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At least 487 records · Page 27

Effect of anisotropic mesh adaptation on surface pressure predictions for atmospheric entry simulations.

Recently, a metric-based mesh adaptation capability has been developed for the advanced compressible flow solver US3D. Metric-based mesh adaptation is a solution informed mesh adaptation strategy that typically improves the resolution of the mesh along anisotropic flow features, like strong shock waves or shear layers. An anisotropic error indicator is reconstructed based on a provided Computational Fluid Dynamics (CFD) solution which prescribes the locally desired element size and orientation. The benefits of this mesh adaptation strategy is twofold: first, it simplifies the manual meshing labor that typically needs to be carried out by the CFD engineer because the mesh adaptation is informed by the provided solution. Second, the computational cost is kept to a minimum while improving the resolution of the simulation. The aim here is to demonstrate how anisotropic mesh adaptation can be employed to improve the predictions of surface pressure for atmospheric entry vehicles. In this work, we compare CFD simulations that use this newly developed anisotropic mesh adaptation capability for US3D with pressure data that was collected by Mars Entry, Descent, and Landing Instrumentation 2 (MEDLI2) during the atmospheric entry phase of Mars2020.

D. Ekelschot↗

Effect of Anisotropic Mesh Adaptation on Surface Pressure Predictions for Atmospheric Entry Simulations

A metric-based mesh adaptation capability has been developed for the advanced compressible flow solver US3D. Metric-based mesh adaptation is a solution informed mesh adaptation strategy that improves the resolution of the mesh along anisotropic flow features, like strong shock waves or shear layers. An anisotropic error indicator is reconstructed based on a provided Computational Fluid Dynamics (CFD) solution which prescribes the locally desired element size and orientation. The benefits of this mesh adaptation strategy is twofold: first, it simplifies the manual meshing labor that typically needs to be carried out by the CFD engineer because the mesh adaptation is informed by the provided solution. Second, the computational cost is kept to a minimum while improving the resolution of the simulation. The aim here is to demonstrate how anisotropic mesh adaptation can be employed to improve the predictions of surface pressure for atmospheric entry vehicles. In this work, we compare CFD simulations that use this newly developed anisotropic mesh adaptation capability for US3D with pressure data that was collected by Mars Entry, Descent, and Landing Instrumentation (MEDLI2) suite.

Dirk Ekelschot↗

Validation of Artemis I Aerothermal Design Models Using Developmental Flight Instrumentation

The inaugural flight of the Space Launch System (SLS) Block 1 launch vehicle, Artemis I, occurred on November 16, 2022, and featured a full suite of Developmental Flight Instrumentation (DFI) that provided aerothermodynamic measurements to assess thermal design and substantiate aerothermodynamic models. The Block 1 launch vehicle aerothermal instrumentation consisted of approximately 277 aerothermal gauges mounted throughout the Orion Multi-Purpose Crew Vehicle (MPCV), Integrated Spacecraft and Payload Element (ISPE), Core Stage (CS) and Solid Rocket Boosters (SRB) and an additional 179 thermal gauges on the Orion Crew Module (CM). Instrumentation included calorimeters, radiometers, pressure transducers, gas temperature probes, and thermocouples. Data was collected from lift-off through CS Main Engine Cut-Off (MECO). The flight data was invaluable for determining aerothermal model performance and developing flight-derived aerothermal environments for flight reconstruction thermal analysis and future SLS aerothermal models. The data offered critical insights into the aerothermodynamic conditions experienced during the launch and ascent of the SLS vehicle. This study compares the flight derived environments to pre-existing design models. The aerothermal models were constructed using MINIVER, the aerothermal engineering code which predicts aerodynamic heating and acts as an integration tool for incorporating databases from computational fluid dynamics (CFD) simulations and wind tunnel test data. The comparisons reveal the fidelity of the design models, highlighting areas where the design models accurately predicted flight conditions and instances where deviations were observed. Preliminary results suggest that while the design models largely aligned with the observed flight data, there were unique observations that reflected needed areas of model refinement. Aerothermal flight data from Artemis I for the SLS Block 1 vehicle will be further utilized to enhance the accuracy of Block 1B and Block 2 aerothermal models, ensuring improved safety and performance for subsequent Artemis missions.

aerothermodynamics↗

Validation of Artemis I Aerothermal Design Models Using Developmental Flight Instrumentation

