamlessly integrate the results into the ASI Sensors Data Portal (https://nes.energy.gov/). By doing so, the software aims to enhance the accessibility, usability, and organization of sensor data for nuclear energy applications. The software initial phase focuses on retrieving comprehensive datasets, prioritizing the past five years of publicly available information from the Office of Scientific and Technical Information (OSTI). These datasets will be meticulously processed to ensure compatibility, employing cleaning and preprocessing steps to eliminate irrelevant, incomplete, or corrupted information, thus establishing a robust foundation for subsequent AI use. The data will serve as the backbone for training an AI model and chatbot, which will act as an interactive tool enabling users to ask complex, context-specific questions and receive accurate, validated answers derived from constrained literature. In parallel, the project incorporates a data structuring process supported by AI to organize sensor information from multiple sources into a standardized format. This structured data will include detailed sensor specifications, such as measurement range, applications, accuracy, and operating conditions, generated and documented with AI. These specifications will be systematically integrated into the sensor portal. To maintain the highest levels of accuracy and relevance, all AI-generated outputs will be reviewed and validated by subject matter experts (SMEs), with additional fields or parameters added as needed. Future stages of the project aim to expand the dataset beyond OSTI to include other sources and potentially incorporate unclassified controlled information (UCI) with restricted access protocols to address security and confidentiality requirements.

Mapes, NormanJ. [Idaho National Laboratory (INL), ↗
DOE OSTI2019

Wireless 3D Nanorod Composite Arrays based High Temperature Surface-Acoustic-Wave Sensors for Selective Gas Detection through Machine Learning Algorithms (Final Report)

This is the final scientific and technical report which summarizes the research conducted through this funded project. In this report, we first present the accomplishments of the project, major research activities and specific activities conducted, and then discuss the significant results. We also describe the opportunities for training and professional development provided to the involved students as well as the products produced. Finally, we report the impact of the research on the development of human resources and present the budgetary information.

42 ENGINEERING↗
NASA NTRS2017

The Evolution of Planetary Protection Implementation on Mars Landed Missions

NASA has developed requirements dedicated to the prevention of forward and backward contamination during space exploration. Historically, international agreements provided guidelines to prevent contamination of the Moon and other celestial bodies, as well as the Earth (e.g., sample return missions). The UN Outer Space Treaty was established in 1967 and the Committee on Space Research (COSPAR) maintains a planetary protection policy complying with Article IX of this treaty. By avoiding forward contamination, the integrity of scientific exploration is preserved. Planetary Protection mission requirements are levied on missions to control contamination. These requirements are dependent on the science of the mission and on the celestial bodies encountered or targeted along the way. Consequently, categories are assigned to missions, and specific implementation plans are developed to meet the planetary protection requirements. NASA missions have evolved over time with increasingly more demanding scientific objectives and more complex flight systems to achieve those objectives and, thus, planetary protection methods and processes used for implementation have become much more intricate, complicated, and challenging. Here, we will portray the evolution of planetary protection implementation at JPL in several important areas throughout the course of NASA sponsored robotic Mars lander or rover missions, starting from Mars Pathfinder through the beginning of Mars 2020. Highlighted in the discussion will be process changes in planetary protection requirements development and flow down. Development and implementation of new and improved methods used in the reduction of spacecraft bioburden will be discussed as well as approaches and challenges that come along with setting up remote laboratories to perform bioassays. The consequences and forward planning of delays on missions will be highlighted as well as lessons learned on the impact of communication and training in achieving planetary protection requirements. The evolution of methods used for the detection of microbial bioburden on spacecraft hardware will be considered. These methods use standard microbiology as well as the adaptation of advances in biotechnology, molecular biology, and bioinformatics. Technical approaches developed for the prevention of contamination and recontamination of hardware during Assembly, Test, and Launch Operations will be discussed.

