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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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The VULCAN Beamline dataset provides the sample measurement, where temperatures is recorded in two physically different places on the sample. These are held in two different hdf5 groups in the data file.
The Campaign Management project at the National Ignition Facility is embarking on a major redesign of the software used by experimentalists to setup experiments on the NIF. The current editor was architected over a decade ago and optimized for a different purpose than supporting production science campaigns. It has a steep learning curve and lacks many desirable features. Furthermore, its underlying technology stack and architecture do not support the kind of routine capability evolution that represents current and future growth needs of the Program. The principal stakeholders are the physicists who are users of the editing application, but the entire integrated suite of Campaign Management software has a broad customer base spanning experimentalists, NIF sub-system subject matter experts, planners, and shot operations staff. A recent DOE-mandated review of NIF activity, conducted with the goal of improving the shot rate at NIF, identified the experiment editor as a clear barrier to a more productive and efficient experiment lifecycle, exposing unnecessary levels of detail, lacking adequate automation, and lacking adequate integration with related activities and data sources in what should be a shared data environment.
A prescription for computing the Feynman Y as a function of coincidence gate width using a deterministic multigroup neutron transport code has been published and the results compared favorably with measurements of the BeRP ball. In this paper, we report on our project to implement the method and reproduce the results. There are several clarifications and corrections of the published prescription. We show results using two multigroup cross section libraries compared with measurements and with Monte Carlo results. Deterministic simulations of the mean count rates compare very favorably with previously published Monte Carlo results, and deterministic simulations of the Feynman Y asymptote compare somewhat favorably. In Feynman beta plots, the deterministic simulations reached the asymptotic value much sooner than did a fit to the measured data.
Chirp signals have evolved primarily from radar/sonar signal processing applications specifically attempting to estimate the location of a target in surveillance/tracking volume. The chirp, which is essentially a sinusoidal signal whose phase changes instantaneously at each time sample, has an interesting property in that its correlation approximates an impulse function. It is well-known that a matched-filter detector in radar/sonar estimates the target range by cross-correlating a replicant of the transmitted chirp with the measurement data reflected from the target back to the radar/sonar receiver yielding a maximum peak corresponding to the echo time and therefore enabling the desired range estimate. In this application, we perform the same operation as a radar or sonar system, that is, we transmit a “chirp-like pulse” into the target medium and attempt to first detect its presence and second estimate its location or range. Our problem is complicated by the presence of disturbance signals from surrounding broadcast stations as well as extraneous sources of interference in our frequency bands and of course the ever present random noise from instrumentation. First, we discuss the chirp signal itself and illustrate its inherent properties and then develop a model-based processing scheme enabling both the detection and estimation of the signal from noisy measurement data.
This report describes the continuation of the Computational Fluid Dynamics (CFD) model of the Supo cooling system described in the reports, Supo Thermal Model Development 1 and Supo Thermal Model Development II 2 . The goal for this report is to more accurately estimate the natural convection heat transfer coefficient (HTC) of the system using the CFD results and to compare those results to remaining past operational data.
Main task was to create a deliverable (report) calculating the amount of efficiency that could be acquired with the implementation of Wireless manufacturing. A methodology was defined to combine and compare different quantifiable parameters. The relevance of this data is to demonstrate the effects that wireless connections could have when implemented. This was demonstrated with published industry data.
With the adoption of drtsans as the data reduction software for the GP-SANS, Bio-SANS and EQ-SANS instruments at ORNL, tools for data visualization and analysis that can be integrated into drtsans scripts are needed to further improve the user experience. New tools that do not need to be incorporated directly into data reduction scripts can also positively impact users during their experiments. In this report, a new set of tools is presented that complements the previous set released. The set includes tools for both fitting data and for visualizing data.
Empirical observations of tool exit from the blank are interpreted on the basis of the model developed.
The influence of oscillatory smoothing on the residual stress in cylindrical components is investigated by simulation and laboratory experiments. The residual stress is found to depend on the tool supply, the interference, the workpiece speed, the oscillatory frequency, and the tool’s angular position (inclination). The experimental results are in good agreement with the modeling data.
The past decade has seen significant progress in the field of metabolic engineering and synthetic biology. The exponentially growing multi-omics data and technological advances in the development of efficient genetic manipulation tools and techniques have allowed scientists to explore and expand their understanding of microbial metabolisms and further develop sophisticated engineering strategies to realize the use of industrial "workhorses" and non-conventional microorganisms for sustainable bioconversion and biorefinery. There is of great interest for the research community in using C1 compounds (i.e., CO 2 , CO/syngas, methane, methanol) as the next generation feedstocks for microbial cell factories and biocatalysts to promote the sustainable development of a green economy (Figure 1). Considering lowering input costs is also a main consideration for successful business ventures, the use of inexpensive, abundant, and widely accessible C1 compounds is envisioned as a promising route for the sustainable production of fine chemicals, fuels, and other high-value products. Many C1 compounds are waste gases from industrial activities and may have detrimental effects on climate change upon emission into the atmosphere. Therefore, promoting the use of C1 compounds as renewable carbon feedstocks can greatly contribute to the reduction of anthropogenic emission of air pollutants.
