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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Spontaneous Raman Scattering Diagnostics: Applications in Practical Combustion Systems

In this chapter, the recent advancements and practical aspects of laser SRS diagnostics have been reviewed wi til regards to applications in practical combustion systems. Clearly, SRS represents a theoretically and experimentally mature diagnostic technology that has become an essential tool for multiscalar measurements in turbulent combustion at elevated pressures. Today, time-, space-, spectrally, and even polarization-resolved S RS diagnostics is at hand, with aid from recent innovations in theoretical and technological developments on electro-optical or electromechanical devices. Whilst a linear increase in SRS signals can be expected in high-pressure systems (this is perhaps one of the most important advantages for using SRS in high-pressure systems), there are practical (often severe) restrictions associated with pressurized vessels, due mainly to the limited degree of optical access. This narrows ti,e available choice of diagnostics that can be employed at any given time. Point-wise SRS diagnostics provides the highest accuracy on the chemical species and temperature measurements, and will continue to remain a vital approach for the study in such harsh environments. The practical design considerations and hands-on set-up guide for SRS diagnostics provided in this chapter are rarely presented elsewhere. Although the second-harmonic Nd:YAG pulsed laser (532 nm), combined with pulse-stretching optics or the recently introduced White Cell-based laser, seems to be the most favored excitation source of choice by the research community, UV excitation will undoubtedly continue to be used on many occasions, and especially in sooting flames. Detection methods may be divided into ICCD-based nanosecond-gate detection or a rotary-chopper electromechanical shutter-based CCD array detection, and the levels of background flame emission in individual cases would determine this critical design choice. Here, a process of Raman signal calibration based on ti,e crosstalk matrix formalism was explained step-by-step. As tI,is process may be very time-consuming and expensive, a well-planned experimental approach (01' building a transferable calibration database or library (at least with in a user's own facility over a series of different testing and runs) is vitally important. Hands on advice on the design and construction of flow control systems for high pressure burner facilities were also presented.

Kojima, Jun↗
DOE OSTI2021

An automated approach to the alignment of compound refractive lenses

Compound refractive lenses (CRLs) are established X-ray focusing optics, and are thus a key element of many beamlines at X-ray facilities, used to either to focus a beam or image a sample. While CRLs are quite established, the stack of single lens elements affords a very small numerical aperture because of the thick lens profile, making them far more difficult to align than classical optical lenses that obey the thin-lens approximation. This means that the alignment must be very precise and is highly sensitive to changes to the incident beam; aligning CRLs is thus typically treated as a time-consuming manual process. Many groups circumvent day-to-day realignment by using engineering controls (e.g. mounting optics) that sacrifice some of the beam’s focusing characteristics, i.e. spot size, or resolution. While these choices minimize setup time, there are clear disadvantages. This work presents a new automated approach to align CRLs using a simple alignment apparatus that is easy to adapt and install at different types of X-ray experiments or facilities. Our approach builds on recent CRL modeling efforts, using an approach based on the Stochastic Nelder-Mead (SNM) simplex method. We demonstrate the efficacy of this method by numerical simulation and then extend this test to real experiments conducted at the Advanced Photon Source to confirm its performance with a synchrotron X-ray beam. This work provides an opportunity to automate key instrumentation at X-ray facilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Forest structural complexity and ignition pattern influence simulated prescribed fire effects

Background: Forest structural characteristics, the burning environment, and the choice of ignition pattern each influence prescribed fire behaviors and resulting fire effects; however, few studies examine the influences and interactions of these factors. Understanding how interactions among these drivers can influence prescribed fire behavior and effects is crucial for executing prescribed fires that can safely and effectively meet management objectives. To analyze the interactions between the fuels complex and ignition patterns, we used FIRETEC, a three-dimensional computational fluid dynamics fire behavior model, to simulate fire behavior and effects across a range of horizontal and vertical forest structural complexities. For each forest structure, we then simulated three different prescribed fires each with a unique ignition pattern: strip-head, dot, and alternating dot. Results: Forest structural complexity and ignition pattern affected the proportions of simulated crown scorch, consumption, and damage for prescribed fires in a dry, fire-prone ecosystem. Prescribed fires in forests with complex canopy structures resulted in increased crown consumption, scorch, and damage compared to less spatially complex forests. The choice of using a strip-head ignition pattern over either a dot or alternating-dot pattern increased the degree of crown foliage scorched and damaged, though did not affect the proportion of crown consumed. We found no evidence of an interaction between forest structural complexity and ignition pattern on canopy fuel consumption, scorch, or damage. Conclusions: We found that forest structure and ignition pattern, two powerful drivers of fire behavior that forest managers can readily account for or even manipulate, can be leveraged to influence fire behavior and the resultant fire effects of prescribed fire. These simulation findings have critical implications for how managers can plan and perform forest thinning and prescribed burn treatments to meet risk management or ecological objectives.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Model-Free Building Temperature Control and Power Allocation Under Measurement Time Delays