Kazarians, Gayane A.↗
DOE OSTI2021

Value of Information and Data Management Platform Promoting Modern Data Analysis Utilization. STTR Phase I, Final Technical Report

The immense growth in weather and river sensor data availability along with increases in computational power and algorithmic sophistication have enabled the widespread application of physical, machine learning, and artificial intelligence algorithms to river forecasting. The forecasts produced by widely varying model approaches are inherently limited in different ways, such as by the number and quality of training observations, producing biased predictions that achieve optimal skill only over specific ranges of weather and river conditions. Thus, despite the growing availability and new sources of forecasts, hydropower owners cannot fully leverage the information because they lack an effective mechanism to determine the “best” forecast for given conditions or objectives. Tools are needed to consolidate forecast information, demonstrate skill, and extract optimal forecast guidance from the range of possibilities. Such tools will increase uptake and beneficial use of the growing wealth of forecast information, and lead to improved operating decisions, optimal power generation, and enhanced system value. This research proposes to improve the value of forecasts by developing a broadly accessible verification framework and applying machine learning techniques to identify the ‘best’ forecast from an ensemble of sources given the current weather, river, and operating conditions.

13 HYDRO ENERGY↗
DOE OSTI2021

A Heterogeneous System for Eagle Detection, Deterrent, and Wildlife Collision Detection for Wind Turbines (Final Technical Report)

This report summarizes the design, implementation, and test of an integrated system for automated detection and deterrence of eagles, with included wind turbine blade strike detection and imaging functionality. A machine learning approach was used in conjunction with a 360° camera system for automated detection and classification of golden eagles. This was developed using footage obtained from trained golden eagles and other raptors, in collaboration with wildlife biologists and professional bird handlers. Oregon State University developed a visual deterrent system, which uses inflatable anthropomorphic sculptures with random, kinetic motion to deter eagles, and conducted limited field testing on live eagles; the deterrent can be triggered by the visual detection of eagles using the vision system. Finally, a multi-sensor module was developed that is mounted at the turbine blade root. This module measures vibration and other motions to detect blade strikes, and an integrated on-blade camera captures an image of any impacting objects. Long-term, this blade strike detection system is intended to support an automatic monitoring and certification system for the eagle detection and deterent system. Independent field testing of each system component is described. Testing of the integrated system on an operational wind turbine was conducted across three separate field tests. This includes multi-day fields tests on a General Electric 1.5MW wind turbine at the National Renewable Energy Laboratory (NREL) National Wind Technology Center (NWTC) in Boulder, CO in October 2018 and July 2019; installation procedures, test procedures, and a summary of collected data are presented. A third multi-day on-turbine field test is also presented, which was performed using a General Electric 1.5MW wind turbine at the North American Wind Research and Training Center (NAWRTC) at Mesalands Community College, Tucumcari, NM in April 2019. Across these field tests, the vision system was demonstrated using unmanned aerial vehicles (UAV), and the eagle classification algorithm was not tested; the visual deterrent system was demonstrated, including automatic, remote deployment following surrogate visual detections; and, multi-sensor on-blade data was recorded across multiple wind turbine operational conditions and through more than 100 surrogate blade strikes using soft projectiles, including the successful demonstration of automatic image capture of striking objects. This data set was also used for offline development and validation of enhanced collision detection algorithms. As summarized in this report, the development and field validation of an integrated detection, deterrent, and blade collision detection system represents a critical proof of concept for future technology development of related detection and deterrent technologies, where both deterrent as well as collision detection recording devices are needed for future siting, monitoring, and operation of wind turbine installations, both onshore and offshore.

17 WIND ENERGY↗
NASA NTRS2017

The NASA Space Life Sciences Training Program: Accomplishments Since 2013

The NASA Space Life Sciences Training Program (SLSTP) provides undergraduate students entering their junior or senior years with professional experience in space life science disciplines. This challenging ten-week summer program is held at NASA Ames Research Center. The primary goal of the program is to train the next generation of scientists and engineers, enabling NASA to meet future research and development challenges in the space life sciences. Students work closely with NASA scientists and engineers on cutting-edge research and technology development. In addition to conducting hands-on research and presenting their findings, SLSTP students attend technical lectures given by experts on a wide range of topics, tour NASA research facilities, participate in leadership and team building exercises, and complete a group project. For this presentation, we will highlight program processes, accomplishments, goals, and feedback from alumni and mentors since 2013. To date, 49 students from 41 different academic institutions, 9 staffers, and 21 mentors have participated in the program. The SLSTP is funded by Space Biology, which is part of the Space Life and Physical Sciences Research and Application division of NASA's Human Exploration and Operations Mission Directorate. The SLSTP is managed by the Space Biology Project within the Science Directorate at Ames Research Center.

