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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

In Situ Investigation of Upper Airway Occlusion in Sleep Disordered Breathing Using Ultrasonic Transducer Arrays

This work presents a novel application of ultrasound for the real-time, non-invasive investigation of occlusion of the upper airway during events of obstructive sleep apnea/hypopnea syndrome. It is hypothesized that ultrasonic pulses applied to the neck during apneic events produce spectral and temporal features that can detect apnea occurrence. Theoretical models of ultrasound propagation and an in vitro test were conducted to test this hypothesis in both transmission and reflection modes. Complete specifications and technical details of the system design and fabrication, which is mounted on each subject’s neck, are presented, including the methodology. Nine patients (seven male and two female, mean age of 42 years, with a range of 25 to 56 years, and body mass index 37.6 ± 6.6 kg/m2) were recruited for a full night study, which included simultaneous nocturnal polysomnography for the validation of the results. Nine temporal features and four spectral features were extracted from the envelope of the received pulse waveform. These were used to compute 26 metrics to quantify the changes in the ultrasonic waveforms between normal breathing and apneic events. The statistical analysis of the collected ultrasonic data showed that at least two or more of the proposed features could detect apneic events in all subjects. The findings establish the feasibility of the proposed method as a cost-effective and non-invasive OSAHS screening tool.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Radsource Mr: Mixed Reality Planning Tool For Radioactive Recovery

The RadSource MR system leverages Meta Quest 3's advanced mixed reality capabilities to create a comprehensive spatial planning platform for end-of-life sealed radioactive source recovery operations. The application utilizes the Quest 3's high-resolution passthrough cameras and spatial mapping algorithms to generate accurate 3D environmental models. Core technical components include: (1) Real-time spatial measurement algorithms calculating distances, angles, slopes, and surface areas with sub-centimeter accuracy; (2) Virtual object placement system allowing users to position digital representations of recovery equipment (trailers, containment vessels, protective barriers) within the real environment; (3) Voice recording and annotation system for hands-free documentation in protective equipment; (4) 3D mesh capture and storage capabilities for post-operation analysis and regulatory documentation. (5) Procedure documentation is available for viewing in Mixed Reality, providing an innovative and convenient way to access the information during pre-visit and inspection activities. (6) Support for screen capture for the view for real world and virtual objects together to use it later for planning. The system integrates computer vision techniques for environmental understanding, spatial mathematics for precise measurements, and human-computer interaction principles optimized for hazardous environment operations. Data persistence allows teams to save and share planning sessions across multiple stakeholders while maintaining operational security requirements.

Khadka, Rajiv [Idaho National Laboratory (INL), Id↗
DOE OSTI2020

Cost and Efficiency Analysis for Hybrid AC/DC Distribution System Planning with PV and Battery

Distribution system planning is one of the main tasks for the electric utilities. Cost and energy efficiency are two main concerns in the distribution planning process. In this work, cost and efficiency analyses are conducted for the hybrid AC and DC distribution grids for the planning purposes. The IEEE 34-bus feeder has been applied for the case studies. The investment cost, operation and maintenance cost, replacement cost, etc., have been considered in the life cycle cost analysis. Power losses of both the AC and DC section are calculated with an open source simulation tool, the Open Distribution Simulator Software (OpenDSS). The proposed framework can be applied to quantitatively evaluate the cost and efficiency of hybrid AC and DC distribution grids and help comparing different planning options.

AC/DC hybrid system planning↗
DOE OSTI2022

Optimization Models For Drone Deployment

Model that supports drone deployment. Analysis on speed, package weight, energy consumption, # of drones, and battery replacements. This software developed tools for drone deployment optimization for direct delivery by introducing a new model that presents new insights addressing real-life issues. Specifically, this developed a new mixed-integer programming model with both time windows and battery replacements.

