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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 793 records · Page 44

Sensor Data Qualification Technique Applied to Gas Turbine Engines

This paper applies a previously developed sensor data qualification technique to a commercial aircraft engine simulation known as the Commercial Modular Aero-Propulsion System Simulation 40,000 (C-MAPSS40k). The sensor data qualification technique is designed to detect, isolate, and accommodate faulty sensor measurements. It features sensor networks, which group various sensors together and relies on an empirically derived analytical model to relate the sensor measurements. Relationships between all member sensors of the network are analyzed to detect and isolate any faulty sensor within the network.

control↗

Trades Between Opposition and Conjunction Class Trajectories for Early Human Missions to Mars

Candidate human missions to Mars, including NASA's Design Reference Architecture 5.0, have focused on conjunction-class missions with long crewed durations and minimum energy trajectories to reduce total propellant requirements and total launch mass. However, in order to progressively reduce risk and gain experience in interplanetary mission operations, it may be desirable that initial human missions to Mars, whether to the surface or to Mars orbit, have shorter total crewed durations and minimal stay times at the destination. Opposition-class missions require larger total energy requirements relative to conjunction-class missions but offer the potential for much shorter mission durations, potentially reducing risk and overall systems performance requirements. This paper will present a detailed comparison of conjunction-class and opposition-class human missions to Mars vicinity with a focus on how such missions could be integrated into the initial phases of a Mars exploration campaign. The paper will present the results of a trade study that integrates trajectory/propellant analysis, element design, logistics and sparing analysis, and risk assessment to produce a comprehensive comparison of opposition and conjunction exploration mission constructs. Included in the trade study is an assessment of the risk to the crew and the trade offs between the mission duration and element, logistics, and spares mass. The analysis of the mission trade space was conducted using four simulation and analysis tools developed by NASA. Trajectory analyses for Mars destination missions were conducted using VISITOR (Versatile ImpulSive Interplanetary Trajectory OptimizeR), an in-house tool developed by NASA Langley Research Center. Architecture elements were evaluated using EXploration Architecture Model for IN-space and Earth-to-orbit (EXAMINE), a parametric modeling tool that generates exploration architectures through an integrated systems model. Logistics analysis was conducted using NASA's Human Exploration Logistics Model (HELM), and sparing allocation predictions were generated via the Exploration Maintainability Analysis Tool (EMAT), which is a probabilistic simulation engine that evaluates trades in spacecraft reliability and sparing requirements based on spacecraft system maintainability and reparability.

Mattfeld, Bryan↗

Mechanical Properties and Real-Time Damage Evaluations of Environmental Barrier Coated SiC/SiC CMCs Subjected to Tensile Loading Under Thermal Gradients

SiC/SiC ceramic matrix composites (CMCs) require new state-of-the art environmental barrier coatings (EBCs) to withstand increased temperature requirements and high velocity combustion corrosive combustion gasses. The present work compares the response of coated and uncoated SiC/SiC CMC substrates subjected to simulated engine environments followed by high temperature mechanical testing to asses retained properties and damage mechanisms. Our focus is to explore the capabilities of electrical resistance (ER) measurements as an NDE technique for testing of retained properties under combined high heat-flux and mechanical loading conditions. Furthermore, Acoustic Emission (AE) measurements and Digital Image Correlation (DIC) were performed to determine material damage onset and accumulation.

Ceramic matrix composites↗

Airborne Observation of the Hayabusa Sample Return Capsule Re-Entry

NASA Ames Research Center and the SETI Institute collaborated on an effort to observe the Earth re-entry of the Japan Aerospace Exploration Agency's Hayabusa sample return capsule. Hayabusa was an asteroid exploration mission that retrieved a sample from the near-Earth asteroid Itokawa. Its sample return capsule re-entered over the Woomera Prohibited Area in southern Australia on June 13, 2010. Being only the third sample return mission following NASA's Genesis and Stardust missions, Hayabusa's return was a rare opportunity to collect aerothermal data from an atmospheric entry capsule returning at superorbital speeds. NASA deployed its DC-8 airborne laboratory and a team of international researchers to Australia for the re-entry. For approximately 70 seconds, spectroscopic and radiometric imaging instruments acquired images and spectra of the capsule, its wake, and destructive re-entry of the spacecraft bus. Once calibrated, spectra of the capsule will be interpreted to yield data for comparison with and validation of high fidelity and engineering simulation tools used for design and development of future atmospheric entry system technologies. A brief summary of the Hayabusa mission, the preflight preparations and observation mission planning, mission execution, and preliminary spectral data are documented.

