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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 955 records · Page 53

Simulation, Challenge Testing and Validation of Solutions for Residential and Commercial Occupancy Sensing/Counting and CO2 Sensing (Final Report)

Carbon dioxide sensors used for monitoring and control applications in buildings are known to be sensitive to long term drift and can be affected by variations in temperature, humidity, other gas interferents, pressure and other factors that cannot be corrected through the typical auto-calibration methods often embedded in the sensor electronics. This investigation was part of the Category D defined in the ARPA-E Saving Energy Nationwide in Structures With Occupancy Recognition (SENSOR) Financial Assistance Funding Opportunity Announcement No. DE-FOA-0001737, FFDA No. 81.135, January 18, 2017. The FOA defined target criteria for the evaluation of the Category C commercial CO2 sensors selected for review and development through the ARPA-E SENSOR program and charged the Iowa State Category D team with developing an evaluation methodology for Category C sensors in accordance with these criteria. As part of the work, the Iowa State team chose to engage the standards community in the development of the evaluation methodology. Standard development work in the D22.05 Indoor Air and D22.03 Ambient Atmospheres and Source Emissions subcommittees of ASTM International Committee D22 on Air Quality on the evaluation of low cost sensors and provision of guidance for using indoor carbon dioxide concentrations to evaluate indoor air quality and ventilation is of particular relevance to the Category D efforts. To date, three draft standards with specific input by the Iowa State Category D team have passed the subcommittee balloting stage and are being balloted in December 2022 and January 2023 in the main D22 committee. In addition to the aforementioned standards to which the PI was a contributing author, intellectual property developed in this project pertaining to “An Automated System for Evaluation of the Long Term Performance of Carbon Dioxide Sensors” and “An Automated Ground Truth System for Real-Time Reliability Assessment, Capture of Control Decisions and Energy Savings Measurements for Occupancy Recognition Systems and Other Applications” are the other major deliverables of the project. These standards and the developed intellectual property are expected to benefit the public in a number of ways stemming from their provision of means to benchmark the performance of carbon dioxide and other sensor systems. In particular, there is high interest in techniques to demonstrate the performance of low-cost carbon dioxide sensors which can be used for typical HVAC applications (e.g., demand controlled ventilation, outdoor and indoor air monitoring, estimation of occupancy, etc.).

42 ENGINEERING↗

Methodology for urban rail and construction technology research and development planning

A series of transit system visits, organized by the American Public Transit Association (APTA), was conducted in which the system operators identified the most pressing development needs. These varied by property and were reformulated into a series of potential projects. To assist in the evaluation, a data base useful for estimating the present capital and operating costs of various transit system elements was generated from published data. An evaluation model was developed which considered the rate of deployment of the research and development project, potential benefits, development time and cost. An outline of an evaluation methodology that considered benefits other than capital and operating cost savings was also presented. During the course of the study, five candidate projects were selected for detailed investigation; (1) air comfort systems; (2) solid state auxiliary power conditioners; (3) door systems; (4) escalators; and (5) fare collection systems. Application of the evaluation model to these five examples showed the usefulness of modeling deployment rates and indicated a need to increase the scope of the model to quantitatively consider reliability impacts.

Rubenstein, L. D.↗

Infrared spectral studies of asteroids

The research objective was to improve the understanding of the surface mineralogy of asteroids and to link the vast existing body of meteorite geochemical data with specific astronomical objects which may be the targets of future NASA missions. The methodology used is as follow: (1) to use advanced astronomical instrumentation to obtain reflection spectra in the 0.3 to 5.2 micron wavelength range of selected asteroids; (2) to compare the asteroid data with similar data on simulated asteroid regoliths of various compositions to determine the surface mineralogy and meteoritic affinities of asteroid spectral classes and specific asteroids; (3) to integrate the mineralogical information with other astronomical data, orbital dynamics studies, and meteoritic geochemistry data to reconstruct the condensational, thermal, and collisional history of the present asteroids and their parent planetesimals; and (4) to use the information obtained to assist planning of future NASA asteroid missions such as Galileo and CRAF.

