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At least 1,117 records · Page 62

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NASA NTRS2008

Advanced Stirling Convertor (ASC) - From Technology Development to Future Flight Product

The Advanced Stirling Convertor (ASC) is being developed by Sunpower, Inc. under contract to NASA s Glenn Research Center (GRC) with critical technology support tasks lead by GRC. The ASC development, funded by NASA s Science Mission Directorate, started in 2003 as one of 10 competitively awarded contracts that were to address future Radioisotope Power System (RPS) advanced power conversion needs. The ASC technology has since evolved through progressive convertor builds and successful testing to demonstrate high conversion efficiency (38 %), low mass (1.3 kg), hermetic sealing, launch vibration simulation, EMI characterization, and is undergoing extended operation. The GRC and Sunpower team recently delivered three ASC-E machines to the Department of Energy (DOE) and Lockheed Martin Space Systems Company, two units for integration onto the Advanced Stirling Radioisotope Generator Engineering Unit (ASRG EU) plus one spare. The design has recently been initiated for the ASC-E2, an evolution from the ASC-E that substitutes higher temperature materials enabling improved performance and higher reliability margins. This paper summarizes the history and status of the ASC project and discusses plans for this technology which enables RPS specific power of 8 W/kg for future NASA missions.

Wong, Wayne A.↗

NASA NTRS2019

Myco-Architecture off Planet: Growing Surface Structures at Destination

Our work focused on filling major select key technical knowledge gaps, and technical aspects to be addressed in a Phase II proposal were identified such as the secretion of glues or plastics by the fungi or bacteria to form biocomposites. Specifically, we raised the technical TRL by assessing the growth of in-house mycelial-producing strains on potential food substrates and analyzed the advantages and disadvantages to their use off planet. Growth of the mycelia on sawdust and powdered nutrients including dried, powdered algae, was used as a baseline. We measured growth as a function of temperature, tested the relevant material properties of the mycelia products produced, and measured the mass of input and output volume for production per volume of material. Mycotecture was produced in a bag simulating the proposed mission implementation. Post-production such as heat treatment (as is done with terrestrial mycotecture)was assessed.The material properties of the dried, frozen and baked mycelial outputs included density, strength,thermal insulation and flame retardation. Tensile/compression testing on biocomposite material specimens was performed to obtain three-dimensional elastic constants, as well as to examine deformation and fracture behavior. These mechanical tests were performed on both dormant and activated samples to understand the evolution of the structural material. In addition, experimental data obtained from the mechanical testing was used to build a failure prediction model that accounts for material anisotropy. This aided in future structural design through a quantitative understanding of the mechanical limits of the material. To examine the texture, defects, fracture surfaces of the material, high-resolution microstructural imaging was utilized before and after the mechanical tests. This microstructural analysis informed us about the macro-structural behavior and influenced structural design. Thermal decomposition analysis was also performed tounderstand the thermal limits.

Biocomposites↗

NASA NTRSDate not supplied

Pterodactyl: 6-DOF Integration of Guidance and Control Algorithms in Genesis

The NASA-funded Pterodactyl project seeks to advance the current state-of-the-art for entry vehicles by developing novel guidance and control technologies for Deployable Entry Vehicles. This paper builds upon the Pterodactyl architecture that employed eight individually articulating flaps with two options for guidance, bank angle modulation with the Fully Numerical Predictor Corrector Entry Guidance (FNPEG) technique and angle of attack and sideslip modulation with FNPEG uncoupled range control. These, with a linear quadratic regulator controller, have previously been presented in separate 3-DOF trajectory simulations, one for translational motion and another for rotational dynamics. This work will show results for integrated 6-DOF simulations, leveraging recent advancements in trajectory simulation tools, namely the Julia-based Genesis package. Results show similar performance for both schemes when compared to the previously presented 3-DOF results once the controllers were adequately tuned. Angle of attack and sideslip modulation necessitated a controller designed at high dynamic pressure conditions, and bank angle modulation necessitated a controller designed at lower dynamic pressure conditions. Notably, angle of attack and sideslip modulation could not achieve the parachute deploy point target Mach number of 2, when only tuning the controller gains, thus future work will be needed to tune guidance specific parameters to achieve acceptable range targeting and guidance command tracking.