Taking a step towards a greener planet has created an increased need for a higher integration of renewable energy resources into the electric grid. Nonetheless, the intermittency and uncertainty associated with renewable generation have slowed down this integration. Demand response (DR) has been recently adopted to address this challenge by utilizing demand side flexibility and enabling the participation of many grid-interactive efficient buildings (GEBs). However, existing DR methods require significant modeling and/or training efforts and are computationally expensive. To address the aforementioned issues, we propose a model-free control (MFC)-based strategy that is robust to the time delays in the temperature measurements of the thermostatically controlled loads (TCLs). It assigns to each GEB a local controller to maintain the TCLs’ temperatures within desired comfort levels, while the load aggregator (LA) allocates the assigned reference power provided by the distribution system operator (DSO) to support a specific grid service, such as demand peak reduction, load shifting, balancing supply and demand, and consuming the solar photovoltaic power locally. We investigate the effects of such loss of information on the local control action as well as on meeting the power allocation constraint. We conclude that, for an appropriate choice of design parameters, the proposed MFC controller is satisfactorily robust to measurement time delays.

Telsang, Bhagyashri↗
DOE OSTI2022

How do perceptions of safety and car ownership importance affect autonomous vehicle adoption?

In this study, we explicitly modeled how individuals' perceptions of automated vehicle (AV) safety and the importance they place on car ownership affect mode choices involving conventional and automated vehicles in the context of privately owned cars and ridehailing services. We adopted psychometric questions to capture these two latent variables and designed a stated preference survey based on the participants' actual travel patterns. Then, we quantified the impact of these latent variables on mode choices using an integrated choice and latent variable (ICLV) model. We found that both latent variables have a statistically significant effect on mode choices. The results show that car ownership importance has the most potent effect on privately owned cars (conventional car and self-driving car), followed by driverless ridehailing and conventional ridehailing. We also found that changes in safety perception are equivalent to sizable changes in price. In addition, we further investigated the impact of improvements in safety perception through four scenarios. The scenario testing results show that as the distribution of perceived safety is compressed toward positive safety perception, the market share of AVs spikes and dominates regular cars. Our results demonstrate that based on our respondents' current understanding of AVs, even if AV prices were comparable to regular cars, we cannot expect widespread use of AVs. However, improvements in AVs' safety and, consequently, consumer safety perception can considerably expand AVs' market share, and may offset the high cost of using the technology.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2009

The Development of Wheels for the Lunar Roving Vehicle

The Lunar Roving Vehicle (LRV) was developed for NASA s Apollo program so astronauts could cover a greater range on the lunar surface, carry more science instruments, and return more soil and rock samples than by foot. Because of the unique lunar environment, the creation of flexible wheels was the most challenging and time consuming aspect of the LRV development. Wheels developed for previous lunar systems were not sufficient for use with this manned vehicle; therefore, several new designs were created and tested. Based on criteria set by NASA, the choices were narrowed down to two: the wire mesh wheel developed by General Motors (GM), and the hoop spring wheel developed by the Bendix Corporation. Each of these underwent intensive mechanical, material, and terramechanical analyses, and in the end, the wire mesh wheel was chosen for the LRV. Though the wire mesh wheel was determined to be the best choice for its particular application, it may be insufficient towards achieving the objectives of future lunar missions that could require higher tractive capability, increased weight capacity, or extended life. Therefore lessons learned from the original LRV wheel development and suggestions for future Moon wheel projects are offered.