Bell, Jeffrey F.↗

Error latency measurements in symbolic architectures

Error latency, the time that elapses between the occurrence of an error and its detection, has a significant effect on reliability. In computer systems, failure rates can be elevated during a burst of system activity due to increased detection of latent errors. A hybrid monitoring environment is developed to measure the error latency distribution of errors occurring in main memory. The objective of this study is to develop a methodology for gauging the dependability of individual data categories within a real-time application. The hybrid monitoring technique is novel in that it selects and categorizes a specific subset of the available blocks of memory to monitor. The precise times of reads and writes are collected, so no actual faults need be injected. Unlike previous monitoring studies that rely on a periodic sampling approach or on statistical approximation, this new approach permits continuous monitoring of referencing activity and precise measurement of error latency.

Young, L. T.↗

Application of the Galerkin/least-squares formulation to the analysis of hypersonic flows. I - Flow over a two-dimensional ramp

An FEM for the compressible Navier-Stokes equations is introduced. The discretization is based on entropy variables. The methodology is developed within the framework of a Galerkin/least-squares formulation to which a discontinuity-capturing operator is added. Results for three test cases selected among those of the Workshop on Hypersonic Flows for Reentry Problems are presented.

Chalot, F.↗

Application of the Galerkin/least-squares formulation to the analysis of hypersonic flows. II - Flow past a double ellipse

A finite element method for the compressible Navier-Stokes equations is introduced. The discretization is based on entropy variables. The methodology is developed within the framework of a Galerkin/least-squares formulation to which a discontinuity-capturing operator is added. Results for four test cases selected among those of the Workshop on Hypersonic Flows for Reentry Problems are presented.

Chalot, F.↗

Toward Establishing a Realistic Benchmark for Airframe Noise Research: Issues and Challenges

The availability of realistic benchmark configurations is essential to enable the validation of current Computational Aeroacoustic (CAA) methodologies and to further the development of new ideas and concepts that will foster the technologies of the next generation of CAA tools. The selection of a real-world configuration, the subsequent design and fabrication of an appropriate model for testing, and the acquisition of the necessarily comprehensive aeroacoustic data base are critical steps that demand great care and attention. In this paper, a brief account of the nose landing-gear configuration, being proposed jointly by NASA and the Gulfstream Aerospace Company as an airframe noise benchmark, is provided. The underlying thought processes and the resulting building block steps that were taken during the development of this benchmark case are given. Resolution of critical, yet conflicting issues is discussed - the desire to maintain geometric fidelity versus model modifications required to accommodate instrumentation; balancing model scale size versus Reynolds number effects; and time, cost, and facility availability versus important parameters like surface finish and installation effects. The decisions taken during the experimental phase of a study can significantly affect the ability of a CAA calculation to reproduce the prevalent flow conditions and associated measurements. For the nose landing gear, the most critical of such issues are highlighted and the compromises made to resolve them are discussed. The results of these compromises will be summarized by examining the positive attributes and shortcomings of this particular benchmark case.

Khorrami, Mehdi R.↗

Space-Time Data fusion for Remote Sensing Applications

NASA has been collecting massive amounts of remote sensing data about Earth's systems for more than a decade. Missions are selected to be complementary in quantities measured, retrieval techniques, and sampling characteristics, so these datasets are highly synergistic. To fully exploit this, a rigorous methodology for combining data with heterogeneous sampling characteristics is required. For scientific purposes, the methodology must also provide quantitative measures of uncertainty that propagate input-data uncertainty appropriately. We view this as a statistical inference problem. The true but notdirectly- observed quantities form a vector-valued field continuous in space and time. Our goal is to infer those true values or some function of them, and provide to uncertainty quantification for those inferences. We use a spatiotemporal statistical model that relates the unobserved quantities of interest at point-level to the spatially aggregated, observed data. We describe and illustrate our method using CO2 data from two NASA data sets.

carbon dioxide↗

Application of Adjoint Methodology in Various Aspects of Sonic Boom Design

One of the advances in computational design has been the development of adjoint methods allowing efficient calculation of sensitivities in gradient-based shape optimization. This paper discusses two new applications of adjoint methodology that have been developed to aid in sonic boom mitigation exercises. In the first, equivalent area targets are generated using adjoint sensitivities of selected boom metrics. These targets may then be used to drive the vehicle shape during optimization. The second application is the computation of adjoint sensitivities of boom metrics on the ground with respect to parameters such as flight conditions, propagation sampling rate, and selected inputs to the propagation algorithms. These sensitivities enable the designer to make more informed selections of flight conditions at which the chosen cost functionals are less sensitive.

