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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 991 records · Page 55

Characterization Data Package for Containerized Sludge Samples Collected from Engineered Container SCS-CON-210

This data package contains the K Basin sludge characterization results obtained by Pacific Northwest National Laboratory during processing and analysis of four sludge core samples collected from Engineered Container SCS-CON-210 in 2010 as requested by CH2M Hill Plateau Remediation Company. Sample processing requirements, analytes of interest, detection limits, and quality control sample requirements are defined in the KBC-33786, Rev. 2. The core processing scope included reconstitution of a sludge core sample distributed among four to six 4-L polypropylene bottles into a single container. The reconstituted core sample was then mixed and subsampled to support a variety of characterization activities. Additional core sludge subsamples were combined to prepare a container composite. The container composite was fractionated by wet sieving through a 2,000 micron mesh and a 500-micron mesh sieve. Each sieve fraction was sampled to support a suite of analyses. The core composite analysis scope included density determination, radioisotope analysis, and metals analysis, including the Waste Isolation Pilot Plant Hazardous Waste Facility Permit metals (with the exception of mercury). The container composite analysis included most of the core composite analysis scope plus particle size distribution, particle density, rheology, and crystalline phase identification. A summary of the received samples, core sample reconstitution and subsampling activities, container composite preparation and subsampling activities, physical properties, and analytical results are presented. Supporting data and documentation are provided in the appendices. There were no cases of sample or data loss and all of the available samples and data are reported as required by the Quality Assurance Project Plan/Sampling and Analysis Plan.

core sampling↗

The application of neural networks to the SSME startup transient

Feedforward neural networks were used to model three parameters during the Space Shuttle Main Engine startup transient. The three parameters were the main combustion chamber pressure, a controlled parameter, the high pressure oxidizer turbine discharge temperature, a redlined parameter, and the high pressure fuel pump discharge pressure, a failure-indicating performance parameter. Network inputs consisted of time windows of data from engine measurements that correlated highly to the modeled parameter. A standard backpropagation algorithm was used to train the feedforward networks on two nominal firings. Each trained network was validated with four additional nominal firings. For all three parameters, the neural networks were able to accurately predict the data in the validation sets as well as the training set.

Meyer, Claudia M.↗

The application of neural networks to the SSME startup transient

Feedforward neural networks were used to model three parameters during the Space Shuttle Main Engine startup transient. The three parameters were the main combustion chamber pressure, a controlled parameter, the high pressure oxidizer turbine discharge temperature, a redlined parameter, and the high pressure fuel pump discharge pressure, a failure-indicating performance parameter. Network inputs consisted of time windows of data from engine measurements that correlated highly to the modeled parameter. A standard backpropagation algorithm was used to train the feedforward networks on two nominal firings. Each trained network was validated with four additional nominal firings. For all three parameters, the neural networks were able to accurately predict the data in the validation sets as well as the training set.

Meyer, Claudia M.↗

Bridging the Engineering and Medicine Gap

A primary challenge NASA faces is communication between the disparate entities of engineers and human system experts in life sciences. Clear communication is critical for exploration mission success from the perspective of both risk analysis and data handling. The engineering community uses probabilistic risk assessment (PRA) models to inform their own risk analysis and has extensive experience managing mission data, but does not always fully consider human systems integration (HSI). The medical community, as a part of HSI, has been working 1) to develop a suite of tools to express medical risk in quantitative terms that are relatable to the engineering approaches commonly in use, and 2) to manage and integrate HSI data with engineering data. This talk will review the development of the Integrated Medical Model as an early attempt to bridge the communication gap between the medical and engineering communities in the language of PRA. This will also address data communication between the two entities in the context of data management considerations of the Medical Data Architecture. Lessons learned from these processes will help identify important elements to consider in future communication and integration of these two groups.