Asnani, Vivake↗
DOE OSTI2022

Risk-Informed Operations and Maintenance Decision Making Using Deep Reinforcement Learning

A challenge for operating nuclear power plants is the significant cost of operations and maintenance, at times consuming up to 66% of annual operating costs. This project aims to build a framework for a risk-informed asset-management tool that integrates inspections, repairs, spare-part inventory, supply chain, and business choices to lower overall O&M costs. Our approach uses a combination of data-driven modeling and deep reinforcement learning to create and implement optimal maintenance policies for the existing nuclear fleet, as well as new advanced reactors. The creation of an asset management tool that uses these advanced methods will give operators new capabilities to help reduce the burden of O&M spending in nuclear power plants.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Virtual Log-Structured Storage for High-Performance Streaming

Over the past decade, given the higher number of data sources (e.g., Cloud applications, Internet of things) and critical business demands, Big Data transitioned from batch-oriented to real-time analytics. Stream storage systems, such as Apache Kafka, are well known for their increasing role in real-time Big Data analytics. For scalable stream data ingestion and processing, they logically split a data stream topic into multiple partitions. Stream storage systems keep multiple data stream copies to protect against data loss while implementing a stream partition as a replicated log. This architectural choice enables simplified development while trading cluster size with performance and the number of streams optimally managed. This paper introduces a shared virtual log-structured storage approach for improving the cluster throughput when multiple producers and consumers write and consume in parallel data streams. Stream partitions are associated with shared replicated virtual logs transparently to the user, effectively separating the implementation of stream partitioning (and data ordering) from data replication (and durability). We implement the virtual log technique in the KerA stream storage system. When comparing with Apache Kafka, KerA improves the cluster ingestion throughput by up to 4x when multiple producers write over hundreds of data streams.

consistent stream ordering↗
DOE OSTI2021

Repeal of the Clean Power Plan: Social Cost and Distributional Implications

The Clean Power Plan (CPP) was repealed due to concerns about the “unnecessary, costly burdens” it may impose on electric utilities, thereby delaying efforts to reduce carbon dioxide emissions (CO 2 ) from the electricity sector. This paper examines the greenhouse gas and welfare implications of this repeal while incorporating the presence of the state renewable portfolio standards (RPS) in the US as the status quo. We assess the carbon abatement and welfare costs with the CPP relative to two alternative baselines: a no–policy baseline and a pre–existing policy baseline with the RPS. The CPP is implemented as a regional mass–based standard, a regional rate–based standard, or as a national mass–based standard with trading of emissions across regions over the 2022–2030 period. We find that the incremental discounted welfare costs per metric ton of CO 2 that would have been abated by the CPP relative to the RPS would be substantially lower than the global social cost of CO 2 . However, the overall costs of carbon abatement with the CPP added to the RPS would have become higher than the social cost of carbon when estimated relative to a no–policy baseline, except with a national mass–based CPP. Across all policy combinations and choice of baselines, the aggregate welfare costs were lowest under a national mass–based standard and highest under the regional rate–based standard. Here, we also find that the CPP would have imposed large welfare costs on consumers and fossil fuel producers while benefiting the renewable fuel producers.

, Q42↗
DOE OSTI2026

2019 California Vehicle Survey

The 2019 California Vehicle Survey of residential and commercial light-duty fleet owners in California assessed consumer preferences for vehicles and included a targeted sample of plug-in electric vehicle (PEV) owners. In addition to economic and demographic data, the survey integrated light-duty vehicle holding and use information with vehicle choice data, which was collected via a set of eight exercises on vehicle and fuel type choice. The PEV owner survey participants provided additional data on charging behavior, electricity rates, and their main motivations for purchasing PEVs.