DEV↗

DOE OSTI2022

Broadband impedance modeling and single bunch instabilities estimations of the advanced light source upgrade project

We report the Advanced Light Source Upgrade (ALS-U) is a 4th generation diffraction-limited soft x-ray radiation source, consisting of a new accumulator ring (AR) and a new storage ring (SR). In both rings coupling-impedance driven instabilities need careful evaluation to ensure meeting the machine’s high-performance goals. This paper presents the workflow followed in building the impedance models and the beam-stability analysis based on those models. We follow the commonly accepted approach of separating the resistive-wall and the geometric parts of the impedance; the former is obtained by analytical formulas, the latter by numerical electro-magnetic codes (primarily CST Studio software) with perfectly-conducting boundary conditions. Impedance budgets are established and pseudo-Green functions calculated to be used in beam dynamics studies. We also present various ways to cross-check simulation results for reliable impedance modeling. Finally, the crucial single-bunch instability current thresholds for various operation modes are determined and discussed.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2026

Status and performance of the GlueX DIRC

In support of the future physics program at Ce+BAF, we propose a prototype positron target. The prototype target consists of a tungsten disk mounted on a water-cooled copper support structure to enhance heat removal. The primary goals of this work are to benchmark CFD simulations, ensure vacuum integrity at the 10^-6 Pa level, achieve stable target rotation up to 10 Hz, and implement efficient water-based cooling for sustained high-power operation. To manage the thermal load, the target is designed to rotate, allowing the deposited heat to spread over a larger region, and thereby reducing localized thermal stress while maintaining the maximum temperature below 1000 K. To experimentally evaluate the thermal performance and structural stability of the target, we plan to conduct high-power laser heating tests at Laser Lab 5, LERF Building, JLab. These tests will serve as a stepping-stone for the positron production target at CEBAF.

Stevens, J.R. [College of William and Mary, Willia↗

DOE OSTI2021

Physics-informed machine learning of the Lagrangian dynamics of velocity gradient tensor

Reduced models describing the Lagrangian dynamics of the velocity gradient tensor (VGT) in homogeneous isotropic turbulence (HIT) are developed under the physics-informed machine learning (PIML) framework. We consider the VGT at both Kolmogorov scale and coarse-grained scale within the inertial range of HIT. Building reduced models requires resolving the pressure Hessian and subfilter contributions, which is accomplished by constructing them using the integrity bases and invariants of the VGT. The developed models can be expressed using the extended tensor basis neural network (TBNN) introduced by Ling et al. [J. Fluid Mech. 807, 155 (2016)]. Physical constraints, such as Galilean invariance, rotational invariance, and incompressibility condition, are thus embedded in the models explicitly. Our PIML models are trained on the Lagrangian data from a high-Reynolds number direct numerical simulation (DNS). To validate the results, we perform a comprehensive out-of-sample test. We observe that the PIML model provides an improved representation for the magnitude and orientation of the small-scale pressure Hessian contributions. Statistics of the flow, as indicated by the joint PDF of second and third invariants of the VGT, show good agreement with the “ground-truth” DNS data. A number of other important features describing the structure of HIT are reproduced by the model successfully. We have also identified challenges in modeling inertial range dynamics, which indicates that a richer modeling strategy is required. This helps us identify important directions for future research, in particular towards including inertial range geometry into the TBNN.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

The SONATA data format for efficient description of large-scale network models

Increasing availability of comprehensive experimental datasets and of high-performance computing resources are driving rapid growth in scale, complexity, and biological realism of computational models in neuroscience. To support construction and simulation, as well as sharing of such large-scale models, a broadly applicable, flexible, and high-performance data format is necessary. To address this need, we have developed the Scalable Open Network Architecture TemplAte (SONATA) data format. It is designed for memory and computational efficiency and works across multiple platforms. The format represents neuronal circuits and simulation inputs and outputs via standardized files and provides much flexibility for adding new conventions or extensions. SONATA is used in multiple modeling and visualization tools, and we also provide reference Application Programming Interfaces and model examples to catalyze further adoption. SONATA format is free and open for the community to use and build upon with the goal of enabling efficient model building, sharing, and reproducibility.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Regal Beloit Final Technical Report