Walton, M.↗

LANDSAT-4 evaluation program and scientific characterization activities

The characterization objectives of the LANDSAT 4 Science Office at GSFC are to: (1) determine the accuracy and precision of sensor and spacecraft performance, image data quality, and derived information; (2) recommend LANDSAT 4 system improvements; and (3) communicate results to the research community. In-house activities are directed toward full access and utilization of the prelaunch and in-orbit engineering test data on the sensor and spacecraft. Principle scientists in remote sensing are involved as part of a major scientific characterization effort, and workshops were held for these investigative teams. A symposium is scheduled prior to turnover of the TM to NOAA.

Barker, J. L.↗

Online Detection of Low-Quality Synchrophasor Data Considering Frequency Similarity

Here, this letter proposes a new approach for online detection of low-quality synchrophasor data under both normal and event conditions. The proposed approach utilizes the features of synchrophasor data in time and frequency domains to distinguish multiple regional PMU signals and detect low-quality synchrophasor data. It is more effective to detect low-quality data with apparently indistinguishable profiles. Case studies from recorded synchrophasor measurements verify the effectiveness of the proposed approach for detecting low-quality synchrophasor data in frequency, voltage magnitude and voltage angle.

42 ENGINEERING↗

An expert system to analyze high frequency dependent data for the space shuttle main engine turbopumps

The prototype expert system ADDAMX identifies selected sinusoid frequencies from spectral data graphs as speed frequencies and harmonics from each turbopump, frequency feed through from one turbopump to another, frequencies generated by turbopump bearings, pseudo 3N for the phase 2 high pressure fuel turbopump, and electrical noise. ADDAMX does the analysis in an interactive or batch mode and the results can be displayed on the screen or hardcopy.

Garcia, Raul C., Jr.↗

Digitalization Guiding Principles and Method for Nuclear Industry Work Processes

The commercial U.S. light-water reactor fleet has been operating at historical efficiency, reliability, and safety over the last decade. Nuclear power has the highest capacity factor of any other power generation technology while also serving as the largest baseload source for carbon-free energy. Despite this remarkable achievement, continued operations for many plants are threatened due to fierce electricity market competition and rising operations and maintenance costs of which continued maintenance of obsolete analog equipment is a contributor. The digital age and associated technologies are where the future lies in process control, and nuclear has yet to take full advantage of the capabilities offered therein. The Light Water Reactor Sustainability Program (LWRS) at Idaho National Laboratory (INL), sponsored by the Department of Energy, has a mission to help the light-water reactor fleet manage its foundational capabilities to continue providing safe and reliable carbon-free power. LWRS helps support that mission by providing scientific, technology-based solutions for advanced concepts of operations with a more viable business model that will allow the fleet to continue to operate at peak levels through extended plant operation. The LWRS Digitalization Project at INL seeks to leverage digital technologies to synthesize and transform work processes. We provide a state-of-the-art analysis of digitalized work processes in nuclear power and investigate ways in which researchers at INL and the nuclear industry can work together to identify what data to access, how to access it, what to do with the data, and most importantly, how to use the insights for decision-making across all levels within the business. Borne from these considerations, we present four guiding principles for digitalization: develop a coherent digitalization plan, apply human factors engineering, establish data governance, and anticipate unintended consequences. Together, these principles form a method that plants can use to effectively to digitalize nuclear industry work processes. Our guiding principles are informed by multiple knowledge sources. First, we document activities from the Work Digitalization Initiative, which was conceived as a means for nuclear organizations to help define and standardize the industry’s approach to digitalizing work. Second, we detail primary research conducted with industry professionals regarding drivers and barriers to digitalization adoption. We present survey results that demonstrate what the industry hopes to get out of digitalization and the ways that INL can continue to support the industry’s digital transformation. Third, we present a digitalization use case with industry partners NextAxiom Technology and Xcel Energy. The project objective was to transform the current condition report work process from paper to digital, incorporating digitalized principles. We report the development of the application and lessons learned. The accomplishments achieved by this research and development serve to identify critical needs for plant guidance in support of digitalization implementation and contribute to the knowledge and strategies available for utilities considering or undertaking digitalization.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

