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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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Spherical Coordinate Systems for Streamlining Suited Mobility Analysis

Introduction: 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. It has been shown that using a spherical coordinate system allows Anthropometry and Biomechanics Facility (ABF) personnel to increase their ability to transmit important human mobility data to engineers, in a format that is readily understandable and directly translatable to their design efforts. Objectives: The goal of this project was to use innovative 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 a new method before it was implemented in the ABF's data analysis practices. A mechanical test rig was built and tracked in 3D using an optical motion capture system. Its position and orientation were reported in both Euler and spherical reference systems. 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 rest of the joints of the body. The third stage of the project involved creating visualization methods to assist in interpreting motion in a spherical frame. These visualization methods will be incorporated in a tool to evaluate a database of suited mobility data, which is currently in development. Results: Initial results demonstrated that a spherical coordinate system is helpful in describing and visualizing the motion of a space suit. The system is particularly useful in describing the motion of the shoulder, where multiple degrees of freedom can lead to very complex motion paths.

Benson, Elizabeth↗
NASA NTRS2001

Experimental Assessment of the Emissions Control Potential of a Rich/Quench/ Lean Combustor for High Speed Civil Transport Aircraft Engines

In support of Pratt & Whitney efforts to define the Rich burn/Quick mix/Lean burn (RQL) combustor for the High Speed Civil Transport (HSCT) aircraft engine, UTRC conducted a flametube-scale study of the RQL concept. Extensive combustor testing was performed at the Supersonic Cruise (SSC) condition of an HSCT engine cycle. Data obtained from probe traverses near the exit of the mixing section confirmed that the mixing section was the critical component in controlling combustor emissions. Circular-hole configurations, which produced rapidly-, highly-penetrating jets, were most effective in limiting NO(x). The spatial profiles of NO(x) and CO at the mixer exit were not directly interpretable using a simple flow model based on jet penetration, and a greater understanding of the flow and chemical processes in this section are required to optimize it. Neither the rich-combustor equivalence ratio nor its residence time was a direct contributor to the exit NO(x). Based on this study, it was also concluded that: (1) While NO(x) formation in both the mixing section and the lean combustor contribute to the overall emission, the NOx formation in the mixing section dominates. The gas composition exiting the rich combustor can be reasonably represented by the equilibrium composition corresponding to the rich combustor operating condition. Negligible NO(x) exits the rich combustor. (2) At the SSC condition, the oxidation processes occurring in the mixing section consume 99 percent of the CO exiting the rich combustor. Soot formed in the rich combustor is also highly oxidized, with combustor exit SAE Smoke Number <3. (3) Mixing section configurations which demonstrated enhanced emissions control at SSC also performed better at part-power conditions. Data from mixer exit traverses reflected the expected mixing behavior for off-design jet to crossflow momentum-flux ratios. (4) Low power operating conditions require that the RQL combustor operate as a lean-lean combustor to achieve low CO and high efficiency. (5) An RQL combustor can achieve the emissions goal of EINO(x) = 5 at the Supersonic Cruise operating condition for an HSCT engine.

Tacina, Robert R.↗
NASA NTRS1978

Utilization of waste heat in trucks for increased fuel economy

The waste heat utilization concepts include preheating, regeneration, turbocharging, turbocompounding, and Rankine engine compounding. Predictions are based on fuel-air cycle analyses, computer simulation, and engine test data. All options are evaluated in terms of maximum theoretical improvements, but the Diesel and adiabatic Diesel are also compared on the basis of maximum expected improvement and expected improvement over a driving cycle. The study indicates that Diesels should be turbocharged and aftercooled to the maximum possible level. The results reveal that Diesel driving cycle performance can be increased by 20% through increased turbocharging, turbocompounding, and Rankine engine compounding. The Rankine engine compounding provides about three times as much improvement as turbocompounding but also costs about three times as much. Performance for either can be approximately doubled if applied to an adiabatic Diesel.

Leising, C. J.↗
DOE OSTI2013

Engineering Upgrades to the Radionuclide Aerosol Sampler/Analyzer for the CTBT International Monitoring System

The Radionuclide Aerosol Sampler/Analyzer (RASA) is an automated aerosol collection and analysis system designed by Pacific Northwest National Laboratory in the 1990’s and is deployed in several locations around the world as part of the International Monitoring System (IMS) required under the Comprehensive Nuclear-Test-Ban Treaty (CTBT). The utility of such an automated system is the reduction of human intervention and the production of perfectly uniform results. However, maintainability and down time issues threaten this utility, even for systems with over 90% data availability. Engineering upgrades to the RASA are currently being pursued to address these issues, as well as Fukushima lessons learned. Current work includes a new automation control unit, and other potential improvements such as alternative detector cooling and sampling options are under review. This paper presents the current state of upgrades and improvements under investigation