The original project proposal submitted from NovaTorque Inc (NovaTorque) in 2016 was to improve the existing motor with 95% efficiency by reducing the losses by 21% to achieve 96%. A few months after the proposal was submitted, NovaTorque lost funding and went out of business. The assets of NovaTorque were then acquired by Regal Beloit Corporation (“Regal Beloit” or “Regal”). When the NovaTorque proposal was selected, the project was transferred to Regal Beloit. Once we had production samples from the new Regal production line, they were tested at the Regal Beloit test lab in Wausau, WI. The original NovaTorque motor had an efficiency of 95%, but when the technology was transferred to Regal Beloit, there were multiple manufacturing improvements made, even though the basic electromagnetic design did not change. The test results in Wausau showed that the motors made at the Regal Beloit plant had an efficiency of 96%. Since the goal of the project was to reduce the losses by 21%, a new efficiency target of 96.8% became the project objective. In the first budget period, motors were tested to get the baseline performance. We then used FEA modeling with ANSYS Maxwell to model the existing motor to get correlation between the FEA simulations and the actual test results. Once the model was validated, we evaluated some changes that could be made to the stator to reduce the losses and improve efficiency without changing the rotor or stator housing, keeping the modifications easy to implement. The changes were primarily in the area of making the stator axially shorter and adding Soft Magnetic Composite (SMC) tooth tips. In the second budget period, we proceeded to design and build the new stator that was identified above and identified additional improvements in the process that included a stator machining modification and the use of rectangular wire. When we actually built the motor, the choice of rectangular wire turned out to be a problem. The wire was made by squishing round wire to get the rectangular shape, which caused work hardening, making the wire too stiff to make the desired coils. We shifted to annealed square wire which was better, but we still could not maintain the proper coil envelope. The result was that we had reduced cross section area for stator laminations. We also had to have a radial offset resulting in a radial misalignment between the stator and rotor because of the oversized coils. After the motor was completed, it was shipped to Texas A&M University for testing. With the loss of flux from these issues, the measured motor efficiency was only 96.3%. The primary focus of this motor was to make sure our FEA simulation model predicted the measured losses and overall efficiency, this we moved on to the FEA simulation. The FEA simulations of the motor “as built” with misalignments had good correlation with the test results, so the next step was to use that model to optimize the design of the motor for a final build. This time we considered changes to the stator and rotor and also minor changes to the housing diameter. In the third budget period, we did the detailed design and construction of the final prototypes. The final prototypes had a slight increase in the stator diameter to fit in a standard Regal Beloit housing. We shortened the stator and use more layers of wire in the coils. We also increased the cone angle of the rotor and stator from the original 110 degrees to 130 degrees to get some additional efficiency and optimized the stator cross section. The predicted efficiency from the FEA simulations was 96.9%. When completed, the motors were tested. We were a little short of reaching our target efficiency goal of 96.8%. We were only able to get to 96.7% efficiency. While it may be possible with additional iterations in designs and future builds to gain that additional 0.1%, we believe that we are close to the best we can achieve from a practical viewpoint, and additional iterations would be more work than the potential gains would be worth. No other motor in this class can even reach the 96% that we started with.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Achieving High Strength and Creep Resistance in Inconel 740H Superalloy through Wire-Arc Additive Manufacturing and Thermodynamic-Guided Heat Treatment