Roni, MohammadS↗
DOE OSTI2024

45Q Addendum to the NETL CO2U LCA Guidance Document (V.2.0)

This document provides additional guidance and changes to the Carbon Dioxide Utilization Life Cycle Analysis Guidance for the U.S. DOE Office of Fossil Energy and Carbon Management, Version 2.0 to make it more applicable to taxpayers preparing life cycle analyses for the 45Q tax credit. This update adds clarity to existing text and includes information on new tools and data available.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Reinventing wastewater treatment plants: energy neutral treatment and enhanced fertilizer production through a novel resource recovery center

Wastewater treatment plants (WWTPs) are typically energy intensive, mainly due to the secondary treatment processes such as activated sludge (AS) for treatment of organics as well as nutrients like nitrogen. Nitrogen removal presents a big problem for WWTPs. The main form of nitrogen in wastewater is ammonium, and an AS process uses oxygen to convert ammonium into nitrite and nitrate which is then converted to nitrogen through denitrification process. During anaerobic digestion (AD), organic nitrogen gets degraded, resulting in an effluent stream (centrate) with a high nitrogen content, mostly in the form of ammonium. This contributes 15-30% of total nitrogen to the wastewater influent which further increases energy consumption for aeration. The project aims to transform this conventional municipal WWTPs into energy-neutral, resource-recovering facilities by integrating three core technologies: • Cloth Media Filtration (CMF) to replace conventional primary sedimentation (CPS) and increase the diversion of organics from the energy intensive secondary treatment to AD. This results in reduced energy demand for aeration in the secondary process while simultaneously increasing the biogas production in the anaerobic digesters. • Anerobic Digester to increase biogas and ammonia production. • Membrane Evaporation (ME) to recover ammonia from AD centrate and produce marketable fertilizer. The benefits of proposed WWTP process modifications were evaluated using techno economic analysis (TEA) and life cycle assessment (LCA). For CMF portion of the research a statistical analysis was employed to develop data-driven tools that could be used to enhance and optimize its performance in terms of energy savings and effluent quality. The main objective of this project is to reduce the energy demand for secondary treatment at municipal WWTPs by at least 50%, increase anaerobic digester (AD) biogas and ammonia production by 100% and 120%, respectively, and recover 90% of ammonia from the AD. Integrated CMF, AD, and ME was shown to work synergistically toward achieving these decarbonization targets through energy-positive treatment and fertilizer recovery techniques.

42 ENGINEERING↗
DOE OSTI2023

A hybrid method to evaluate the life cycle climate performance of heat pumps

Heat pumps have a significant impact on the climate, and numerous studies exist discussing the environmental impact of heat pumps quantitatively. Life Cycle Climate Performance (LCCP) is a widely accepted metric and can evaluate the carbon footprint of heat pumps from cradle to grave. LCCP calculation typically requires inputs like annual energy consumption, the material used, refrigerant type, and charge level, which are usually the intermediate or final results from heat pump simulation tools. Thus, a platform linking the heat pump simulation software, local weather conditions, and LCCP evaluation tool can simplify the heat pump design process, especially for complicated systems. This paper presents an LCCP evaluation tool accessing the outputs from the DOE Heat Pump Design Model and the building loads and temperature bin data from AHRI standard 210/240. As for case studies, this paper investigates the LCCP values and life cycle electricity costs (LCEC) of a given cooling-based heat pump with R410A in five typical US cities. In conclusion, this cooling-based heat pump has the highest LCCP value at Chicago and lowest LCCP value at Seattle. In contrast, the heat pump has the highest LCEC at Seattle and the lowest LCEC at Miami. As a future work, a more comprehensive carbon emission and cost analysis of heat pump systems will be conducted through all major cities around the world.

Shen, Bo↗
DOE OSTI2024

Machine learning at the edge to improve in-field safeguards inspections

Artificial intelligence (AI) and machine learning (ML) are near-ubiquitous in day-to-day life; from cars with automated driver-assistance, recommender systems, generative content platforms, and large language chatbots. Implementing AI as a tool for international safeguards could significantly decrease the burden on safeguards inspectors and nuclear facility operators. The use of AI would allow inspectors to complete their in-field activities quicker, while identifying patterns and anomalies and freeing inspectors to focus on the uniquely human component of inspections. Sandia National Laboratories has spent the past two and a half years developing on-device machine learning to develop both a digital and robotic assistant. This combined platform, which we term inspecta, has numerous on-device machine learning capabilities that have been demonstrated at the laboratory scale. Here this work describes early successes implementing AI/ML capabilities to reduce the burden of tedious inspector tasks such as seal examination, information recall, note taking, and more.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