Spectroscopy↗

NASA Hybrid Wing Aircraft Aeroacoustic Test Documentation Report

This report summarizes results of the Hybrid Wing Body (HWB) N2A-EXTE model aeroacoustic test. The N2A-EXTE model was tested in the NASA Langley 14- by 22-Foot Subsonic Tunnel (14x22 Tunnel) from September 12, 2012 until January 28, 2013 and was designated as test T598. This document contains the following main sections: Section 1 - Introduction, Section 2 - Main Personnel, Section 3 - Test Equipment, Section 4 - Data Acquisition Systems, Section 5 - Instrumentation and Calibration, Section 6 - Test Matrix, Section 7 - Data Processing, and Section 8 - Summary. Due to the amount of material to be documented, this HWB test documentation report does not cover analysis of acquired data, which is to be presented separately by the principal investigators. Also, no attempt was made to include preliminary risk reduction tests (such as Broadband Engine Noise Simulator and Compact Jet Engine Simulator characterization tests, shielding measurement technique studies, and speaker calibration method studies), which were performed in support of this HWB test. Separate reports containing these preliminary tests are referenced where applicable.

Heath, Stephanie L.↗

Automatic Incorporation of Flaws into Cad and FEA Models Based On Measured NDE Data

Automatic incorporation of non-destructive evaluation (NDE) data into CAD and finite element (FE) models for structural analysis is essential for accurate residual-life and strength analyses of composite structures. Currently, two significant but independent challenges exist for incorporating NDE data in such analyses: interpretation of the NDE signals to locate and characterize the structural defects and the incorporation of that information into structural analysis tools. The first challenge will be addressed through linear inversion of calculated synthetic responses generated by a simulation engine to evaluate flaw size, location, and other characteristics. The second challenge will be addressed by building on prior and parallel defect modeling efforts to integrate suitable flaw models into the CAD/finite-element representation of a specimen. Ultrasonic NDE information is usually represented using C-Scans of time-of-flight or intensity information. Other modalities such as thermography and computed tomography (CT) could also be used to characterize the structure. This information will first be projected into material coordinates and then aligned with the specimen’s finite element mesh. The NDE data can then be incorporated by inserting flaw geometry into the CAD and FE analysis model and automatic modification of local material properties and boundary conditions. This process will enable the use of structural analysis tools even for practical modalities such as ultrasound and thermography which may not directly give accurate-enough geometric information to fully define the flaw. The full flaw characteristics will be inferred using prior expert and modeling knowledge to categorize flaw signatures. Outputs for this project will include demonstrated methods for creating structural analysis geometric models that incorporate flaw characterization information; these models can then be used directly in popular commercial FEA software. In addition, the primary deliverable for the project will include a software that will be able to automatically incorporate different kinds of flaws into an existing FE models. The models will be generated in standard file formats to enable direct import into the analysis software.

Adarsh Krishnamurthy↗

Noise Exposure Maps of Urban Air Mobility

A noise exposure map is “a scaled geographic depiction of an airport, its noise exposure contours, noise-sensitive facilities, and land uses in the airport surrounding area” developed in accordance with the FAA’s 14 Code of Federal Regulation Part 150. This paper is the first to explore the applicability of airport noise exposure maps to Urban Air Mobility (UAM). The FAA’s airport noise compatibility planning program is first described. Then the applicability of the noise exposure map to Urban Air Mobility (UAM) is explored. Finally, new airspace infrastructure, including vertiport locations and UAM routes from NASA’s UAM engineering simulations, and local noise-sensitive facility locations and land use information were collected and processed to develop the noise exposure maps of UAM near the Dallas-Fort Worth area. The DNL noise contours resulting from a six-passenger electric quadrotor prototype vehicle are predicted using NASA’s AIRNOISEUAM software. The noise exposure maps of UAM are generated automatically using Python’s data analysis and visualization libraries. The results have applications for UAM’s noise compatibility planning, noise-reducing route planning, and vertiport location selection

