Results for “Computer Tool” — Page 49

NASA NTRSDate not supplied

Overview of Mars Sample Return – Earth Entry System Woven Roughness Heating Augmentation Test in NASA Langley’s Mach 6 Wind Tunnel

The Mars Sample Return Mission (MSR) is a planned NASA flagship mission in which a sample retrieval lander (SRL) with a rover will be flown to Mars to obtain sample tubes on the surface that were dropped by the Mars 2020 rover [1]. After obtaining the sam-ples, the rover will return and ascend back to Martian orbit onboard the Mars Ascent Vehicle (MAV). Upon return to Earth orbit, the samples will perform Entry, Descent, and Landing (EDL) with the Earth Entry Sys-tem (EES) architecture, and land in Utah. The EES vehicle will utilize a HEEET-variant as its TPS, which will be the first time a woven TPS will be used on a flagship NASA mission [2]. This TPS offers a unique challenge for Computational Fluid Dynamics (CFD) modeling of the aerothermal envi-ronment of the vehicle, as woven roughness heating augmentation has not been extensively investigated experimentally. As a result, in order to validate com-putational models for woven roughness heating aug-mentation, a wind tunnel test campaign at NASA Langley Research Center’s Mach 6 wind tunnel was performed in April of 2023. This test campaign consisted of over a hundred runs with Reynolds numbers spanning from 1-7 mil-lion 1/ft and with six separate wind tunnel models used. A second campaign with a suite of new models will be conducted in Summer 2023 as well as a cam-paign with a flat plate model, both of which are of great interest to the MSR-EES project. The data obtained from this test are extremely vital for the MSR mission, as they will validate CFD roughness heating models which will be directly used to design the TPS of the EES portion of MSR and characterize the heating environment that the entry ve-hicle will experience. Further extensions of the MSR-EES test campaign will continue to provide validation data for developing more effective computational tools.

Jonathan Cheatwood↗

NASA NTRSDate not supplied

Simulations of Coupled Shoulder Ablation of A Conceptual Aeroshell

The current study explores coupled numerical simulations of flow dynamics and material response affect ablation of the shoulder region of an entry capsule used in space missions like the Mars Sample Return (MSR) project. A new computational tool named Ares, developed at NASA Ames Research Center, is applied to carry out the coupled simulations by interconnecting well-established US3D (flow solver) and Icarus (material response solver), and the material considered is three-dimensional mid-density carbon phenolic (3MDCP). Particularly, this work extends the uncoupled analysis of Shrestha et al. 2022 by incorporating the coupling mechanism across the ablating surface between fluid and the capsule geometry. For simplicity, an axisymmetric geometry of the entry system is considered. A few mission-relevant parametric studies such as angles of orientation of the material layers with respect to the streamwise direction, backshell boundary conditions, and alternation of convective heat-transfer coefficients are investigated to essentially explore Ares capability with the primary focus on shoulder location.

Coupled Ablation Modeling↗

NASA NTRSDate not supplied

Aerothermodynamic Analyses for the LOFTID Technology Demonstration Mission

On November 10, 2023, the LOFTID flight test successfully demonstrated the aerodynamic and thermal protection system performance of an inflatable aeroshell at conditions relevant to an operational mission. Aerodynamic performance and aeroheating environment databases for this mission were generated using multiple computational tools for the rarefied, hypersonic, and supersonic flow regimes, supplemented by wind tunnel testing to obtain aeroshell boundary-layer transition and wake flow simulation validation data. A detailed discussion of tools, methods and results is presented herein.

Brian R. Hollis↗

NASA NTRSDate not supplied

Aerothermodynamic Analyses for the LOFTID Technology Demonstration Mission

On November 10, 2023, the LOFTID flight test successfully demonstrated the aerodynamic and thermal protection system performance of an inflatable aeroshell at conditions relevant to an operational mission. Aerodynamic performance and aeroheating environment databases for this mission were generated using multiple computational tools for the rarefied, hypersonic, and supersonic flow regimes, supplemented by wind tunnel testing to obtain aeroshell boundary-layer transition and wake flow simulation validation data. A detailed discussion of tools, methods and results is presented herein.