Residential Facade Retrofits Modeling: Results and Documentation

Utilizing NREL's ResStock analysis tool and datasets, we performed an economic analysis for various facade upgrade combinations and strategies. This analysis considers the combined life-cycle cost of re-siding and window and insulation upgrades including both home value impacts and recurring bill savings estimates from a ResStock analysis, for varying years of home ownership.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Comparative Life Cycle Assessment of Bacterial and Thermochemical Retting of Hemp

The processes of hemp bast fiber retting, forming, and drying offer the opportunity for value-added products such as natural fiber-reinforced composites. A new process for the retting of raw bast fibers through enzyme-triggered self-cultured bacterial retting was developed in the lab-scale setup. This study focused on comparing the energy consumption and environmental impacts of this bacterial retting process with the thermochemical retting process currently widely used to obtain lignocellulosic fibers for composites. The gate-to-gate life cycle assessment (LCA) models of the two retting processes were constructed to run a comparison analysis using the TRACI (the tool for the reduction and assessment of chemical and other environmental impacts) method for environmental impacts and the cumulative energy demand (CED) method for energy consumptions. This work has demonstrated the advantages of the bacterial retting method from an environmental standpoint. The result of our research shows about a 24% gate-to-gate reduction in CED for bacterial retting and 20–25% lower environmental impacts relating to global warming, smog formation, acidification, carcinogenics, non-carcinogenics, respiratory effects, ecotoxicity, and fossil fuel depletion when compared to that of thermochemical retting.

Chemistry↗
DOE OSTI2022

Molecular mechanism of active Cas7-11 in processing CRISPR RNA and interfering target RNA

Cas7-11 is a Type III-E CRISPR Cas effector that confers programmable RNA cleavage and has potential applications in RNA interference. Cas7-11 encodes a single polypeptide containing four Cas7- and one Cas11-like segments that obscures the distinction between the multi-subunit Class 1 and the single-subunit Class-2 CRISPR Cas systems. We report a cryo-EM (cryo-electron microscopy) structure of the active Cas7-11 from Desulfonema ishimotonii (DiCas7-11) that reveals the molecular basis for RNA processing and interference activities. DiCas7-11 arranges its Cas7- and Cas11-like domains in an extended form that resembles the backbone made up by four Cas7 and one Cas11 subunits in the multi-subunit enzymes. Unlike the multi-subunit enzymes, however, the backbone of DiCas7-11 contains evolutionarily different Cas7 and Cas11 domains, giving rise to their unique functionality. The first Cas7-like domain nearly engulfs the last 15 direct repeat nucleotides in processing and recognition of the CRISPR RNA, and its free-standing fragment retains most of the activity. Both the second and the third Cas7-like domains mediate target RNA cleavage in a metal-dependent manner. The structure and mutational data indicate that the long variable insertion to the fourth Cas7 domain has little impact on RNA processing or targeting, suggesting the possibility for engineering a compact and programmable RNA interference tool.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

An Open-Source Framework for PV in the Circular Economy Evaluation

This open-source tool follows the dynamic Material and flows for each component and material in a PV system, from mining to end of life to evaluate the material and energy impacts of different paths. Following circularity principles, virgin material inputs can be offset by recovered materials to reduce impacts due to mining and extraction. Unlike consumer products, renewable energy technologies generate power over their useful life to quickly offset energy required for manufacturing. The model provides unique baselines of PV evolution, and allows us to evaluate the material and soon energy return on investment of decisions such as field repair, off-site refurbishment, reuse, or recycling. Energy layer and cost, as well as visual dashboard under development.

circular economy modeling↗
DOE OSTI2020

Optimal Sizing of Resilience Solutions for the U.S. Army Reserve

Power or water outages in buildings threaten the ability of the military to support surrounding communities during natural disasters. Outages can last for days, weeks or months. Typical solutions include very expensive batteries and onsite generation that are sized based on historical power needs. The U.S. Army Reserve (USAR) has teamed up with the Pacific Northwest National Laboratory (PNNL) to develop a simulation framework that optimizes future power needs to reduce the cost of resilience solutions. The approach starts with the building. Power needs during an emergency event are simulated at the building end-use level, then loads are reduced through the selection of life cycle cost-effective building-level technology improvements. These new optimized loads are then fed into a microgrid sizing tool that dynamically constructs many different combinations of solar photovoltaic, battery storage, and generator resources to meet the load for hundreds of statistically generated outage scenarios. Six site assessments completed by USAR and PNNL in 2019 have resulted in a 1-14% reduction in overall investment when optimizing the buildings first before determining the generation requirements. This approach helps the Army secure critical missions and provide a 14 day-minimum supply of necessary energy and water in the most efficient manner.