Urban Air Mobility↗

Noise Exposure Map of Urban Air Mobility

A noise exposure map is “a scaled geographic depiction of an airport, its noise exposure contours, noise-sensitive facilities, and land uses in the airport surrounding area” developed in accordance with the FAA’s 14 Code of Federal Regulation Part 150. This paper is the first to explore the applicability of airport noise exposure maps to Urban Air Mobility (UAM). The FAA’s airport noise compatibility planning program is first described. Then the applicability of the noise exposure map to Urban Air Mobility (UAM) is explored. Finally, new airspace infrastructure, including vertiport locations and UAM routes from NASA’s UAM engineering simulations, and local noise-sensitive facility locations and land use information were collected and processed to develop the noise exposure maps of UAM near the Dallas-Fort Worth area. The DNL noise contours resulting from a six-passenger electric quadrotor prototype vehicle are predicted using NASA’s AIRNOISEUAM software. The noise exposure maps of UAM are generated automatically using Python’s data analysis and visualization libraries. The results have applications for UAM’s noise compatibility planning, noise-reducing route planning, and vertiport location selection. (To hear the voice please utilize the video uploaded to the record)

Urban Air Mobility↗

Navigation Sensor Technology Assessment Capability for Data-Driven Systems Analysis

The capability to assess the mission performance of novel navigation technologies from a systems-level approach and to provide quantitative results is crucial. With growing interest and innovations from NASA’s commercial partners, data-driven results that quantify the technological impact will guide research developments and facilitate stakeholder decision-making while requiring less time and resources. This paper presents a method to evaluate various sensor combinations and their impact on the overall system performance using an existing six degrees-of-freedom, physics-based engineering simulation for a government reference lunar lander as a testbed. Selected navigation technologies over various technology readiness levels, including Inertial Measurement Units, Navigation Doppler Lidar, and radar altimeter-radar velocimeter, were studied in this paper. Results using this testbed to perform sensitivity studies and to provide quantitative assessments are reported. One key finding is that there are diminishing returns for reducing sensor errors. The most influential sensor parameter to landing success are vehicle configuration and mission dependent. Results from this method could be used by stakeholders to make data-driven systems-based decisions and by technology developers as guidance for the specific parameter improvements that will have the most significant impact on mission success. This capability could be further used to assess alternative scenarios should one type of technology become unavailable or to re-assess initial assumptions and identify appropriate requirements from a system perspective.

Esther Lee↗

A High Performance Computing Platform for Performing High-Volume Studies With Windows-based Power Grid Tools

Serial Windows-based programs are widely used in power utilities. For applications that require high volume simulations, the single CPU runtime can be on the order of days or weeks. The lengthy runtime, along with the availability of low cost hardware, is leading utilities to seriously consider High Performance Computing (HPC) techniques. However, the vast majority of the HPC computers are still Linux-based and many HPC applications have been custom developed external to the core simulation engine without consideration for ease of use. This has created a technical gap for applying HPC-based tools to today’s power grid studies. To fill this gap and accelerate the acceptance and adoption of HPC for power grid applications, this paper presents a prototype of generic HPC platform for running Windows-based power grid programs on Linux-based HPC environment. The preliminary results show that the runtime can be reduced from weeks to hours to improve work efficiency.

High-performance computing, power grid, power syst↗

Autotune

The Autotune software code uses an island-based evolutionary algorithm to solve multi-objective optimization problems. For the code provided, this has been applied to the whole-building simulation engine EnergyPlus to allow a software description of a building to be calibrated to measured data.

Joshua New, Aaron Garrett↗

Henson v1.0

Modern scientific and engineering simulations track the time evolution of billions of elements. For such large runs, storing most time steps for later analysis is not a viable strategy. It is far more efficient to analyze the simulation data while it is still in memory. The developers present a novel design for running multiple codes in situ: using coroutines and position-independent executables they enable cooperative multitasking between simulation and analysis, allowing the same executables to post-process simulation output, as well as to process it on the fly, both in situ and in transit. They present Henson, an implementation of our design, and illustrate its versatility by tackling analysis tasks with different computational requirements. Our design differs significantly from the existing frameworks and offers an efficient and robust approach to integrating multiple codes on modern supercomputers. The presented techniques can also be integrated into other in situ frameworks.