International Collaboration Activities on Engineered Barrier Systems

International collaborations on nuclear waste disposal is an integral part of the Spent Fuel Waste Science and Technology (SFWST) campaign within the DOE Fuel Cycle and Technology (FCT) program. These engagements with international repository R&D programs provide key opportunities to participate in experiments with international partners on research investigations developing laboratory/field (underground research laboratories (URL) experiments) data of engineered barrier system (EBS) components (e.g., near-field) and characterization of transport phenomena in the host rock (e.g., far-field). The results of these field and laboratory experiments are used in the evaluation of coupled processes and the development of state-of-the-art simulation approaches to evaluate repository performance. Thermal heating from radionuclide decay in the waste canisters will increase temperature in the surrounding EBS driving chemical and transport processes in the near- and far-field domains of the repository. URL heater-tests for extended periods of times (e.g., years) provide key information and data of thermal effects on barrier responses to temperature and water saturation levels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Phased Array Noise Source Localization Measurements Made on a Williams International FJ44 Engine

A 48-microphone planar phased array system was used to acquire noise source localization data on a full-scale Williams International FJ44 turbofan engine. Data were acquired with the array at three different locations relative to the engine, two on the side and one in front of the engine. At the two side locations the planar microphone array was parallel to the engine centerline; at the front location the array was perpendicular to the engine centerline. At each of the three locations, data were acquired at eleven different engine operating conditions ranging from engine idle to maximum (take off) speed. Data obtained with the array off to the side of the engine were spatially filtered to separate the inlet and nozzle noise. Tones occurring in the inlet and nozzle spectra were traced to the low and high speed spools within the engine. The phased array data indicate that the Inflow Control Device (ICD) used during this test was not acoustically transparent; instead, some of the noise emanating from the inlet reflected off of the inlet lip of the ICD. This reflection is a source of error for far field noise measurements made during the test. The data also indicate that a total temperature rake in the inlet of the engine is a source of fan noise.

Podboy, Gary G.↗

Spherical Coordinate Systems for Streamlining Suited Mobility Analysis

When describing human motion, biomechanists generally report joint angles in terms of Euler angle rotation sequences. However, there are known limitations in using this method to describe complex motions such as the shoulder joint during a baseball pitch. Euler angle notation uses a series of three rotations about an axis where each rotation is dependent upon the preceding rotation. As such, the Euler angles need to be regarded as a set to get accurate angle information. Unfortunately, it is often difficult to visualize and understand these complex motion representations. One of our key functions is to help design engineers understand how a human will perform with new designs and all too often traditional use of Euler rotations becomes as much of a hindrance as a help. It is believed that using a spherical coordinate system will allow ABF personnel to more quickly and easily transmit important mobility data to engineers, in a format that is readily understandable and directly translatable to their design efforts. Objectives: The goal of this project is to establish new analysis and visualization techniques to aid in the examination and comprehension of complex motions. Methods: This project consisted of a series of small sub‐projects, meant to validate and verify the method before it was implemented in the ABF's data analysis practices. The first stage was a proof of concept, where a mechanical test rig was built and instrumented with an inclinometer, so that its angle from horizontal was known. The test rig was tracked in 3D using an optical motion capture system, and its position and orientation were reported in both Euler and spherical reference systems. The rig was meant to simulate flexion/extension, transverse rotation and abduction/adduction of the human shoulder, but without the variability inherent in human motion. In the second phase of the project, the ABF estimated the error inherent in a spherical coordinate system, and evaluated how this error would vary within the reference frame. This stage also involved expanding a kinematic model of the shoulder, to include the torso, knees, ankle, elbows, wrists and neck. Part of this update included adding a representation of 'roll' about an axis, for upper arm and lower leg rotations. The third stage of the project involved creating visualization methods to assist in interpreting motion in a spherical frame. This visualization method will be incorporated in a tool to evaluate a database of suited mobility data, which is currently in development.