Forrester, Joel B.↗
DOE OSTI2019

Data fusion in predicting internal heat gains for office buildings through a deep learning approach

Heating, Ventilation, and Air Conditioning (HVAC) is a major energy consumer in buildings. The predictive control has demonstrated a potential to reduce HVAC energy use. To facilitate predictive HVAC control, internal heat gains prediction is required. Here, we applied Long Short-Term Memory Networks, a special form of deep neural network, to predict miscellaneous electric loads, lighting loads, occupant counts and internal heat gains in two United States office buildings. Compared with the predetermined schedules used in American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) standard 90.1, the Long Short-Term Memory Networks method could reduce the prediction errors of internal heat gains from 12% to 8% in Building A, and from 26% to 16% in Building B. It was also found that for internal heat gains prediction, miscellaneous electric loads is a more important feature than occupant counts for two reasons. First, miscellaneous electric loads is the best proxy variable for internal heat gains, as it is the major component of and has the highest correlation coefficient with the internal heat gains. Second, miscellaneous electric loads contain valuable information to predict occupant count, while occupant count could not help improve miscellaneous electric loads prediction. Lastly, these findings could help researchers and practitioners select the most relevant features to more accurately predict internal heat gains for the implementation of predictive HVAC control in buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1985

Thermal barrier coating life-prediction model development

Life predictions are made for two types of strain-tolerant and oxidation-resistant Thermal Barrier Coating (TBC) systems produced by commercial coating suppliers to the gas turbine industry. The plasma-sprayed TBC system, composed of a low-pressure plasma spray (LPPS) applied oxidation-resistant NiCrAlY bond coating and an air-plasma-sprayed yttria (8 percent) partially stabilized zirconia insulative layer, is applied by both Chromalloy and Klock. The second type of TBC is applied by the electron-beam/physical vapor deposition process by Temescal. Thermomechanical and thermochemical testing of the program TBCs is in progress. A number of the former tests has been completed. Fracture mechanics data for the Chromalloy plasma-sprayed TBC system indicate that the cohesive toughness of the zirconia layer is increased by thermal cycling and reduced by high temperature exposure at 1150 C. Eddy current technology feasibility has been established with respect to nondestructively measuring zirconia layer thickness of a TBC system. High pressure turbine blades have been coated with program TBC systems for a piggyback test in a TFE731-5 turbofan factory engine test. Data from this test will be used to validate the TBC life models.

Strangman, T. E.↗
DOE OSTI2026

Finding the missing pieces: filling gaps that impede the translation of omics data into models

High-throughput omics technologies such as DNA sequencing have made the sequencing and computational assembly of microbial genomes recovered from the environment relatively routine. Computational inference of the protein products encoded by these genomes, and the associated biochemical functions, should enable the accurate prediction and modeling of microbial metabolism, organismal interactions, and ecosystem processes. However, a lack of scalable, probabilistic protein annotation tools limits the full potential of modeling for understanding the metabolism and biogeochemical cycles of microbial communities. Our approach to improve inference of protein annotations and metabolic models relied on learning from and emulating expert manual curation, leveraging software engineering and data science best practices to scale up the throughput and accuracy of annotations and metabolic model construction, building software to objectively evaluate different annotation strategies, and more closely linking the protein annotation and metabolic model inference process. Outcomes of this research include several improved or new computational tools, including DRAM (Distilled and Refined Annotation of Metabolism) for annotating microbial genomes with protein function and metabolic traits, CAMPER (Curated Annotations for Microbial Polyphenol Enzymes and Reactions) for annotating key polyphenol metabolisms, EC-Bench for comprehensive and unbiased benchmarking of annotation tools, and several apps available via the DOE Systems Biology Knowledgebase (KBase) for building genome-scale metabolic models. We demonstrate that these tools allow us to scalably annotate and understand thousands of genomes for microbial communities from a variety of systems and test cases, including rivers, thawing permafrost, and gut microbiomes. All of these computational tools are available as open-source software, with most broadly and easily accessible to the scientific community via KBase apps.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Differential Power Processing for Ultra-Efficient Data Storage

Here this paper presents the hardware, software, and power codesign of an ultra-efficient data storage server with differential power processing (DPP). DPP can reduce the power conversion stress, improve the efficiency, and enhance the functionality of modular power electronics systems. The power inputs of a large number of hard disk drives (HDDs) were connected in series and supported by a multiport ac-coupled differential power processing (MAC-DPP) converter through a multiwinding transformer. Methods for controlling the multi-input multi-output power flow in the multiwinding transformer while avoiding core saturation were investigated. A ten-port MAC-DPP prototype with 700-W/in 3 power density was built to support a 450-W HDD storage system with ten series-stacked voltage domains. The prototype was tested on a 50-HDD server testbench, and the overall system loss is below 1 W (99.77% system efficiency). The server was able to maintain high-speed reading and writing operation of all 50 HDDs against the worst hot-swapping scenarios. A variety of hardware/software configurations and many cloud storage techniques were tested on the fully functioning server. Experimental results show that the energy efficiency of large-scale information systems (CPU/GPU clusters, memory banks, HDD arrays, etc.) can be greatly improved by software, hardware, and power codesign.