Rallabhandi, Sriram K.↗

Transition Modeling Based on the Dual N-factor Method for the CRM-NLF Wind Tunnel Configuration

The dual N-factor method is used to model the boundary-layer transition over the common research model with natural laminar flow (CRM-NLF) aircraft configuration. The flow conditions match selected test conditions from a wind tunnel experiment in the National Transonic Facility at the NASA Langley Research Center. The paper presents a systematic methodology for transition prediction in the presence of a dual shock system and extends the prior capability for iteratively coupled computational fluid dynamics (CFD) predictions to incorporate three-dimensional, transonic wings. The method employs stability computations based on the linear parabolized stability equations (PSE), along with a dual N-factor criterion. The iterative process begins with the fully turbulent Reynolds-averaged-Navier-Stokes (RANS) mean flow solution. For the first iteration, a mean flow solution is calculated with an imposed transition front that aligns with the shock front from the fully turbulent solution. Subsequently, stability computations are performed along a set of streamlines across the wing to calculate the amplification of planar Tollmien-Schlichting (TS) and stationary crossflow (CF) modes. The transition criterion based on the dual N-factor method is used to infer the updated transition front and the process is successively repeated until convergence of the solution. Within three iterations, the predicted fronts for angles of attack of 1.45, 1.98, 2.46 and 2.94 degrees and a mean-aerodynamic-chord Reynolds number equal to 15 million, approach visual convergence in most regions of the studied cases, and the resulting predictions are in good agreement with the transition fronts deduced from measurements of temperature-sensitive paint. Even though surface pressure measurements based on fully-turbulent flow agree well with the measured pressure coefficient distributions, strong viscous-inviscid interaction effects cause significant shifts in the shock locations based on the imposed transition front, underscoring the intrusive nature of static pressure measurements using surface mounted ports on the CRM-NLF configuration.

Boundary Layer Transition↗

Definition of NASTRAN sets by use of parametric geometry

Many finite element preprocessors describe finite element model geometry with points, lines, surfaces and volumes. One method for describing these basic geometric entities is by use of parametric cubics which are useful for representing complex shapes. The lines, surfaces and volumes may be discretized for follow on finite element analysis. The ability to limit or selectively recover results from the finite element model is extremely important to the analyst. Equally important is the ability to easily apply boundary conditions. Although graphical preprocessors have made these tasks easier, model complexity may not lend itself to easily identify a group of grid points desired for data recovery or application of constraints. A methodology is presented which makes use of the assignment of grid point locations in parametric coordinates. The parametric coordinates provide a convenient ordering of the grid point locations and a method for retrieving the grid point ID's from the parent geometry. The selected grid points may then be used for the generation of the appropriate set and constraint cards.

Baughn, Terry V.↗

Design of an Integrated Solids Handling System to Maximize Syngas Process Reliability (Cooperative Research and Development Final Report)

The National Renewable Energy Laboratory (NREL), in partnership with Wonderful Renewable Energy (WRE) and Idaho National Laboratory (INL), plans to develop a general methodology for designing integrated biorefinery solids preprocessing, handling, and feeding systems based on the chemical, physical, and mechanical attributes of the starting biomass material. This attribute-driven approach will include detailed feedstock property measurements, iterative computational modeling, and bench-scale testing to design systems for preprocessing, handling, and reactor in-feed, up to and including the selection of the conversion reactor. The initial tests and system design will be conducted using waste material from almond and pistachio growing and production operations (shells, hulls, and wood), targeting the conversion of this material to syngas for electricity production. The methodology will then be generalized to other feedstocks. The purpose of this project is to design an integrated solids handling system to maximize the process reliability of converting almond and pistachio waste to electricity. The design methodology and workflow developed from this example will then be applied to the Feedstock Conversion Interface Consortium (FCIC) benchmark loblolly pine residues, thus demonstrating the robustness of the overall design approach and providing insight and guidance for future conversion systems. V-Grid Energy Systems was brought on as a subcontractor to provide gasifiers and labor to complete gasifier runs.