Brian R. Hollis↗

NASA NTRSDate not supplied

Overview of the Subscale RAVEN Flight Controls and Modeling Testbed

The Research Aircraft for eVTOL Enabling TechNologies (RAVEN) Subscale Wind-Tunnel and Flight Test (SWFT) model is a subscale aircraft built for flight dynamics and controls research demonstrated in wind-tunnel and flight-test experiments. The intent of this paper is to provide a summary of past, current, and future efforts being pursued by the RAVEN-SWFT project. Initially, vehicle development guidelines were crafted by a multidisciplinary team to ensure that the RAVEN-SWFT vehicle was well suited for research in multiple areas, including aero-propulsive modeling, flight controls, and autonomy, among others. The vehicle has been used to obtain extensive wind-tunnel data, enabling aero-propulsive model development across the transition flight envelope and validation of computational tools. The vehicle will be used to conduct flight testing in order to evaluate modeling strategies and flight control logic. The RAVEN-SWFT model also serves as a risk reduction activity for a conceptual, full-scale vehicle in the 1000-lb class. The next steps in the project are to successfully demonstrate free flight in hover, transition, forward flight, and the reverse thereof, utilizing custom control laws integrated onto the RAVEN-SWFT avionics hardware. The project intends to publicize all of the geometry, data, and methods in future reports.

eVTOL↗

NASA NTRSDate not supplied

Ice Shape Analysis of an eVTOL Propeller in Forward Flight at the NASA Glenn Icing Research Tunnel

Advanced Air Mobility (AAM) introduces many novel electric vertical takeoff and landing (eVTOL) aircraft configurations for which the effect of icing is not well understood. While icing computational tools have often aided in the design and certification of conventional aircraft, experimental data is needed to support the development and validation of such tools for eVTOL applications. To investigate the icing phenomenon relevant to eVTOL aircraft, NASA Glenn Research Center developed a general-purpose propeller test stand for conducting fundamental icing research on electrically driven propellers in the Icing Research Tunnel (IRT). A 10-day test entry in the IRT was completed in March, 2023, with the goal of generating ice accretions on a non-proprietary propeller geometry under well-characterized conditions. Three carbon fiber propellers of diameters 0.610, 0.711, and 0.914 m (24, 28, and 36 in) were used during the test. Various parametric sweeps of cloud and operating conditions were performed to evaluate the sensitivity of the parameters on the resulting ice accretion characteristics such as ice thickness, mass, location (impingement limits), and type (glaze vs rime). Ice shapes were reviewed for their repeatability, correctness of trends, and sensitivity to parameter variations. The data from the test is being used to support the development of the ice accretion solver, GlennICE.

Icing↗

NASA NTRSDate not supplied

NASA Icing Research Update 2024

This presentation summarizes NASA’s current icing research portfolio for an invited talk on August 1, 2024, at the AIAA Aviation Forum and Exposition. The presentation overviews NASA facilities, computational tools, and latest research. This research is categorized as application focused research, atmospheric characterization, and fundamental research / capability improvement. The application focused research includes (1) the Transonic Truss Brace Wing, (2) High Lift Common Research Model, (3) Advanced Air Mobility, and (4) Efficient Quiet Integrated Propulsor. The atmospheric characterization work includes High Ice Water Content Flight Research, while the fundamental research / capability improvement area includes (1) the Simulated Inter-compressor Duct Research Model, (2) Characterization of Low Ice Adhesion Materials, (3) Collection Efficiency Measurements, (4) Impedance Based Ice/ Water Sensor, (5) Tomography for Cloud Uniformity in the Icing Research Tunnel, and (6) Supercooled Large Drop Research. Finally, the presentation summarizes collaboration and partnership opportunities with NASA.

Icing↗

NASA NTRS2024

Ice Shape Analysis of an eVTOL Propeller in Forward Flight at the NASA Glenn Icing Research Tunnel

Advanced Air Mobility (AAM) introduces many novel electric vertical takeoff and landing (eVTOL) aircraft configurations for which the effect of icing is not well understood. While icing computational tools have often aided in the design and certification of conventional aircraft, experimental data is needed to support the development and validation of such tools for eVTOL applications. To investigate the icing phenomenon relevant to eVTOL aircraft, NASA Glenn Research Center developed a general-purpose propeller test stand for conducting fundamental icing research on electrically driven propellers in the Icing Research Tunnel (IRT). A 10-day test entry in the IRT was completed in March, 2023, with the goal of generating ice accretions on a non-proprietary propeller geometry under well-characterized conditions. Three carbon fiber propellers of diameters 0.610, 0.711, and 0.914 m (24, 28, and 36 in) were used during the test. Various parametric sweeps of cloud and operating conditions were performed to evaluate the sensitivity of the parameters on the resulting ice accretion characteristics such as ice thickness, mass, location (impingement limits), and type (glaze vs rime). Ice shapes were reviewed for their repeatability, correctness of trends, and sensitivity to parameter variations. The data from the test is being used to support the development of the ice accretion solver, GlennICE.