education↗
DOE OSTI2014

Energy Technologies Research and Education Initiative

For this project, the intended goal of the microgrid component was to investigate issues in policy and technology that would drive higher penetration of renewable energy, and to demonstrate implementation in a utility system. The work accomplished on modeling the dynamics of photovoltaic (PV) penetration can be expanded for practical application. Using such a tool those involved in public policy can examine what the effect of a particular policy initiative, e.g., renewable portfolio standards (RPS) requirements, might be in terms of the desired targets. The work in the area of microgrid design, protection, and operation is fundamental to the development of microgrids. In particular the “Energy Delivery” paradigm provides new opportunities and business models for utilities. Ultimately, Energy Delivery could accrue significant benefits in terms of costs and resiliency. The experimental microgrid will support continued research and allow the demonstration of technology for better integration of renewables. The algal biofuels component of the project was developed to enhance the test facility and to investigate the technical and economic feasibility of a commercial-scale geothermal algal biofuels operation for replication elsewhere in the arid Southwest. The project was housed at New Mexico State University’s (NMSU’s) Geothermal Aquaculture Facility (GAF) and a design for the inoculation train and algae grow-out process was developed. The facility was upgraded with modifications to existing electrical, plumbing and structural components on the GAF and surrounding grounds. The research work was conducted on biomass-processing, harvesting, dewatering, and extraction. Additionally, research was conducted to determine viability of using low-cost, wastewater from municipal treatment plants in the cultivation units as make-up water and as a source of nutrients, including nitrogen and soluble phosphorus. Data was collected on inputs and outputs, growth evaluation and chemical composition of algal biomass feedstock. Also, research was completed on evaluating inoculation train, algae grow-out units, indoor cultivation units and the algal biomass dewatering units to identify opportunities for recapturing waste energy, water and biomass in the individual units or any combination of these units. A preliminary economic analysis was conducted.

09 BIOMASS FUELS↗
DOE OSTI2022

Rooftop Solar PV Quality and Safety in Developing Countries - Key Issues and Potential Solutions

To scale solar photovoltaic (PV) deployment in developing countries, the technology must be safe and reliable, meeting both customer and utility expectations. However, challenges exist in achieving these goals. Because PV systems are novel and complex, the majority of consumers are unable to distinguish between low- and high-quality systems; many may invest based on price alone. Suboptimal PV system performance and safety incidents can have downstream impacts on the solar industry and customer adoption because of unmet expectations and negative publicity. Rooftop solar system components vary in quality, and inadequate training could lead to poor installation practices. And even if inspection checklists, certification procedures, and standards are available, they may not be widely used in countries if they are not mandatory, the workforce is not aware of them, or installers lack the technical capacity to comply. Despite the numerous solar quality and safety challenges developing countries may face, lessons learned and best practices from around the world can address them.

14 SOLAR ENERGY↗
DOE OSTI2026

High-Field Quantum Diamond Magnetometers for Fusion Diagnostics (Final Technical Report)

Summary of research performed to enable all-optical quantum diamond magnetometers for fusion diagnostics, including: the physical mechanisms enabling all-optical photoluminescence contrast as a function of magnetic field magnitude and direction for dense ensembles of nitrogen vacancy (NV) centers in diamond; the characterization and optimization of NV-diamond material; and related investigations and student training.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1994

Medical and surgical evaluation and care of illness in space

This report summarizes the work done on the contract NAG9-567, which was activated at the New Jersey Medical School-UMDNJ in April 1992 and carried on during the 1992-93 year to the present 1993-94 year which was terminated in May 1994. The initial examination stage was completed of an interactive program for the recording of physical and physiologic injury information obtained from examination of an injured person, who might be an astronaut sustaining traumatic injury, due to a burn or physical trauma, either in space or in an earth bound training environment. In this report three aspects will be discussed: 1) a description of the system of diagnostic examination graphics, 2) a description of the organization of the therapeutic advisory systems with a demonstration of two specific modules, and 3) a brief technical description of the organization of the programming system carried out on a UNIX based work station using a WINDOWS environment.

Siegel, John H.↗