09 BIOMASS FUELS↗

Characterization of a selective, zero power sensor for distributed sensing of hydrogen in energy applications

The use of hydrogen as a clean and renewable energy source is increasing rapidly for both vehicle and stationary applications. There are safety concerns for the locations in which hydrogen is made, used, and transported (i.e., pipelines and tanker trucks). Sensors are needed to comply with safety regulations and to enable a smooth and safe rollout of hydrogen as an alternative energy. However, hydrogen sensors do not yet exist that have the combined features of small size and low power for easy deployment coupled with high-volume manufacturability and low cost. This is necessary to accommodate the emerging fixed and mobile markets while retaining critical metrological metrics, including measurement range, detection limits, selectivity, fast response, stability, and long lifetime. An amperometric gas sensor for hydrogen (AGS) has been developed using an innovative manufacturing method. The sensor was designed using scalable fabrication strategies based on “Printed Electronics” (PE) methodology which are compatible with large-scale production. Prototype sensors were batch fabricated with multiple individual elements on a substrate compatible in size with a standard 8-inch wafer to enable high-volume, low-cost manufacturing, thereby leveraging PE and semiconductor fabrication infrastructure. This novel AGS was instrumented with control circuitry and evaluated for hydrogen detection in the range of 0–5000 ppmv H2 in air. Specific performance evaluations included assessment of the sensor measurement range, repeatability, and selectivity.

08 HYDROGEN↗

Ares I-X Launch Abort System, Crew Module, and Upper Stage Simulator Vibroacoustic Flight Data Evaluation, Comparison to Predictions, and Recommendations for Adjustments to Prediction Methodology and Assumptions

The National Aeronautics and Space Administration (NASA) Constellation Program (CxP) has identified a series of tests to provide insight into the design and development of the Crew Launch Vehicle (CLV) and Crew Exploration Vehicle (CEV). Ares I-X was selected as the first suborbital development flight test to help meet CxP objectives. The Ares I-X flight test vehicle (FTV) is an early operational model of CLV, with specific emphasis on CLV and ground operation characteristics necessary to meet Ares I-X flight test objectives. The in-flight part of the test includes a trajectory to simulate maximum dynamic pressure during flight and perform a stage separation of the Upper Stage Simulator (USS) from the First Stage (FS). The in-flight test also includes recovery of the FS. The random vibration response from the ARES 1-X flight will be reconstructed for a few specific locations that were instrumented with accelerometers. This recorded data will be helpful in validating and refining vibration prediction tools and methodology. Measured vibroacoustic environments associated with lift off and ascent phases of the Ares I-X mission will be compared with pre-flight vibration predictions. The measured flight data was given as time histories which will be converted into power spectral density plots for comparison with the maximum predicted environments. The maximum predicted environments are documented in the Vibroacoustics and Shock Environment Data Book, AI1-SYS-ACOv4.10 Vibration predictions made using statistical energy analysis (SEA) VAOne computer program will also be incorporated in the comparisons. Ascent and lift off measured acoustics will also be compared to predictions to assess whether any discrepancies between the predicted vibration levels and measured vibration levels are attributable to inaccurate acoustic predictions. These comparisons will also be helpful in assessing whether adjustments to prediction methodologies are needed to improve agreement between the predicted and measured flight data. Future assessment will incorporate hybrid methods in VAOne analysis (i.e., boundary element methods, BEM and finite element methods, FEM). These hybrid methods will enable the ability to import NASTRAN models providing much more detailed modeling of the underlying beams and support structure of the ARES 1-X test vehicle. Measured acoustic data will be incorporated into these analyses to improve correlation for additional post flight analysis.