Icing↗

NASA NTRSDate not supplied

Wi-Fi Signal Survey of the International Space Station by Autonomous Free-Flying Robot

This paper analyzes Wi-Fi signal propagation inside pressurized modules of the International Space Station (ISS). Various flight datasets were collected by the Astrobee fleet of autonomous free-flying robots developed by the NASA Ames Research Center (ARC). The enclosed module spaces of the ISS pose unique challenges for Wi-Fi signal propagation, and understanding these challenges is crucial for optimizing connectivity in such environments. The survey data presented are valuable for optimizing wireless access point (WAP) locations and conditions. A computational method is developed to analyze the wireless communication system, RF coverage, and module compositions. The method is both rigorous and practical for assessing the ISS wireless system performance. The computational tools in this paper serve as a complementary approach to direct, on-orbit measurements, which is a complicated and expensive task. In some operational scenarios, ground measurements may be intractable due to the size of the spacecraft. Results from this research will aid future space missions and commercial spacecraft, providing insights into optimal WAP placements and robust wireless communication systems.

Astrobee↗

NASA NTRSDate not supplied

Wi-Fi Signal Survey of the International Space Station by Autonomous Free-Flying Robot

This paper analyzes Wi-Fi signal propagation inside pressurized modules of the International Space Station (ISS). Various flight datasets were collected by the Astrobee fleet of autonomous free-flying robots developed by the NASA Ames Research Center (ARC). The enclosed module spaces of the ISS pose unique challenges for Wi-Fi signal propagation, and understanding these challenges is crucial for optimizing connectivity in such environments. The survey data presented are valuable for optimizing wireless access point (WAP) locations and conditions. A computational method is developed to analyze the wireless communication system, RF coverage, and module compositions. The method is both rigorous and practical for assessing the ISS wireless system performance. The computational tools in this paper serve as a complementary approach to direct, on-orbit measurements, which is a complicated and expensive task. In some operational scenarios, ground measurements may be intractable due to the size of the spacecraft. Results from this research will aid future space missions and commercial spacecraft, providing insights into optimal WAP placements and robust wireless communication systems.

International Space Station↗

NASA NTRSDate not supplied

Optimal Communication Topology Construction and Sensor Selection for Independent Airspace Surveillance

The paper presents an approach with no estimation feedback to sensors selection and communication network topology computation for independent airspace surveillance with maximum outcome and minimum cost using ground based distributed sensing, computing and communication network infrastructure. The selection criteria includes maximum airspace coverage with minimal resources, minimum communication time and power consumption while guaranteeing the system observability and providing in-time high quality information to both stationary and mobile users. The developed algorithms use multi-objective optimization strategy taking into account trade-offs between conflicting objectives and are implemented using off-the-shelf computational tools. The algorithms are validated in a desktop simulation environment using synthetic sensors data generated for a simulated multi-vehicle flight scenario in the selected regional airspace and parameters of a notional wireless communication network.

Distributed sensing↗

NASA NTRSDate not supplied

High-Fidelity Aeropropulsive Assessment of Distributed Electric Propulsion and Boundary Layer Ingestion for the SUSAN Electrofan

This paper presents a high-fidelity aeropropulsive assessment of the SUSAN Electrofan’s distributed electric propulsion (DEP) and boundary layer ingestion (BLI) aft fuselage turbofan technologies. This is achieved through the application of computational tools for aerodynamic and aeropropulsive design and analysis based on the Reynolds-averaged Navier-Stokes (RANS) equations. Representative aircraft models are first developed in 3D for the SUSAN Electrofan concept, a non-DEP variant, and a year 2020 technology level reference aircraft based on the Boeing 737-8. These include airframes developed through the application of RANS-based aerodynamic shape optimization, with the objective of drag minimization at cruise while subject to constant lift and zero pitching moment constraints. Wing propulsors are also included and modeled as free-flying ducted fans. These are developed through RANS-based aeropropulsive shape optimization, with the objective of shaft power minimization while subject to constant net thrust and maximum fan face Mach number constraints. An iterative power balance method is then used to trim each of the decoupled aircraft configurations, providing estimates of relative aerodynamic performance, shaft power, and range efficiency. Results also include power on and off analyses, which indicate reduced thrust-induced drag for the SUSAN Electrofan’s DEP and BLI aft fuselage turbofan propulsors when compared to those of the Boeing 737-8-like reference aircraft.