1Hz data↗
DOE OSTI2023

Machine-learning-assisted material discovery of oxygen-rich highly porous carbon active materials for aqueous supercapacitors

Abstract Porous carbons are the active materials of choice for supercapacitor applications because of their power capability, long-term cycle stability, and wide operating temperatures. However, the development of carbon active materials with improved physicochemical and electrochemical properties is generally carried out via time-consuming and cost-ineffective experimental processes. In this regard, machine-learning technology provides a data-driven approach to examine previously reported research works to find the critical features for developing ideal carbon materials for supercapacitors. Here, we report the design of a machine-learning-derived activation strategy that uses sodium amide and cross-linked polymer precursors to synthesize highly porous carbons (i.e., with specific surface areas > 4000 m 2 /g). Tuning the pore size and oxygen content of the carbonaceous materials, we report a highly porous carbon-base electrode with 0.7 mg/cm 2 of electrode mass loading that exhibits a high specific capacitance of 610 F/g in 1 M H 2 SO 4 . This result approaches the specific capacitance of a porous carbon electrode predicted by the machine learning approach. We also investigate the charge storage mechanism and electrolyte transport properties via step potential electrochemical spectroscopy and quasielastic neutron scattering measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1994

IMIS: An intelligence microscope imaging system

Until recently microscope users in space relied on traditional microscopy techniques that required manual operation of the microscope and recording of observations in the form of written notes, drawings, or photographs. This method was time consuming and required the return of film and drawings from space for analysis. No real-time data analysis was possible. Advances in digital and video technologies along with recent developments in article intelligence will allow future space microscopists to have a choice of three additional modes of microscopy: remote coaching, remote control, and automation. Remote coaching requires manual operations of the microscope with instructions given by two-way audio/video transmission during critical phases of the experiment. When using the remote mode of microscopy, the Principal Investigator controls the microscope from the ground. The automated mode employs artificial intelligence to control microscope functions and is the only mode that can be operated in the other three modes as well. The purpose of this presentation is to discuss the advantages and disadvantages of the four modes of of microscopy and how the IMIS, a proposed intelligent microscope imaging system, can be used as a model for developing and testing concepts, operating procedures, and equipment design of specifications required to provide a comprehensive microscopy/imaging capability onboard Space Station Freedom.

Caputo, Michael↗
DOE OSTI2024

Encapsulation Materials Tailored to Perovskite Photovoltaics

The work combines NREL as the world leader in perovskite and polymeric materials, and teams them up with The Dow Chemical Company, the world leader in commercial production of PV encapsulation materials. The team will design and evaluate encapsulation materials that are tailored to perovskite photovoltaics. Demonstration of polyolefin-based encapsulants for perovskite PV will be impactful for a number of reasons: 1) There is no clear-cut choice for encapsulation for perovskite PV to date. 2) There is high synthetic control of the material properties for future perovskite module designs. 3) Among the candidate materials, they have the highest barrier properties, 4) Polyolefins are the most prevalent (>20 million metric tons consumed in the US alone) and inexpensive (<1.5 $USD/kg) polymers used worldwide. 5) They are recyclable and may play a role in future of circular PV materials. 6) They are manufactured domestically. The work also highlights careful design of perovskite transport layer materials for surviving vacuum encapsulation.

14 SOLAR ENERGY↗
DOE OSTI2020

DDxNet: a deep learning model for automatic interpretation of electronic health records, electrocardiograms and electroencephalograms

Effective patient care mandates rapid, yet accurate, diagnosis. With the abundance of non-invasive diagnostic measurements and electronic health records (EHR), manual interpretation for differential diagnosis has become time-consuming and challenging. This has led to wide-spread adoption of AI-powered tools, in pursuit of improving accuracy and efficiency of this process. While the unique challenges presented by each modality and clinical task demand customized tools, the cumbersome process of making problem-specific choices has triggered the critical need for a generic solution to enable rapid development of models in practice. In this spirit, we develop DDxNet, a deep architecture for time-varying clinical data, which we demonstrate to be well-suited for diagnostic tasks involving different modalities (ECG/EEG/EHR), required level of characterization (abnormality detection/phenotyping) and data fidelity (single-lead ECG/22-channel EEG). Using multiple benchmark problems, we show that DDxNet produces high-fidelity predictive models, and sometimes even provides significant performance gains over problem-specific solutions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

2015-2017 California Vehicle Survey

The 2015-2017 California Vehicle Survey of residential and commercial light-duty vehicle owners in California assessed consumer preferences for vehicles and included a targeted sample of plug-in electric vehicle (PEV) owners. Resource Systems Group conducted the survey on behalf of the California Energy Commission. In addition to economic and demographic data, the survey integrated light-duty vehicle holding and use information with vehicle choice data collected via the stated preferences survey's set of eight vehicle and fuel type choice exercises. The PEV owner survey participants provided additional data on charging behavior, electricity rates, and their main motivations for purchasing PEVs.