Inconel 740H superalloy is commonly used in advanced ultra-supercritical power plants since it possesses excellent strength and creep resistance. This study investigates the microstructure and mechanical properties of Inconel 740H superalloy fabricated using wire-arc additive manufacturing. The as-printed microstructure consisted of columnar γ grains with the Laves phase and (Nb, Ti)C carbides as secondary phases. The anisotropy in grain structure increased from the bottom to the top regions, while the hardness was highest in the middle portion of the build. To guide the post-heat treatment design, thermodynamic and kinetic simulations were employed to predict the temperature and time. Complete recrystallization with the Laves phase dissolution occurred throughout the build after homogenization at 1200 °C for 2 h. The peak hardness was achieved after aging at 760 °C for 12 h with the M 23 C 6 carbides decorating the grain boundaries and γ’ precipitates in the grain interior. The yield strength (655 MPa) and ductility (29.5%) in the post-heat treated condition exceeded the design targets (620 MPa, 20%). Stress rupture tests at 750 °C showed that the high-temperature performance was at par with the wrought counterparts. The fracture mode after rupture was identified to be intergranular with the presence of grain boundary cavities along with grain boundary sliding.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Virtual Refrigerant Charge Sensing Method for Next-Generation Refrigerant in Residential Heat Pumps

The charge level of refrigerant in heat pump systems significantly affects their operational performance. Virtual refrigerant charge (VRC) sensing technology has been well-established for traditional refrigerants (HFCs and HCFCs) for its low cost compared to physical sensors. However, other than traditional refrigerants, HFOs are increasingly used in next-generation heat pumps; whether these conventional VRC sensing methods remain applicable for heat pump systems utilizing next-generation refrigerants requires further investigation. To address these issues, this study develops a low-cost VRC sensing method for next-generation refrigerant heat pumps used in residential buildings. The developed algorithm is evaluated by using simulation models to evaluate the accuracy, considering an R454B heat pump with a nominal heating capacity of 51K Btu/hr (14.95 kW) as an example, and compared with those of the two reference VRC sensing algorithms. Though the developed VRC sensing algorithm and the two reference methods can accurately predict the charge level for the R454B heat pump system (with mean absolute percentage error for various cooling and heating conditions less than 7%), the developed VRC sensing algorithm uses fewer sensors and improves the overall accuracy for heating conditions by 7.1%, and the accuracy for undercharge cooling conditions 14.2%, compared with a mainstream algorithm. This technology will complement physical leakage detectors, and promote the adoption of next-generation heat pump systems, along with reducing wasted energy and maintenance costs.

Liang, Chenjiyu↗

NASA NTRS1983

The design and development of a vapor compression refrigerator/freezer for spacelab

A computer simulation was performed to determine the design criteria for a spacelab refrigerator/freezer using the test results of a vapor compression refrigerator/freezer which flew on STS-4 without problem. It has been established to have a vapor Reynolds number over 3000 at a vapor quality of 0.2 to maintain annular boiling in the evaporator and for the condenser to have a vapor Reynolds number over 15000 at its inlet to maintain annular condensation. These two constraints will virtually eliminate the effect of gravity on the performance of the refrigerator/freezer. These results are being used to build a refrigerator/freezer which will fly in Spacelab-4 scheduled for launch in December 1985.

Hye, A.↗

NASA NTRS2011

Testing Strategies and Methodologies for the Max Launch Abort System

The National Aeronautics and Space Administration (NASA) Engineering and Safety Center (NESC) was tasked to develop an alternate, tower-less launch abort system (LAS) as risk mitigation for the Orion Project. The successful pad abort flight demonstration test in July 2009 of the "Max" launch abort system (MLAS) provided data critical to the design of future LASs, while demonstrating the Agency s ability to rapidly design, build and fly full-scale hardware at minimal cost in a "virtual" work environment. Limited funding and an aggressive schedule presented a challenge for testing of the complex MLAS system. The successful pad abort flight demonstration test was attributed to the project s systems engineering and integration process, which included: a concise definition of, and an adherence to, flight test objectives; a solid operational concept; well defined performance requirements, and a test program tailored to reducing the highest flight test risks. The testing ranged from wind tunnel validation of computational fluid dynamic simulations to component ground tests of the highest risk subsystems. This paper provides an overview of the testing/risk management approach and methodologies used to understand and reduce the areas of highest risk - resulting in a successful flight demonstration test.