CAS↗

DOE OSTI2019

Point Kinetics and Reactivity Feedback Modeling in SAM

Over the past few years, the rapidly rising interest in advanced nuclear reactor technology has led to an increased need for the developments and applications of advanced computational tools for modeling and simulation. System Analysis Module (SAM) is being developed at Argonne National Laboratory as a modern system-level modeling and simulation tool for advanced non-light water reactor safety analyses [1]. It utilizes the object-oriented application framework MOOSE [2] to leverage the modern software environment and advanced numerical methods [3]. To meet this need, the capabilities of SAM are being extended to enable the transient modeling, analysis, and design of advanced nuclear reactor systems. The objective of this summary is to present the development of Point-Kinetics modeling and reactivity feedback mechanisms in SAM. This summary also presents the new capability for modeling the thermal expansion reactivity feedback by coupling SAM and an external thermomechanics module (Tensor Mechanics) from MOOSE.

Hu, Guojun↗

DOE OSTI2019

Using Big Data Technologies for HEP Analysis

The HEP community is approaching an era were the excellent performances of the particle accelerators in delivering collision at high rate will force the experiments to record a large amount of information. The growing size of the datasets could potentially become a limiting factor in the capability to produce scientific results timely and efficiently. Recently, new technologies and new approaches have been developed in industry to answer to the necessity to retrieve information as quickly as possible to analyze PB and EB datasets. Providing the scientists with these modern computing tools will lead to rethinking the principles of data analysis in HEP, making the overall scientific process faster and smoother. In this paper, we are presenting the latest developments and the most recent results on the usage of Apache Spark for HEP analysis. The study aims at evaluating the efficiency of the application of the new tools both quantitatively, by measuring the performances, and qualitatively, focusing on the user experience. The first goal is achieved by developing a data reduction facility: working together with CERN Openlab and Intel, CMS replicates a real physics search using Spark-based technologies, with the ambition of reducing 1 PB of public data in 5 hours, collected by the CMS experiment, to 1 TB of data in a format suitable for physics analysis. The second goal is achieved by implementing multiple physics use-cases in Apache Spark using as input preprocessed datasets derived from official CMS data and simulation. By performing different end-analyses up to the publication plots on different hardware, feasibility, usability and portability are compared to the ones of a traditional ROOT-based workflow.

Cremonesi, Matteo↗

DOE OSTI2019

Exploring Molecular Mechanisms of Cosolvent Enhanced Biomass Deconstruction: An Overview of Recent Progress

In this chapter, we explore the mechanisms driving efficient thermochemical deconstruction and fractionation of lignocellulosic biomass in cosolvent mixtures for the production of biofuels and bioproducts. New approaches that combine molecular dynamics simulations with experimental characterization highlight the important role of cosolvents and their influence on molecular processes relevant to overcoming the natural recalcitrance of lignocellulose. From localized phase behavior on cellulose fibers to changes in lignin conformation, insights into cosolvent effects on biomass deconstruction involve understanding complex interactions between the solvent–solvent, solvent–substrate, and solvent–catalyst. Recently coordinated research efforts at multiple scales using computational tools, nano-scale imaging, and kinetic models have significantly advanced identification of high-performance cosolvents, shedding light on the mechanisms behind solvent-biomass interactions. Specifically, multifunctional cosolvents have been employed in leading biomass “solvolysis” technologies that favorably coordinate with dilute acids to solubilize and depolymerize all three primary biomass fractions of biomass: cellulose, hemicellulose, and lignin. As a result, recent work in studying solvent effects of multifunctional cosolvents has led to a paradigm shift toward the use of first principles to design biomass deconstruction techniques with the aim of maximizing total carbon utilization in biomass. The synergistic pairing of cosolvents with biomass deconstruction will lead scientists and engineers to overcome key technical and economic barriers of biomass processing, enabling a successful transition of the current energy landscape toward a future bioeconomy based on biomass as an alternative to petroleum.