The inaugural flight of the Space Launch System (SLS) Block 1 launch vehicle, Artemis I, occurred on November 16, 2022, and featured a full suite of Developmental Flight Instrumentation (DFI) that provided aerothermodynamic measurements to assess thermal design and substantiate aerothermodynamic models. The Block 1 launch vehicle aerothermal instrumentation consisted of approximately 277 aerothermal gauges mounted throughout the Orion Multi-Purpose Crew Vehicle (MPCV), Integrated Spacecraft and Payload Element (ISPE), Core Stage (CS) and Solid Rocket Boosters (SRB) and an additional 179 thermal gauges on the Orion Crew Module (CM). Instrumentation included calorimeters, radiometers, pressure transducers, gas temperature probes, and thermocouples. Data was collected from lift-off through CS Main Engine Cut-Off (MECO). The flight data was invaluable for determining aerothermal model performance and developing flight-derived aerothermal environments for flight reconstruction thermal analysis and future SLS aerothermal models. The data offered critical insights into the aerothermodynamic conditions experienced during the launch and ascent of the SLS vehicle. This study compares the flight derived environments to pre-existing design models. The aerothermal models were constructed using MINIVER, the aerothermal engineering code which predicts aerodynamic heating and acts as an integration tool for incorporating databases from computational fluid dynamics (CFD) simulations and wind tunnel test data. The comparisons reveal the fidelity of the design models, highlighting areas where the design models accurately predicted flight conditions and instances where deviations were observed. Preliminary results suggest that while the design models largely aligned with the observed flight data, there were unique observations that reflected needed areas of model refinement. Aerothermal flight data from Artemis I for the SLS Block 1 vehicle will be further utilized to enhance the accuracy of Block 1B and Block 2 aerothermal models, ensuring improved safety and performance for subsequent Artemis missions.

aerothermodynamics↗

Communication System Architecture for Planetary Exploration

Future human missions to Mars will require effective communications supporting exploration activities and scientific field data collection. Constraints on cost, size, weight and power consumption for all communications equipment make optimization of these systems very important. These information and communication systems connect people and systems together into coherent teams performing the difficult and hazardous tasks inherent in planetary exploration. The communication network supporting vehicle telemetry data, mission operations, and scientific collaboration must have excellent reliability, and flexibility.

Braham, Stephen P.↗

Human Thermal Model Evaluation Using the JSC Human Thermal Database

The human thermal database developed at the Johnson Space Center (JSC) is used to evaluate a set of widely used human thermal models. This database will facilitate a more accurate evaluation of human thermoregulatory response using in a variety of situations, including those situations that might otherwise prove too dangerous for actual testing--such as extreme hot or cold splashdown conditions. This set includes the Wissler human thermal model, a model that has been widely used to predict the human thermoregulatory response to a variety of cold and hot environments. These models are statistically compared to the current database, which contains experiments of human subjects primarily in air from a literature survey ranging between 1953 and 2004 and from a suited experiment recently performed by the authors, for a quantitative study of relative strength and predictive quality of the models. Human thermal modeling has considerable long term utility to human space flight. Such models provide a tool to predict crew survivability in support of vehicle design and to evaluate crew response in untested environments. It is to the benefit of any such model not only to collect relevant experimental data to correlate it against, but also to maintain an experimental standard or benchmark for future development in a readily and rapidly searchable and software accessible format. The Human thermal database project is intended to do just so; to collect relevant data from literature and experimentation and to store the data in a database structure for immediate and future use as a benchmark to judge human thermal models against, in identifying model strengths and weakness, to support model development and improve correlation, and to statistically quantify a model s predictive quality.

Cognata, T.↗

Ubiquitous Traffic Volume Estimation through Machine-Learning Procedure

Traffic volume data is one of the most important metrics for accurate assessment of the performance of a transportation system. Quality volume data is required to effectively assess extent of delay and congestion, detect real-time perturbations to the network, and understand traffic patterns during major weather events. Traffic volume on freeways are typically collected through continuous count stations installed by state DOTs, while there is lack of traffic volume observability on off-freeway roads. The National Renewable Energy Laboratory (NREL), in Collaboration with the I-95 Corridor Coalition and the University of Maryland, extended its research into estimating volumes anywhere anytime from industry probe based data for off-freeway roads. NREL combined vehicle probe count data with several other data sets (speed, whether, roadway geometry, time-of-day, day-of-week, etc.) to estimate hourly volumes as well as AADTs. The research validated and demonstrated the machine learning model, namely XGBoost, using data collected from Pennsylvania, North Carolina, and Tennessee.