Schaible, Dawn M.↗

NASA NTRS2013

Large/Complex Antenna Performance Validation for Spaceborne Radar/Radiometeric Instruments

Over the past decade, Earth observing missions which employ spaceborne combined radar & radiometric instruments have been developed and implemented. These instruments include the use of large and complex deployable antennas whose radiation characteristics need to be accurately determined over 4 pisteradians. Given the size and complexity of these antennas, the performance of the flight units cannot be readily measured. In addition, the radiation performance is impacted by the presence of the instrument's service platform which cannot easily be included in any measurement campaign. In order to meet the system performance knowledge requirements, a two pronged approach has been employed. The first is to use modeling tools to characterize the system and the second is to build a scale model of the system and use RF measurements to validate the results of the modeling tools. This paper demonstrates the resulting level of agreement between scale model and numerical modeling for two recent missions: (1) the earlier Aquarius instrument currently in Earth orbit and (2) the upcoming Soil Moisture Active Passive (SMAP) mission. The results from two modeling approaches, Ansoft's High Frequency Structure Simulator (HFSS) and TICRA's General RF Applications Software Package (GRASP), were compared with measurements of approximately 1/10th scale models of the Aquarius and SMAP systems. Generally good agreement was found between the three methods but each approach had its shortcomings as will be detailed in this paper.

Antenna Modeling↗

NASA NTRSDate not supplied

Pterodactyl: 6-DOF Integration of Guidance and Control Algorithms in Genesis

The NASA-funded Pterodactyl project seeks to advance the current state-of-the-art for entry vehicles by developing novel guidance and control technologies for Deployable Entry Vehicles. This paper builds upon the Pterodactyl architecture that employed eight individually articulating flaps with two options for guidance, bank angle modulation with the Fully Numerical Predictor Corrector Entry Guidance (FNPEG) technique and angle of attack and sideslip modulation with FNPEG uncoupled range control. These, with a linear quadratic regulator controller, have previously been presented in separate 3-DOF trajectory simulations, one for translational motion and another for rotational dynamics. This work will show results for integrated 6-DOF simulations, leveraging recent advancements in trajectory simulation tools, namely the Julia-based Genesis flight simulation tool. Results show similar performance for both schemes when compared to the previously presented 3-DOF results once the controllers were adequately tuned. Angle of attack and sideslip angle modulation necessitated a controller designed at high dynamic pressure conditions, and bank angle modulation necessitated a controller designed at lower dynamic pressure conditions. Notably, the angle of attack and sideslip modulation approach could not achieve the parachute deploy point target Mach number of 2, when only tuning the controller gains, so future work will be needed to improve guidance and control tracking.

EDL↗

DOE OSTI2025

Deep Learning–Assisted Multiobjective Optimization of Geological CO 2 Storage Performance under Geomechanical Risks

In geological CO 2 storage, designing the optimal well control strategy for CO 2 injection to maximize CO 2 storage while minimizing the associated geomechanical risks is not trivial. This challenge arises due to pressure buildup, CO 2 plume migration, the highly nonlinear nature of geomechanical responses to rock-fluid interaction, and the high computational cost associated with coupled flow and geomechanics simulations. In this paper, we introduce a novel optimization framework to address these challenges. The optimization problem is formulated as follows: maximize total CO 2 storage while minimizing geomechanical risks by adjusting the injection schedules within bounded constraints. The geomechanical risks are primarily driven by injection-induced pressure build-up, which is characterized by ground displacement and the induced microseismicity. We used the Fourier neural operator (FNO)-based deep learning model to construct surrogate models, replacing the time-consuming coupled flow and geomechanics simulations for evaluating the aforementioned objective functions. The developed surrogate models have been incorporated into a multiobjective optimization framework through a genetic algorithm to reduce the computational burden. The proposed optimization framework reduces the computational cost from approximately 2,400 hours, when using objective function evaluations based on physics-based simulations, to around 20 minutes. A set of Pareto-optimal solutions of the proposed workflow yields nontrivial optimal decisions, reducing the microseismicity potential and the vertical displacement. This Pareto front highlights the optimal trade-offs between CO 2 storage amount, safety, and ground displacement, emphasizing the need for careful optimization and management of injection strategies to achieve a balanced outcome. The novelty of this work is twofold. First, we demonstrate the importance of incorporating the minimization of the geomechanical risks as objective functions into the CO 2 storage optimization workflow to mitigate the potential risk of induced microseismicity and ground displacement. Second, we leverage the FNO-based surrogate models to optimize a real-field CO 2 storage operation.