Mostofian, Barmak↗

DOE OSTI2020

Community-Scale Energy Efficiency Assessment for Zero Net Energy Using the URBANopt Simulation Platform: Preprint

This project explored an innovative modeling approach for assessing the energy efficiency potential of the existing low-income Oceano neighborhood, in unincorporated San Luis Obispo County, and its effects on renewable generation requirements for achieving zero net energy (ZNE). One particular challenge faced was ascertaining the technical energy savings potential across a large neighborhood in a timely manner. The project overcame this challenge through the use of the URBANopt simulation platform, developed at the National Renewable Energy Laboratory. URBANopt manages the automated model creation, simulation, and result aggregation for different design scenarios of existing or candidate buildings in a large neighborhood. Customized energy efficiency packages considered for the residential and commercial sector in the neighborhood included lighting, HVAC, plug load, water heating, envelope, and energy education measures. As a result of the analysis for the Oceano community, energy efficiency measures that are available through incentive programs may provide a 7.4% reduction in the required distributed energy resource (DER) size, corresponding to a 25,000 ft2 decrease in PV array area, to achieve ZNE. Through this work, a computational tool was developed and is being leveraged by the County of San Luis Obispo (CoSLO). The tool has enabled the CoSLO staff to perform similar analysis of the technical potential for energy efficiency, and an understanding of the DER asset requirements and potential savings in other communities within the county.

building energy modeling↗

DOE OSTI2021

BETO 2021 Peer Review - Inverse Bioproduct Design Through Machine Learning and Molecular Simulation

This work aims to identify performance advantaged bioproducts (PABPs) through property prediction, which will guide experimental synthesis. The impact of this work will be faster market adoption of bioproducts with greater performance relative to incumbent products. We have identified >106 bioproduct candidates, but only some will have superior performance to create a market pull. High-throughput property prediction, enabled by machine learning, and elucidation of structure-function relationships, enabled by molecular simulation, provide a hypothesis driven approach for down selection of candidate biomolecules to pursue experimentally. To enable machine learning and molecular simulation for bioproduct discovery, automated structure generation and embedding must capture relevant features for prediction, databases must cover domains applicable to biobased products, and best practices for simulation of polymer systems must be developed. To address these challenges, we have established bioproduct relevant datasets, developed high-throughput polymer structure generation, and built end-to-end neural networks that have predicted 8 properties for >1.4 x 106 biopolymers. A molecular simulation pipeline for building, running, and analyzing polymers and polymer additives is being used to predict performance and develop design principles of biobased products. In collaboration with the PABP synthesis project, these computational tools are guiding synthesis and informing design of PABPs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Economic and Environmental Assessment of Biological Conversions of Agile BioFoundry (ABF) Bio-Derived Chemicals

Bio-derived chemicals are an essential part of the growing bioeconomy. They possess the potential to boost a new domestic bioproduct industry, improve the sustainability of integrated biomanufacturing, and reduce U.S. dependence on fossil energy. The Agile BioFoundry (ABF) consortium, a Department of Energy (DOE)-sponsored collaboration, is investigating biobased pathways to produce advantaged products including advanced biofuels, fuel intermediates, and bioproducts. ABF is integrating advanced computational tools for biological engineering, process design and data analysis, and economic/sustainability modeling tools into a comprehensive and dynamic platform for biomanufacturing of microbes and using them to produce key metabolic intermediates or beachhead molecules which may be derivatized into several distinct bioproducts of industrial interest. In this presentation, we first discuss a methodology to select a single exemplar product molecule to represent each beachhead pathway based on similarities with other end-molecule options (yields/titers/rates, fermentation operation mode, oxygen requirements, general separations challenges, etc.), in order to maintain a reasonable number of cases for rigorous process simulation. We then use techno-economic analysis (TEA) and life-cycle analysis (LCA) to highlight sensitivities and trends around economic performance and environmental footprint, reflecting examples for two selected ABF technology pathways to bio-derived chemicals: 1) adipic acid production via muconic acid fermentation from mixed sugars with Pseudomonas putida and 2) cineole via geranyl diphosphate with Rhodosporidium toruloides. We present multi-variable scan plots highlighting key drivers on costs and greenhouse gas emissions in order to identify the parameter space in which each pathway could ultimately achieve economic and environmental sustainability meeting or exceeding commodity product benchmarks, thus prioritizing future R&D focus areas.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