Benson, Elizabeth↗

PIPER: Performance Insights for Programmers and Exascale Runtimes

During the lifetime of the project, the PIPER at the University of Utah worked in collaboration with the team from the partner institutions to establish a set of software tools for analyzing and improving the performance parallel computing tools. These activities complement and complete the work performed by the other X-Stack 2 projects with the definition of a common data models and computing infrastructures, which have been a central element in the targeted performance analysis pipeline and new programming models. The University of Utah team have focused mainly on developing data analysis and visualization systems to facilitate exploration, comparison and evaluation of the behavior and performance of complex algorithms in modern HPC infrastructures. This is involved several demonstrations of the performance achieved and presentation of the results in a way that facilitates the users understand bottlenecks and ways to overcome them. One major focus of the University of Utah activities has been the analysis of the performance characteristics of Fat-Tree and Dragonfly topology networks. The work involved the development of practical visualization systems especially in collaboration with the team at LLNL, and published several papers and gave invited talks at prestigious venues such as the Salishan Conference on High-Speed Computing or the International Conference on High Performance Computing, Data, and Analytics. In addition, the university of Utah team has advanced the core activities on analyzing the performance characteristics of I/O and other data movement systems and their practical use for scaling Uintah and other simulation codes poised for use in the exascale computing environments of the future.

42 ENGINEERING↗

Develop Advanced Nonlinear Signal Analysis Topographical Mapping System

During the development of the SSME, a hierarchy of advanced signal analysis techniques for mechanical signature analysis has been developed by NASA and AI Signal Research Inc. (ASRI) to improve the safety and reliability for Space Shuttle operations. These techniques can process and identify intelligent information hidden in a measured signal which is often unidentifiable using conventional signal analysis methods. Currently, due to the highly interactive processing requirements and the volume of dynamic data involved, detailed diagnostic analysis is being performed manually which requires immense man-hours with extensive human interface. To overcome this manual process, NASA implemented this program to develop an Advanced nonlinear signal Analysis Topographical Mapping System (ATMS) to provide automatic/unsupervised engine diagnostic capabilities. The ATMS will utilize a rule-based Clips expert system to supervise a hierarchy of diagnostic signature analysis techniques in the Advanced Signal Analysis Library (ASAL). ASAL will perform automatic signal processing, archiving, and anomaly detection/identification tasks in order to provide an intelligent and fully automated engine diagnostic capability. The ATMS has been successfully developed under this contract. In summary, the program objectives to design, develop, test and conduct performance evaluation for an automated engine diagnostic system have been successfully achieved. Software implementation of the entire ATMS system on MSFC's OISPS computer has been completed. The significance of the ATMS developed under this program is attributed to the fully automated coherence analysis capability for anomaly detection and identification which can greatly enhance the power and reliability of engine diagnostic evaluation. The results have demonstrated that ATMS can significantly save time and man-hours in performing engine test/flight data analysis and performance evaluation of large volumes of dynamic test data.

Jong, Jen-Yi↗

Traversing Microphone Track Installed in NASA Lewis' Aero-Acoustic Propulsion Laboratory Dome

The Aero-Acoustic Propulsion Laboratory is an acoustically treated, 65-ft-tall dome located at the NASA Lewis Research Center. Inside this laboratory is the Nozzle Acoustic Test Rig (NATR), which is used in support of Advanced Subsonics Technology (AST) and High Speed Research (HSR) to test engine exhaust nozzles for thrust and acoustic performance under simulated takeoff conditions. Acoustic measurements had been gathered by a far-field array of microphones located along the dome wall and 10-ft above the floor. Recently, it became desirable to collect acoustic data for engine certifications (as specified by the Federal Aviation Administration (FAA)) that would simulate the noise of an aircraft taking off as heard from an offset ground location. Since nozzles for the High-Speed Civil Transport have straight sides that cause their noise signature to vary radially, an additional plane of acoustic measurement was required. Desired was an arched array of 24 microphones, equally spaced from the nozzle and each other, in a 25 off-vertical plane. The various research requirements made this a challenging task. The microphones needed to be aimed at the nozzle accurately and held firmly in place during testing, but it was also essential that they be easily and routinely lowered to the floor for calibration and servicing. Once serviced, the microphones would have to be returned to their previous location near the ceiling. In addition, there could be no structure could between the microphones and the nozzle, and any structure near the microphones would have to be designed to minimize noise reflections. After many concepts were considered, a single arched truss structure was selected that would be permanently affixed to the dome ceiling and to one end of the dome floor.