42 ENGINEERING↗
NASA NTRS1997

Providing the Persistent Data Storage in a Software Engineering Environment Using Java/COBRA and a DBMS

An investigation was undertaken to build the software foundation for the WHERE (Web-based Hyper-text Environment for Requirements Engineering) project. The TCM (Toolkit for Conceptual Modeling) was chosen as the foundation software for the WHERE project which aims to provide an environment for facilitating collaboration among geographically distributed people involved in the Requirements Engineering process. The TCM is a collection of diagram and table editors and has been implemented in the C++ programming language. The C++ implementation of the TCM was translated into Java in order to allow the editors to be used for building various functionality of the WHERE project; the WHERE project intends to use the Web as its communication back- bone. One of the limitations of the translated software (TcmJava), which militated against its use in the WHERE project, was persistent data management mechanisms which it inherited from the original TCM; it was designed to be used in standalone applications. Before TcmJava editors could be used as a part of the multi-user, geographically distributed applications of the WHERE project, a persistent storage mechanism must be built which would allow data communication over the Internet, using the capabilities of the Web. An approach involving features of Java, CORBA (Common Object Request Broker), the Web, a middle-ware (Java Relational Binding (JRB)), and a database server was used to build the persistent data management infrastructure for the WHERE project. The developed infrastructure allows a TcmJava editor to be downloaded and run from a network host by using a JDK 1.1 (Java Developer's Kit) compatible Web-browser. The aforementioned editor establishes connection with a server by using the ORB (Object Request Broker) software and stores/retrieves data in/from the server. The server consists of a CORBA object or objects depending upon whether the data is to be made persistent on a single server or multiple servers. The CORBA object providing the persistent data server is implemented using the Java progranu-ning language. It uses the JRB to store/retrieve data in/from a relational database server. The persistent data management system provides transaction and user management facilities which allow multi-user, distributed access to the stored data in a secure manner.

Dhaliwal, Swarn S.↗
NASA NTRS1987

Characteristics of Space Shuttle Main Engine failures

During development and operation of the Space Shuttle Main Engine (SSME), 27 ground test failures of sufficient severity to be termed 'major incident' have occurred. Resourecs including NASA Failure Investigation Board reports, contractor failure reports, originally recorded data, along with engineering notes, data bases, and presentations connected with the failures were available for compilation into the engine failure review presented in this paper. Most SSME failures were a result of design deficiencies stemming from inadequate definition of dynamic loads. High cycle fatigue was the most frequent mechanism leading to failure. Eighteen of the 27 failures occurred during constant power level operation. Formal board reports were not available for all failures. Therefore, the failure history presented in this paper is not complete or of uniform quality.

Cikanek, Harry A., III↗
NASA NTRS1995

Laser doppler velocimeter system for subsonic jet mixer nozzle testing at the NASA Lewis Aeroacoustic Propulsion Lab

A laser Doppler velocimeter (LDV) system developed for the Aeroacoustic Propulsion Laboratory (APL) at the NASA Lewis Research Center is described. This system was developed to acquire detailed flow field data which could be used to quantify the effectiveness of internal exhaust gas mixers (IEGM's) and to verify and calibrate computational codes. The LDV was used as an orthogonal, three component system to measure the flow field downstream of the exit of a series of IEGM's and a reference axisymmetric splitter configuration. The LDV system was also used as a one component system to measure the internal axial flow within the nozzle tailpipe downstream of the mixers. These IEGM's were designed for low-bypass ratio turbofan engines. The data were obtained at a simulated low flight speed, high-power operating condition. The optical, seeding, and data acquisition systems of the LDV are described in detail. Sample flow field measurements are provided to illustrate the capabilities of the system at the time of this test, which represented the first use of LDV at the APL. A discussion of planned improvements to the LDV is also included.