1Hz data↗
NASA NTRS2012

Benefits of a Single-Person Spacecraft for Weightless Operations

Historically, less than 20 percent of crew time related to extravehicular activity (EVA) is spent on productive external work. For planetary operations space suits are still the logical choice; however for safe and rapid access to the weightless environment, spacecraft offer compelling advantages. FlexCraft, a concept for a single-person spacecraft, enables any-time access to space for short or long excursions by different astronauts. For the International Space Station (ISS), going outside is time-consuming, requiring pre-breathing, donning a fitted space suit, and pumping down an airlock. For each ISS EVA this is between 12.5 and 16 hours. FlexCraft provides immediate access to space because it operates with the same cabin atmosphere as its host. Furthermore, compared to the space suit pure oxygen environment, a mixed gas atmosphere lowers the fire risk and allows use of conventional materials and systems. For getting to the worksite, integral propulsion replaces hand-over-hand translation or having another crew member operate the robotic arm. This means less physical exertion and more time at the work site. Possibly more important, in case of an emergency, FlexCraft can return from the most distant point on ISS in less than a minute. The one-size-fits-all FlexCraft means no on-orbit inventory of parts or crew time required to fit all astronauts. With a shirtsleeve cockpit, conventional displays and controls are used, there is no suit trauma and because the work is not strenuous, no rest days are required. Furthermore, there is no need to collect hand tools because manipulators are equipped with force multiplying end-effectors that can deliver the precise torque for the job. FlexCraft is an efficient solution for asteroid exploration allowing all crew to use one vehicle with no risk of contamination. And, because FlexCraft is a vehicle, its design offers better radiation and micro-meteoroid protection than space suits.

Griffin, Brand Norman↗
DOE OSTI2022

Guiding the choice of informatics software and tools for lipidomics research applications

Progress in mass spectrometry lipidomics has led to a rapid proliferation of studies across biology and biomedicine. These generate extremely large raw datasets requiring sophisticated solutions to support automated data processing. To address this, numerous software tools have been developed and tailored for specific tasks. However, for researchers, deciding which approach best suits their application relies on ad hoc testing, which is inefficient and time consuming. Here we first review the data processing pipeline, summarizing the scope of available tools. Next, to support researchers, LIPID MAPS provides an interactive online portal listing open-access tools with a graphical user interface. This guides users towards appropriate solutions within major areas in data processing, including (1) lipid-oriented databases, (2) mass spectrometry data repositories, (3) analysis of targeted lipidomics datasets, (4) lipid identification and (5) quantification from untargeted lipidomics datasets, (6) statistical analysis and visualization, and (7) data integration solutions. Detailed descriptions of functions and requirements are provided to guide customized data analysis workflows.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2010

Materials Development: Pitfalls, Successes, and Lessons

The incorporation of new or improved materials in aerospace systems, or indeed any systems, can yield tremendous payoffs in the system performance or cost, and in many cases can be enabling for a mission or concept. However, the availability of new materials requires advance development, and too often this is neglected or postponed, leaving a project or mission with little choice. In too many cases, the immediate reaction is to use what was used before; this usually turns out not to be possible and results in large sums of money, and amounts of time, being expended on reinvention rather than development of a material with extended capabilities. Material innovation and development is time consuming, with some common wisdom claiming that the timeline is at least 20 years. This time expands considerably when development is stopped and restarted, or knowledge is lost. Down selection of materials is necessary, especially as the Technical Readiness Level (TRL) increases. However, the costs must be considered and approaches should be taken to retain knowledge and allow for restarting the development process. Regardless of the exact time required, it is clear that it is necessary to have materials, at all stages of development, in a research and development pipeline and available for maturation as required. This talk will discuss some of theses issues, including some of the elements for a development path for materials. Some history of materials developments will be included. The usefulness of computational materials science, as a route to decreasing material development time, will be an important element of this discussion. Collaboration with outside institutions and nations is also critical for innovation, but raises the issues of intellectual property and protections, and national security (ITAR rules, for example).

Johnson, Sylvia M.↗