47 OTHER INSTRUMENTATION↗

Livewire Data Platform-A Solution for Energy Efficient Mobility Systems (EEMS) Data Sharing

This presentation is an overview of progress made on the Livewire Data Platform since June 2021. Livewire is a publicly accessible platform for sharing energy efficiency and mobility research data funded by DOE's Vehicle Technologies Office. Core services and platform capabilities of Livewire include: Free, secure data storage; Access management that allows data owners to control who sees their data; Data collection and preservation; Quality characterization; Detailed access and download metrics; and Increased visibility of projects and data.

energy efficiency mobility↗

Livewire Data Platform-A Solution for Energy Efficient Mobility Systems (EEMS) Data Sharing

This presentation is an overview of progress made on the Livewire Data Platform since June 2022. Livewire is a publicly accessible platform for sharing energy efficiency and mobility research data funded by DOE's Vehicle Technologies Office. Core services and platform capabilities of Livewire include: Free, secure data storage; Access management that allows data owners to control who sees their data; Data collection and preservation; Quality characterization; Detailed access and download metrics; and Increased visibility of projects and data. Anyone can create an account and access data at https://livewire.energy.gov/.

energy efficiency↗

A UAV-Based Fog Collector Design for Fine-Scale Aerobiological Sampling

Airborne microbes are found throughout the troposphere and into the stratosphere. Knowing how the activity of airborne microorganisms can alter water, carbon, and other geochemical cycles is vital to a full understanding of local and global ecosystems. Just as on the land or in the ocean, atmospheric regions vary in habitability; the underlying geochemical, climatic, and ecological dynamics must be characterized at different scales to be effectively modeled. Most aerobiological studies have focused on a high level: 'How high are airborne microbes found?' and 'How far can they travel?' Most fog and cloud water studies collect from stationary ground stations (point) or along flight transects (1D). To complement and provide context for this data, we have designed a UAV-based modified fog and cloud water collector to retrieve 4D-resolved samples for biological and chemical analysis.Our design uses a passive impacting collector hanging from a rigid rod suspended between two multi-rotor UAVs (Unmanned Aerial Vehicles). The suspension design reduces the effect of turbulence and potential for contamination from the UAV downwash. The UAVs are currently modeled in a leader-follower configuration, taking advantage of recent advances in modular UAVs, UAV swarming, and flight planning.The collector itself is a hydrophobic mesh. Materials including Tyvek, PTFE, nylon, and polypropylene monofilament fabricated via laser cutting, CNC knife, or 3D printing were characterized for droplet collection efficiency using a benchtop atomizer and particle counter. Because the meshes can be easily and inexpensively fabricated, a set can be pre-sterilized and brought to the field for 'hot swapping' to decrease cross-contamination between flight sessions or use as negative controls.An onboard sensor and logging system records the time and location of each sample; when combined with flight tracking data, the samples can be resolved into a 4D volumetric map of the fog bank. Collected samples can be returned to the lab for a variety of analyses. Based on a review of existing flight studies, we have identified ion chromatography, metagenomic sequencing, cell staining and quantification, and ATP quantification as high-priority assays for implementation. Support for specific toxicology assays, such as methyl-mercury quantification, is also planned.

Design↗

Entry, Descent, and Landing Instrumentation

The first purpose of this white paper is to summarize the state-of-the-art of engineering instrumentation available for atmospheric Entry, Descent, and Landing (EDL) vehicles. Capabilities of the various types of measurements, along with recent examples from human and robotic EDL missions and technology development programs, significance to planetary science, and current challenges are discussed. Second, this paper provides recommendations for continuing to collect data on future missions with an EDL phase. Although the focus of this paper will be primarily on entry, instrumentation for descent and landing are also recognized to be important areas of future investment.