Monozov, Dmitriy↗

Commercial Building Energy Saver, API

The CBES API provides Application Programming Interface to a suite of functions to improve energy efficiency of buildings, including building energy benchmarking, preliminary retrofit analysis using a pre-simulation database DEEP, and detailed retrofit analysis using energy modeling with the EnergyPlus simulation engine. The CBES API is used to power the LBNL CBES Web App. It can be adopted by third party developers and vendors into their software tools and platforms.

Hong, Tianzhen↗

A SIMPLIFIED ENERGY MODELING APPROACH FOR BUILDINGS

This paper introduces simplified energy modeling (SEM) approaches using DOE2 and EnergyPlus and proposes a validation method for simplified energy modeling. Simplified energy modeling can allow more design teams and owners to leverage the power of energy modeling to inform their designs and lead to greater energy savings and a lower first cost because the technologies and design strategies can be thoroughly tested against models before the decisions are made. By starting a discussion on how to develop simplified energy modeling approaches and methods to validate results, we hope to increase innovation in energy modeling software while decreasing variation between modelers. Simplified modeling is not yet widely accepted because it is unclear if the simplifications reduce the accuracy of the results. By starting an industry dialogue on a testing method for these modeling approaches, we hope to aid adoption of more streamlined tools when they can be shown to provide similar accuracy to more detailed tools. This paper proposes a method to test simplified energy modeling programs against the DOE prototype buildings. It builds on the testing procedure established for simulation engines by ASHRAE Standard 140. By comparing whole building and end use results from the accepted prototype buildings to any simplified modeling approach across multiple building types and climate zones we can determine if the simplifications create unwarranted error. We will present the SEM approach and results for a case study validation for a sample building types in 16 US climate zones from two such simplified energy modeling tools.

Energy Modeling, 90.1 Appendix G, Asset Score Tool↗

Experimental Studies and Energy Modeling for Evaluating Performance of Various Deep Wall Retrofits

The Pacific Northwest National Laboratory, Oak Ridge National Laboratory, and the University of Minnesota conducted a three-year, multipart study on residential retrofit wall assemblies. The project, which was funded by the U.S. Department of Energy’s Building Technology Office, aimed to compare a range of residential wall retrofit systems that prioritized affordability, durability, and energy savings potential. The research team identified, constructed, tested, simulated, and analyzed the feasibility and economics of 16 wall retrofit assemblies (14 test configurations and two baseline configurations) that can be applied to the exterior side of existing walls (either with or without the existing cladding). The 16 wall assemblies were installed in an in-situ laboratory environment, to evaluate the ease of construction and study the thermal and hygrothermal performance of the walls. This paper presents the methodology used to evaluate the thermal performance of the walls and discusses the energy modeling results of the study. The results from the experiments were used to calibrate a THERM model of each wall assembly, which was then applied to a whole building using the EnergyPlus 8.6 simulation engine. A residential prototype building was used to extrapolate whole-building energy savings in each U.S. climate zone. To capture the conditions of the largest number of homes in the United States, the most frequent building characteristics (e.g., attic insulation level, window specifications, foundation insulation, etc.) were extracted from ResStock data and applied to the prototype model. Results from the energy modeling showed that the climate zones with the highest potential for retrofit savings are those which are heating-dominated (i.e., Cold and Very Cold climate designations). In these climate zones, heating and cooling energy savings due to the wall retrofits alone ranged from 21.5% to 38.2%.