buidlings, efficiency, resilience, FEDS, MCOR↗
DOE OSTI2022

Machine learning for surrogate process models of bioproduction pathways

Technoeconomic analysis and life-cycle assessment are critical to guiding and prioritizing bench-scale experiments and to evaluating economic and environmental performance of biofuel or biochemical production processes at scale. Traditionally, commercial process simulation tools have been used to develop detailed models for these purposes. However, developing and running such models can be costly and computationally intensive, which limits the degree to which they can be shared and reproduced in the broader research community. This study evaluates the potential of an automated machine learning approach to develop surrogate models based on conventional process simulation models. The analysis focuses on several high-value biofuels and bioproducts for which pathways of production from biomass feedstocks have been well-established. The results demonstrate that surrogate models can be an accurate and effective tool for approximating the cost, mass and energy balance outputs of more complex process simulations at a fraction of the computational expense.

09 BIOMASS FUELS↗
DOE OSTI2021

Identification of Life Models for Li-Ion Batteries Using Penalized Regression and Bilevel Optimization

Reduced-order physics-based life models are extremely useful for rapidly predicting battery state-of-health and for simulating battery lifetime in arbitrary aging conditions. However, identification of well-parameterized models is difficult. This is because, for maximum usefulness in predicting lifetime under a variety of conditions, aging test data exhibits many degradation mechanisms, which all need to be accurately modeled. However, because aging tests are time-consuming and expensive, especially for large-format batteries, a minimum of tests are conducted while probing many stress factors. Building a well-parameterized model is then very challenging: an under-parameterized model will neglect critical degradation modes, and an over-parameterized model will extrapolate poorly to new testing conditions. To complicate this matter, the functional form of the model for any individual degradation rate can be very difficult to identify. In this work, the statistical tools of penalized regression and bilevel optimization are used to help identify both the functional forms of and optimize the parameters of reduced-order life models, accelerating identification of robust models. Model robustness is demonstrated through traditional statistics methods of cross-validation and sensitivity analysis, uncertainty quantification through bootstrap resampling and Monte-Carlo simulation, and simulation of real-world use cases.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Pathways to a Sustainable Aviation Ecosystem: Life Cycle Analysis with Blockchain Carbon Accounting

When linked with the National Renewable Energy Laboratory's (NREL's) rigorous life cycle assessment methodologies, blockchain technology can enable aviation stakeholders to quantify and transact on the impacts and benefits of sustainable aviation fuels and technologies. NREL can develop high-fidelity carbon modeling tools that enable apples-to-apples comparisons across technologies, fuels, companies, and jurisdictions.

aviation↗
DOE OSTI2024

Opportunities for retrieval and tool augmented large language models in scientific facilities

Upgrades to advanced scientific user facilities such as next-generation x-ray light sources, nanoscience centers, and neutron facilities are revolutionizing our understanding of materials across the spectrum of the physical sciences, from life sciences to microelectronics. However, these facility and instrument upgrades come with a significant increase in complexity. Driven by more exacting scientific needs, instruments and experiments become more intricate each year. This increased operational complexity makes it ever more challenging for domain scientists to design experiments that effectively leverage the capabilities of and operate on these advanced instruments. Large language models (LLMs) can perform complex information retrieval, assist in knowledge-intensive tasks across applications, and provide guidance on tool usage. Using x-ray light sources, leadership computing, and nanoscience centers as representative examples, we describe preliminary experiments with a Context-Aware Language Model for Science (CALMS) to assist scientists with instrument operations and complex experimentation. With the ability to retrieve relevant information from facility documentation, CALMS can answer simple questions on scientific capabilities and other operational procedures. With the ability to interface with software tools and experimental hardware, CALMS can conversationally operate scientific instruments. By making information more accessible and acting on user needs, LLMs could expand and diversify scientific facilities’ users and accelerate scientific output.

97 MATHEMATICS AND COMPUTING↗