Supporting experimental data for "Conversion of Stored Thermochemical Potential into High Quality Heat in a Continuous Flow Reactor/Heat Exchanger" including steady-state temperatures and conversion data.
The fastest commercially available 16-bit ADC can only perform around 200 mega-samples per second (200 MS/s). Connecting ADC chips together in eight different time domains increases the quantity of samples taken by a factor of eight. This method of interleaving requires that the input signal being sampled is split into eight identical signals and arrives at each ADC chip at the same point in time. The splitting of the input signal is performed in the analog front end containing a wideband filter that impedance matches the input signal to the ADC chips. Each ADC uses a clock to tell it when to perform a conversion. Using eight unique clocks spaced in 45-degree increments is the method used to time shift when each ADC chip performs its conversion. Given that this control clock is a fixed frequency, the clock phase shifting is accomplished by tightly controlling the distance that the clock must travel, resulting in a time delay. The interleaved ADC chips will now generate digital data in eight different time domains. These data are processed inside a field-programmable gate array (FPGA) to move the data back into a single time domain and store it into memory. The FPGA also contains a Nios II processor that provides system control and data retrieval via Ethernet.
Introduced a novel contrast metric in combination with traditional metrics to evaluate quality of coherent aperture radar, data products.
The purpose of this study was to develop a process to convert input signals from one facility into another by reflecting geometric and environmental settings. The Dynamic Energy Transport and Integration Laboratory (DETAIL) is a research facility in development. Its aim is to emulate the daily interactions among power production industry systems and receive real-time data from those systems as inputs. To convert signals and ensure that the temporal sequences and magnitudes reflect laboratory settings, the ability to scale and project data is essential. To demonstrate this ability, Dynamical System Scaling (DSS) and Hierarchical Two-Tiered Scaling (H2TS) (methodologies that enable systems to scale and project or extrapolate data sets to desired environments while conserving the observed behavior based on first principles) were applied to DETAIL’s thermocline thermal storage system in the Thermal Energy Distribution System (TEDS) facility and solid-oxide electrolysis cell in the High Temperature Hydrogen Electrolysis (HTHE) facility. Both thermocline and electrolysis cell systems were successfully scaled, and test cases were conducted to generate a doubly accelerated energy charge and discharge in reference to past experimental data from the facilities. The research results represented a case for the thermocline system that required signals to be accelerated without altering the stored energy. To enhance the quality of the accelerated data, error propagation analyses were conducted on DSS post-processing terms to determine the consequences of raw-data-associated errors.
Advanced packaging technologies are currently being designed and developed by the power electronics industry however, the maximum operating temperature is still limited to 175 degrees Celsius for the silicon carbide devices. Bonded materials such as sintered copper and polymeric materials are potential candidates for high temperature operation, but it is critical to characterize and evaluate its reliability under harsh operating conditions. In this project, we discuss the results of the accelerated experiments conducted on sintered copper and polymeric materials. Additionally, a novel framework to develop the lifetime prediction model of bonded interfaces through employing statistical and machine learning models are described. In this task, scanning acoustic microscope images of bonded interfaces obtained under thermal cycling experiments are used as the data.
An update will be provided on NREL's ongoing work to address the range of soiling challenges the PV community is facing. First, results will be shown on the efforts to develop a low-cost and low-maintenance soiling measurement sensor. Second, the latest NREL soiling map will be demonstrated as well as how the PVfleets database is enabling regular improvement to the map. Additionally, PVfleets is uncovering challenges with pollen and other bio-soiling in rainy regions in the southeast United States. Finally new results will be presented for improvement of automated algorithms to extract soiling losses from PV data.
Safety, risk, and reliability issues are vital to ensure the continuous and profitable operation of hydrogen technologies. Quantitative risk assessment (QRA) has been used to enable the safe deployment of engineering systems, especially hydrogen fueling stations. However, QRA studies require reliability data which are essential to collect to make the studies as realistic and relevant as possible. These data are currently lacking and data from other industries, such as oil and gas, are used in hydrogen system QRAs. This may lead to inaccurate results since hydrogen fueling stations have differences in physical properties, system design, and operational parameters when compared to other fueling stations, thus necessitating new data sources are necessary to capture the effects of these differences. To address this gap, we developed a structure for a hydrogen component reliability database, (HyCReD) [1], which could be used to generate reliability data to be used in QRA studies. In this paper, we demonstrate populating the HyCReD database with information extracted from new narrative reports on hydrogen fueling station incidents, specifically focused on the dispensing processes. We analyze five new events and demonstrate the feasibility of populating the database and types of meaningful insights that can be obtained at this stage.
Model-based, distribution powerflow analysis is a foundational component of system planning and grid modernization efforts, but data security is an impediment to collaboration among utility engineers, researchers, developers, community members, and other stakeholders. Pacific Northwest National Laboratory (PNNL) and the National Renewable Energy Laboratory (NREL) are partnering to develop the new Distribution Grid Atlas - a publicly available catalog of realistic, geographically relevant, representative distribution feeder models without sensitive geographic information, customer data, or disclosure of utility models. We are looking for utilities to share data for the Distribution Grid Atlas.