Bauman, Steven W.↗

Performance and Operational Characteristics of a Python Turbine-propeller Engine at Simulated Altitude Conditions / Carl L. Meyer and Lavern A. Johnson

The performance and operational characteristics of a Python turbine propeller engine have been investigated over a range of engine operating conditions at simulated altitudes from 5000 to 40,000 feet in the NACA Lewis altitude wind tunnel . For the performance phase of the investigation, a single cowl-inlet ram pressure ratio was maintained and independent control of engine speed and fuel flow was used to obtain a range of power at each engine speed. Engine performance data obtained at a given altitude could not be used to predict performance accurately at other altitudes by use of the standard air pressure and temperature generalizing factors. Specific fuel consumption based on shaft horsepower decreased as the shaft horsepower increased at a given engine speed. At a given altitude condition and turbine -inlet total temperature, there was an optimum engine speed at which maximum shaft horsepower was obtained. At a given engine speed and turbine-inlet total temperature, a greater portion of the total available energy was converted to propulsive power as the altitude increased. Windmilling starts were made at altitudes up to 40,000 feet; the minimum true airspeed required for successful windmilling starts increased as the altitude was raised. In general, the engine control prevented large overshoots or undershoots of engine speed during starts, accelerations, and decelerations.

Engines - Armstrong-Siddely Python Turbo-Propeller↗

Aircraft Engine Run-To-Failure Data Set Under Real Flight Conditions

The generation of data-driven prognostics models requires the availability of datasets with run-to-failure trajectories. In order to contribute to the development of these methods, the dataset provides a new realistic dataset of run-to-failure trajectories for a small fleet of aircraft engines under realistic flight conditions. The damage propagation modelling used for the generation of this synthetic dataset builds on the modelling strategy from previous work [1] and incorporates two new levels of fidelity. First, it considers real flight conditions as recorded on board of a commercial jet [2]. Secondly, it extends the degradation modelling by relating the degradation process to the operation history. The dataset was generated with the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) dynamical model [3]. More details about the generation process can be found in [4].

CMAPSS↗

Improving Thermal Management Strategies for Data Centers: A Physical Testbed Incorporating Small Modular Reactor and Microreactor Technology

This study aims to accelerate the demonstration of various thermal management systems for data centers using nuclear-generated heat to enhance energy and grid reliability. Utilizing mobile containerized and stationary test beds at INL's High Performance Computing (HPC) facility, this project integrates with various nuclear-related energy systems testing facilities. Key components include immersion cooling apparatus, absorption chillers, and adjustable thermal management simulators. Tasks involve acquiring necessary hardware, sensors, and cooling apparatus, engaging with data center industry stakeholders, and providing a testing platform for algorithms, models, tools, and software. The objective is to expedite the deployment of nuclear-powered data centers, thereby improving energy reliability and affordability.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

The DeepLynx Data Warehouse

Digital Engineering and the development of digital twins necessitate the use of highly sophisticated tools and software. These methodologies and systems bring many benefits but rely on accomplishing challenging goals such as disparate data and systems integration into a single cohesive and holistic system. Idaho National Laboratory has recently released an open-source data warehouse – DeepLynx – to help in the planning, creation, execution, and management of projects in the digital engineering space, with an emphasis on supporting digital twins in an operational space.

97 MATHEMATICS AND COMPUTING↗