Nagda, Harshil↗

Subsidence Risk Mitigation in LLW Final Covers: A Case History - 18286

Typical waste packaging and disposal practices at low-level radioactive waste (LLW) disposal facilities, while adequate for safe transportation and facility operations, introduce significant subsidence risk for the facilities' final cover systems. Subsidence is often caused by the collapse of voids in the waste packaging and surrounding cover soils that eventually propagate to the ground surface. This subsidence could result in the loss of final cover system integrity, stormwater ponding, concentrated flow of surface water and/or gas, increased leachate generation, transport of contaminants from the landfill, and potential adverse chemical reactions within the waste mass. For new LLW facilities, steps can be taken to minimize the subsidence potential of newly placed waste. However, there is a significant inventory of existing disposal facilities (trenches, pits, shafts, vaults, etc.), tank farms, and historic, subsurface burial grounds that require final covers - all of which present real subsidence risks. Final covers for these existing LLW disposal sites can be engineered to mitigate these risks. A case history of a 60-acre LLW final cover system design and construction project illustrates an innovative approach to this problem that offers superior risk mitigation compared to typical final cover design practice. This approach combines engineering simulations of the projected final cover mechanical performance, specific probabilistic performance targets, and targeted cover system improvements to manage the subsidence risk in the final design. The result is a successful final cover project that meets the needs of the community, state and federal regulators, and facility owner. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Integration of Decentralized Graph-Based Multi-Agent Reinforcement Learning with Digital Twin for Traffic Signal Optimization

Machine learning (ML) methods, particularly Reinforcement Learning (RL), have gained widespread attention for optimizing traffic signal control in intelligent transportation systems. However, existing ML approaches often exhibit limitations in scalability and adaptability, particularly within large traffic networks. This paper introduces an innovative solution by integrating decentralized graph-based multi-agent reinforcement learning (DGMARL) with a Digital Twin to enhance traffic signal optimization, targeting the reduction of traffic congestion and network-wide fuel consumption associated with vehicle stops and stop delays. In this approach, DGMARL agents are employed to learn traffic state patterns and make informed decisions regarding traffic signal control. The integration with a Digital Twin module further facilitates this process by simulating and replicating the real-time asymmetric traffic behaviors of a complex traffic network. The evaluation of this proposed methodology utilized PTV-Vissim, a traffic simulation software, which also serves as the simulation engine for the Digital Twin. The study focused on the Martin Luther King (MLK) Smart Corridor in Chattanooga, Tennessee, USA, by considering symmetric and asymmetric road layouts and traffic conditions. Comparative analysis against an actuated signal control baseline approach revealed significant improvements. Experiment results demonstrate a remarkable 55.38% reduction in Eco_PI, a developed performance measure capturing the cumulative impact of stops and penalized stop delays on fuel consumption, over a 24 h scenario. In a PM-peak-hour scenario, the average reduction in Eco_PI reached 38.94%, indicating the substantial improvement achieved in optimizing traffic flow and reducing fuel consumption during high-demand periods. These findings underscore the effectiveness of the integrated DGMARL and Digital Twin approach in optimizing traffic signals, contributing to a more sustainable and efficient traffic management system.

actuated signal control↗

Large eddy simulation of a reacting spray flame with multiple realizations under compression ignition engine conditions

An n-dodecane spray flame (Spray A from Engine Combustion Network) was simulated using a detailed combustion model along with a dynamic structure LES model to evaluate its performance at engine-relevant conditions and understand the transient behavior of this turbulent flame. The liquid spray was treated with a traditional Lagrangian method and the gas-phase reaction was modeled using a detailed combustion model. A 103-species skeletal mechanism was used for the n-dodecane chemical kinetic model. Significantly different flame structures and ignition processes are observed for the LES compared to those of RANS predictions. The LES data suggests that the first ignition initiates in lean mixture and propagates to rich mixture, and the main ignition happens in rich mixture, preferable less than 0.14 in mixture fraction space. LES was observed to have multiple ignition spots in the mixing layer simultaneously while the main ignition initiates in a clearly asymmetric fashion. The temporal flame development also indicates the flame stabilization mechanism is auto-ignition controlled and modulated by flame propagation. Soot predictions by LES present much better agreement with experiments compared to RANS both qualitatively and quantitatively. Multiple realizations for LES were performed to understand the realization to realization variation and to establish best practices for ensemble-averaging diesel spray flames. The relevance index analysis suggests that an average of 2 and 5 realizations can reach 99\% of similarity to the target average of 16 realizations on the temperature and mixture fraction fields, respectively. However, more realizations are necessary for OH and soot mass fraction due to their high fluctuations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