EDL↗

Overview of the Space Launch System Ascent Aeroacoustic Environment Test Program

Characterization of accurate flight vehicle unsteady aerodynamics is critical for component and secondary structure vibroacoustic design. The Aerosciences Branch at the National Aeronautics and Space Administration (NASA) Marshall Space Flight Center has conducted a test at the NASA Ames Research Center (ARC) Unitary Plan Wind Tunnels (UPWT) to determine such ascent aeroacoustic environments for the Space Launch System (SLS). Surface static pressure measurements were also collected to aid in determination of local environments for venting, CFD substantiation, and calibration of the flush air data system located on the launch abort system. Additionally, this test supported a NASA Engineering and Safety Center study of alternate booster nose caps. Testing occurred during two test campaigns: August - September 2013 and December 2013 - January 2014. Four primary model configurations were tested for ascent aeroacoustic environment definition. The SLS Block 1 vehicle was represented by a 2.5% full stack model and a 4% truncated model. Preliminary Block 1B payload and manned configurations were also tested, using 2.5% full stack and 4% truncated models respectively. This test utilized the 11 x 11 foot transonic and 9 x 7 foot supersonic tunnel sections at the ARC UPWT to collect data from Mach 0.7 through 2.5 at various total angles of attack. SLS Block 1 design environments were developed primarily using these data. SLS Block 1B preliminary environments have also been prepared using these data. This paper discusses the test and analysis methodology utilized, with a focus on the unsteady data collection and processing.

Herron, Andrew J.↗

The X-43A Flush Airdata Sensing System Flight Test Results

The National Aeronautics and Space Administration (NASA) has flight-tested a flush airdata sensing (FADS) system on the Hyper-X Research Vehicle (X-43A) at hypersonic speeds during the course of two successful flights. For this series of tests, the FADS system was calibrated to operate between Mach 3 and Mach 8, and flight test data was collected between Mach 1 and Mach 10. The FADS system acquired pressure data from surface-mounted ports and generated a real-time angle-of-attack (alpha) estimate on board the X-43A. The collected data were primarily intended to evaluate the FADS system performance, and the estimated alpha was used by the flight control algorithms on the X-43A for only a portion of the first successful flight. This paper provides an overview of the FADS system and alpha estimation algorithms, presents the in-flight alpha estimation algorithm performance, and provides comparisons to wind tunnel results and theory. Results indicate that the FADS system adequately estimated the alpha of the vehicle during the hypersonic portions of the two flights.

Baumann, Ethan↗

Comprehensive Assessment of On-And Off-Board Vehicle-To-Grid Technology Performance and Impacts on Battery and the Grid

This project defined, developed, and tested the open standards-based requirements, engineering design and system integration of on and off-vehicle Vehicle-to-Grid technologies both on the grid and on the PEV, to assess their effectiveness in implementing the use cases that create value for the grid, which in turn, can be passed on to the ratepayers and the PEV owners. The project comprised of three key categories of work and four key sub-areas of work. The three key categories were: On-Vehicle V2G, Off-Vehicle V2G, and impact of V2G operation on the battery capacity degradation. The four key sub-areas of work under each of these categories were: defining requirements, implementing the technology, performing system integration testing, and estimating the value of each of the grid services under specific assumptions, on a per-vehicle and on an aggregated basis. The technical implementation demonstrated the validity of standards-based approach to grid integration that led to interoperability, in addition to assessing the operational details with grid constraints imposed at the transformer level. The technology implementation also identified the subtle gaps in the standards definition to close the feedback loop on the accuracy of the standards as written, which are being implemented as revisions to the appropriate protocols. The battery impacts assessment developed a test cycle that the batteries from a real PHEV were subjected to for both the mobility-only and mobility with V2G specific energy cycling. While the battery impact results show a clear incremental degradation in response to additional throughput for V2G application purposes, the amount of additional kWh that can be made available without exceeding the end-of-life capacity definition of the battery at its 10-year warranty period was found to be significant. Given that the PEV battery being exercised during testing was a PHEV battery (smaller energy capacity), and 44% of its usable energy (i.e., SOC) was utilized daily for V2G applications, the EVs with much larger batteries will fare much better, either in terms of extracting more value in terms of incremental kWh for V2G, or in terms of relative incremental degradation of the capacity through the battery lifespan. Further, this battery was the second-generation Lithium-Ion chemistry circa 2015, which is at least two generations ago. Continual improvements in electrochemistry and manufacturing techniques as well as on-board capacity will enable the future batteries to provide even more energy for non-mobility-related services. Finally, the valuation of V2G energy services at the premise, distribution, and the ISO/market level was carried out for both the on-vehicle and off-vehicle cases, to understand both the GHG mitigation and operational efficiency improvements in quantitative terms. The analysis indicates that between $\$400$ and $\$1400$ per year of total value to the grid can be realized. When netted of costs to implement V2G either on or off-vehicle, the net value is available to be shared between the ratepayers and the EV owners. Over the life of the EV, therefore, this value becomes significant and can easily provide both ratepayer and EV owner benefits more than the cost of the equipment, either on or off-board, in addition to providing GHG mitigation benefits both on the grid and on the mobility sides. For these benefits to accrue, the key learnings from both the on- and off-vehicle V2G parts of the project indicate the need for at-scale demonstrations through involvement of real EV owners to validate both the technical feasibility, interoperability, as well as real grid benefits by performing extensive data collection and analysis. This will help inform the grid planners, the program designs, and tariff designers, as well as automotive and equipment manufacturers how best to create their products to maximize grid, ratepayer, and EV owner value.