42 ENGINEERING↗

DOE OSTI2021

Computational Framework for Machine-Learning-Enabled 13 C Fluxomics

13 C metabolic flux analysis (MFA) has emerged as a powerful tool for synthetic biology. This optimization-based approach suffers long computation time and unstable solutions depending on the initial guess. Here, we develop a machine-learning-based framework for 13 C fluxomics. Specifically, training and test data sets are generated by metabolic network decomposition and flux sampling, in which flux ratios at metabolic nodes and simulated labeling patterns of metabolites are used as training targets and features, respectively. To improve prediction accuracy and simplify the model, automated processes are developed for flux ratio selection based on solvability and feature screening based on importance. We found that predictive performance can be significantly improved using both amino acids and central carbon metabolites in comparison with amino acids alone. Together with measured external fluxes, the predicted flux ratios determine the mass balance system, yielding global flux distributions. This approach is validated by flux estimation using both simulated and experimental data in comparison with canonical 13 C MFA. The approach represents a reliable fluxomics method readily applicable to high-throughput metabolic phenotyping, which highlights the advances of intelligent learning algorithms in synthetic biology, specifically in the Test and Learn stage of the Design-Build-Test-Learn cycle.

13C metabolic flux analysis↗

DOE OSTI2021

Automated discovery of a robust interatomic potential for aluminum

Machine learning, trained on quantum mechanics (QM) calculations, is a powerful tool for modeling potential energy surfaces. A critical factor is the quality and diversity of the training dataset. Here we present a highly automated approach to dataset construction and demonstrate the method by building a potential for elemental aluminum (ANI-Al). In our active learning scheme, the ML potential under development is used to drive non-equilibrium molecular dynamics simulations with time-varying applied temperatures. Whenever a configuration is reached for which the ML uncertainty is large, new QM data is collected. The ML model is periodically retrained on all available QM data. The final ANI-Al potential makes very accurate predictions of radial distribution function in melt, liquid-solid coexistence curve, and crystal properties such as defect energies and barriers. We perform a 1.3M atom shock simulation and show that ANI-Al force predictions shine in their agreement with new reference DFT calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Magnetic Navigation for GPS-Denied Airborne Applications

Most current flight systems are dependent on GPS for navigation. Recently, however, navigation in GPS-denied environments has become an area of intensive research. Additional navigation sensor data can be obtained from visual observations (stars or terrain), inertial measurement units, radar, measurements of the local magnetic field, or perhaps even gravity. Absolute and relative positioning via magnetic field measurements have been shown to be viable in many applications including ground navigation, low altitude aircraft flight, and spaceflight. There is greater variability in the magnetic field over shorter distances when flying at low altitude and in ground applications, leading to more accurate positioning. However, ground-based magnetic navigation is often heavily influenced by man-made structures, especially in urban environments. This is not the case for airborne magnetic navigation since the influence of buildings, roads, etc. is negligible for typical aircraft altitudes. For absolute magnetic navigation, the positioning accuracy decreases as altitude increases for a given vehicle velocity, but the observed time variability in the field can be reclaimed by traveling faster through the field. Thus, navigation accuracy becomes a balance of speed and altitude since the higher altitude can be counterbalanced by higher velocity. To understand these effects quantitatively, we explored various techniques to aid a simulated inertial measurement unit with magnetic information. Using a technique known as two-dimensional magnetic map matching, we simulated the performance of airborne magnetic navigation at fixed speed while varying the altitude, flight direction, magnetometer data collection time, reference magnetic map bias error, and type of trajectory (over land or over ocean).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