Smith, Andrew↗

Evaluation of Suitability of Selected Set of Coal Plant Sites for Repowering with Small Modular Reactors

This report summarizes the approach that ORNL developed for screening a sample set of small coal stations for possible repowering with SMRs; the methodology employed, including spatial modeling; and initial results for these sample plants. The objective in conducting this type of siting evaluation is to demonstrate the capability to characterize specific sample coal plant sites to identify any particular issues associated with repowering existing coal stations with SMRs using OR-SAGE; it is not intended to be a definitive assessment per se as to the absolute suitability of any particular site.

Coal↗

Evaluation of Select Heat and Pressure Measurement Gauges for Potential Use in the NRC/OECD High Energy Arc Fault (HEAF) Test Program

In an effort to improve the current state of the art in fire probabilistic risk assessment methodology, the U.S. Nuclear Regulatory Commission, Office of Regulatory Research, contracted Sandia National Laboratories (SNL) to conduct a series of scoping tests to identify thermal and mechanical probes that could be used to characterize the zone of influence (ZOI) during high energy arc fault (HEAF) testing. For the thermal evaluation, passive and active probes were exposed to HEAF-like heat fluxes for a period of 2 seconds at the SNL's National Solar Thermal Test Facility to determine their ability to survive and measure such an extreme environment. Thermal probes tested included temperature lacquers (passive), NANMAC thermocouples, directional flame thermometers, modified plate thermometers, infrared temperature sensors, and a Gardon heat flux gauge. Similarly, passive and active pressure probes were evaluated by exposing them to pressures resulting from various high-explosive detonations at the Sandia Terminal Ballistic Facility. Pressure probes included bikini pressure gauges (passive) and pressure transducers. Results from these tests provided good insight to determine which probes should be considered for use during future HEAF testing.

47 OTHER INSTRUMENTATION↗

Structural Analysis Methodology for Space Deployable Structures Using Multi-Body Dynamic Solver

The purpose of this paper is to provide detailed structural analysis implementation for space deployable structures using a multi-body dynamic solver. The selected commercial code is MSC/ADAMS. Four benchmark problems are used to evaluate mechanism motion, frictional contacts, and geometrically non-linear large deformation. This paper examines the software functionality, performance, accuracy and ability to solve the benchmark problems. The discussions covered are related to solver convergence, tracking internal force, velocity and acceleration of different parts in each model and comparing results to closed form solutions if available.

Montazersadgh, Farzin↗

A novel active optimization approach for rapid and efficient design space exploration using ensemble machine learning

In this work, a novel design optimization technique based on active learning, which involves dynamic exploration and exploitation of the design space of interest using an ensemble of machine learning algorithms, is presented. In this approach, a hybrid methodology incorporating an explorative weak learner (regularized basis function model) which fits high-level information about the response surface, and an exploitative strong learner (based on committee machine) that fits finer details around promising regions identified by the weak learner, is employed. For each design iteration, an aristocratic approach is used to select a set of nominees, where points that meet a threshold merit value as predicted by the weak learner are selected to be evaluated using expensive function evaluation. In addition to these points, the global optimum as predicted by the strong learner is also evaluated to enable rapid convergence to the actual global optimum once the most promising region has been identified by the optimizer. This methodology is first tested by applying it to the optimization of a two-dimensional multi-modal surface. The performance of the new active learning approach is compared with traditional global optimization methods, namely micro-genetic algorithm (pGA) and particle swarm optimization (PSO). It is demonstrated that the new optimizer is able to reach the global optimum much faster with a significantly fewer number of function evaluations. Subsequently, the new optimizer is also applied to a complex internal combustion (IC) engine combustion optimization case with nine control parameters related to fuel injection, initial thermodynamic conditions, and in-cylinder flow. It is again found that the new approach significantly lowers the number of function evaluations that are needed to reach the optimum design configuration (by up to 80%) when compared to particle swarm and genetic algorithm-based optimization techniques.

Machine learning, active learning, design optimiza↗