30 DIRECT ENERGY CONVERSION↗

Power Prediction of Airborne Wind Energy Systems Using Multivariate Machine Learning

Kites can be used to harvest wind energy at higher altitudes while using only a fraction of the material required for conventional wind turbines. In this work, we present the kite system of Kyushu University and demonstrate how experimental data can be used to train machine learning regression models. The system is designed for 7 kW traction power and comprises an inflatable wing with suspended kite control unit that is either tethered to a fixed ground anchor or to a towing vehicle to produce a controlled relative flow environment. A measurement unit was attached to the kite for data acquisition. To predict the generated tether force, we collected input–output samples from a set of well-designed experimental runs to act as our labeled training data in a supervised machine learning setting. We then identified a set of key input parameters which were found to be consistent with our sensitivity analysis using Pearson input–output correlation metrics. Finally, we designed and tested the accuracy of a neural network, among other multivariate regression models. The quality metrics of our models show great promise in accurately predicting the tether force for new input/feature combinations and potentially guide new designs for optimal power generation.

17 WIND ENERGY↗

Mapping Van

A NASA Center for the Commercial Development of Space (CCDS) - developed system for satellite mapping has been commercialized for the first time. Global Visions, Inc. maps an area while driving along a road in a sophisticated mapping van equipped with satellite signal receivers, video cameras and computer systems for collecting and storing mapping data. Data is fed into a computerized geographic information system (GIS). The resulting amps can be used for tax assessment purposes, emergency dispatch vehicles and fleet delivery companies as well as other applications.

Source record↗

Ares I Aerodynamic Testing at the Boeing Polysonic Wind Tunnel

Throughout three full design analysis cycles, the Ares I project within the Constellation program has consistently relied on the Boeing Polysonic Wind Tunnel (PSWT) for aerodynamic testing of the subsonic, transonic and supersonic portions of the atmospheric flight envelope (Mach=0.5 to 4.5). Each design cycle required the development of aerodynamic databases for the 6 degree-of-freedom (DOF) forces and moments, as well as distributed line-loads databases covering the full range of Mach number, total angle-of-attack, and aerodynamic roll angle. The high fidelity data collected in this facility has been consistent with the data collected in NASA Langley s Unitary Plan Wind Tunnel (UPWT) at the overlapping condition ofMach=1.6. Much insight into the aerodynamic behavior of the launch vehicle during all phases of flight was gained through wind tunnel testing. Important knowledge pertaining to slender launch vehicle aerodynamics in particular was accumulated. In conducting these wind tunnel tests and developing experimental aerodynamic databases, some challenges were encountered and are reported as lessons learned in this paper for the benefit of future crew launch vehicle aerodynamic developments.

Pinier, Jeremy T.↗

Human Thermal Model Evaluation Using the JSC Human Thermal Database

Human thermal modeling has considerable long term utility to human space flight. Such models provide a tool to predict crew survivability in support of vehicle design and to evaluate crew response in untested space environments. It is to the benefit of any such model not only to collect relevant experimental data to correlate it against, but also to maintain an experimental standard or benchmark for future development in a readily and rapidly searchable and software accessible format. The Human thermal database project is intended to do just so; to collect relevant data from literature and experimentation and to store the data in a database structure for immediate and future use as a benchmark to judge human thermal models against, in identifying model strengths and weakness, to support model development and improve correlation, and to statistically quantify a model s predictive quality. The human thermal database developed at the Johnson Space Center (JSC) is intended to evaluate a set of widely used human thermal models. This set includes the Wissler human thermal model, a model that has been widely used to predict the human thermoregulatory response to a variety of cold and hot environments. These models are statistically compared to the current database, which contains experiments of human subjects primarily in air from a literature survey ranging between 1953 and 2004 and from a suited experiment recently performed by the authors, for a quantitative study of relative strength and predictive quality of the models.

Bue, Grant↗