Podboy, Gary G.↗
NASA NTRS1998

Optical Instrumentation for Temperature and Velocity Measurements in Rig Turbines

Non-intrusive optical measurement techniques have been examined in the context of developing robust instruments which can routinely yield data of engineering utility in high speed turbomachinery test rigs. The engineering requirements of such a measurement are presented. Of particular interest were approaches that provide both velocity and state-variable information in order to be able to completely characterize transonic flowfields. Consideration of all of the requirements lead to the selection of particle image velocimetry (PIV) for the approach to velocity measurement while laser induced fluorescence of oxygen (O2 LIF) appeared to offer the most promise for gas temperature measurement. A PIV system was developed and demonstrated on a transonic turbine stage in the MIT blowdown turbine facility. A comprehensive data set has been taken at one flow condition. Extensive calibration established the absolute accuracy of the velocity measurements to be 3-5 %. The O2 LIF proved less successful. Although accurate for low speed flows, vibrational freezing of O2 prevented useful measurements in the transonic, 300-600 K operating range of interest here.

Ceyhan, I.↗
DOE OSTI2022

Photovoltaic System Health-State Architecture for Data-Driven Failure Detection

The timely detection of photovoltaic (PV) system failures is important for maintaining optimal performance and lifetime reliability. A main challenge remains the lack of a unified health-state architecture for the uninterrupted monitoring and predictive performance of PV systems. To this end, existing failure detection models are strongly dependent on the availability and quality of site-specific historic data. The scope of this work is to address these fundamental challenges by presenting a health-state architecture for advanced PV system monitoring. The proposed architecture comprises of a machine learning model for PV performance modeling and accurate failure diagnosis. The predictive model is optimally trained on low amounts of on-site data using minimal features and coupled to functional routines for data quality verification, whereas the classifier is trained under an enhanced supervised learning regime. The results demonstrated high accuracies for the implemented predictive model, exhibiting normalized root mean square errors lower than 3.40% even when trained with low data shares. The classification results provided evidence that fault conditions can be detected with a sensitivity of 83.91% for synthetic power-loss events (power reduction of 5%) and of 97.99% for field-emulated failures in the test-bench PV system. Finally, this work provides insights on how to construct an accurate PV system with predictive and classification models for the timely detection of faults and uninterrupted monitoring of PV systems, regardless of historic data availability and quality. Such guidelines and insights on the development of accurate health-state architectures for PV plants can have positive implications in operation and maintenance and monitoring strategies, thus improving the system’s performance.

photovoltaics↗
NASA NTRS1998

Data Mining and Optimization Tools for Developing Engine Parameters Tools

This project was awarded for understanding the problem and developing a plan for Data Mining tools for use in designing and implementing an Engine Condition Monitoring System. From the total budget of $5,000, Tricia and I studied the problem domain for developing ail Engine Condition Monitoring system using the sparse and non-standardized datasets to be available through a consortium at NASA Lewis Research Center. We visited NASA three times to discuss additional issues related to dataset which was not made available to us. We discussed and developed a general framework of data mining and optimization tools to extract useful information from sparse and non-standard datasets. These discussions lead to the training of Tricia Erhardt to develop Genetic Algorithm based search programs which were written in C++ and used to demonstrate the capability of GA algorithm in searching an optimal solution in noisy datasets. From the study and discussion with NASA LERC personnel, we then prepared a proposal, which is being submitted to NASA for future work for the development of data mining algorithms for engine conditional monitoring. The proposed set of algorithm uses wavelet processing for creating multi-resolution pyramid of the data for GA based multi-resolution optimal search. Wavelet processing is proposed to create a coarse resolution representation of data providing two advantages in GA based search: 1. We will have less data to begin with to make search sub-spaces. 2. It will have robustness against the noise because at every level of wavelet based decomposition, we will be decomposing the signal into low pass and high pass filters.

Dhawan, Atam P.↗
NASA NTRS1998

Data Mining and Optimization Tools for Developing Engine Parameters Tools

This project was awarded for understanding the problem and developing a plan for Data Mining tools for use in designing and implementing an Engine Condition Monitoring System. Tricia Erhardt and I studied the problem domain for developing an Engine Condition Monitoring system using the sparse and non-standardized datasets to be available through a consortium at NASA Lewis Research Center. We visited NASA three times to discuss additional issues related to dataset which was not made available to us. We discussed and developed a general framework of data mining and optimization tools to extract useful information from sparse and non-standard datasets. These discussions lead to the training of Tricia Erhardt to develop Genetic Algorithm based search programs which were written in C++ and used to demonstrate the capability of GA algorithm in searching an optimal solution in noisy, datasets. From the study and discussion with NASA LeRC personnel, we then prepared a proposal, which is being submitted to NASA for future work for the development of data mining algorithms for engine conditional monitoring. The proposed set of algorithm uses wavelet processing for creating multi-resolution pyramid of tile data for GA based multi-resolution optimal search.

Dhawan, Atam P.↗