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At least 1,405 records · Page 78

Part distortion monitoring in additive manufacturing using machining

In additive manufacturing, accumulation of residual stresses can result in severe part distortion from the desired preform shape. Current methods for in-situ part distortion monitoring in additive manufacturing typically require expensive sensors, or capital equipment, and require time-consuming post-processing to understand the shape deviation. This paper presents an in-situ method, in the context of hybrid manufacturing, for part distortion detection using machining of additively manufactured parts. As a surrogate, three test artifacts were used to represent different distorted geometries. The tool axis positions from the machine tool controller and the cutting power were monitored during a facing operation. Cutting power data was used to detect the tool entry and exit in the workpiece using a novel approach with power standard deviation metric. The workpiece geometry and distorted configuration was subsequently predicted for positional and rotational deviations to within 2 mm accuracy using synchronized tool position data with cutting power. The proposed method can be used in a hybrid (additive and subtractive) machine tool to periodically check part distortion in the additive build. The method is applicable for any additive process and is low-cost and computationally inexpensive.

36 MATERIALS SCIENCE↗

5G Enabled Energy Innovation: Advanced Wireless Networks for Science

Digital wireless communication has become a foundational technology for the nation. The U.S. Department of Energy’s Office of Science (DOE-SC) is the Nation’s largest supporter of basic research in the physical sciences discovering new materials, designing advanced microelectronics, and understanding the physics of radio frequency signaling. The expanding national rollout of a new fifth-generation (5G) mobile network, coupled with the torrent of scientific data generated by next-generation devices such as battery-powered Internet of Things (IoT) sensors, has created an urgent need to enhance cutting-edge wireless technology. Breakthroughs in the deployment, integration, security, and operational range of wireless networking can provide new scientific capabilities for the next decade - from autonomous mobile instruments for scientific user facilities to intelligent sensors networks distributed over thousands of kilometers to study environmental processes. To realize this promise, however, we must continue to drive innovations in computing, artificial intelligence (AI), advanced materials, high-speed networking, and microelectronics. In March 2020, the DOE-SC convened a workshop to identify the potential opportunities and explore the scientific challenges of advanced wireless technologies.

42 ENGINEERING↗

Variable-Speed Induction Motor Drives for Aircraft Environmental Control Compressors

New, more-efficient designs for aircraft jet engines are not capable of supplying the large quantities of bleed air necessary to provide pressurization and air conditioning for the environmental control systems (ECS) of the next generation of large passenger aircraft. System analysis and engineering have determined that electrically-driven ECS can help to maintain the improved fuel efficiencies; and electronic controllers and induction motors are now being developed in a NASA/NPD SBIR Program to drive both types of ECS compressors. Previous variable-speed induction motor/controller system developments and publications have primarily focused on field-oriented control, with large transient reserve power, for maximum acceleration and optimum response in actuator and robotics systems. The application area addressed herein is characterized by slowly-changing inputs and outputs, small reserve power capability for acceleration, and optimization for maximum efficiency. This paper therefore focuses on the differences between this case and the optimum response case, and shows the development of this new motor/controller approach. It starts with the creation of a new set of controller requirements. In response to those requirements, new control algorithms are being developed and implemented in an embedded computer, which is integrated into the motor controller closed loop. Buffered logic outputs are used to drive the power switches in a resonant-technology, power processor/motor-controller, at switching/resonant frequencies high enough to support efficient high-frequency induction motor operation at speeds up to 50,000-RPA

Mildice, J. W.↗

Pressure Gain, Stability, and Operability of Methane/Syngas Based RDEs Under Steady and Transient Conditions (Final Project Report)

The scope of this work addresses key issues associated with losses associated with the detonation wave and other processes internal to the RDE operation, as well as it develops modeling tools for the evaluation of these losses and exhaust emissions in RDEs. The main challenge in studying RDEs is that RDE performance is highly reliant on the specifics of the design so much so that simple/canonical systems alone cannot provide useful engineering information, but practical RDE designs are sufficiently complex and involve extreme operational environments that detailed access either experimentally (laser diagnostics, for instance) or computationally (direct numerical simulations) are as yet to become practical. To overcome this challenge, we have conducted a combined experimental/simulation/analytical study investigating key phenomena that control the characteristics of operation of RDEs. As a result, the study has developed tools and methods that can be used to evaluate performance and design approaches using reduced-physics models, with the assumptions validated using detailed simulations, and the model prediction tested using experimental observations. The specific objectives of the research were: (1) Develop and demonstrate a low-loss fully axial injection concept, taking advantage of stratification effects to alter the detonation structure and position the wave favorably within the combustor; (2) Obtain stability and operability characteristics of an RDE across operating conditions to aid in the development of operability and performance rules for the operations of other systems; and (3) Develop quantitative metrics for performance gain as well as quantitative description of the loss mechanisms through a combination of diagnostics development, reduced-order modeling, and detailed simulations. The work conducted here has made contribution on design of low-loss inlets that has broad application within the power generation industry for use with pressure gain combustion. The operability and stability of different designs, while focusing on axial air inlet designs, has been analyzed. The effect of nozzle and injection conditions was studied. Models and simulations of exhaust emissions, focusing on NOx emission has been developed and used to investigate how operation of the RDE affect NOx production using Lagrangian analysis of RDE simulations. This work has built on previous programs, with the goal of further understanding operation of RDEs and elevate the readiness of design consideration. In addition, a suite of diagnostic and modeling tools have been developed to obtain quantitative metrics on performance based on measurements, which can be readily transferred to other experimental configurations.

08 HYDROGEN↗

Composite Flywheels Assessed Analytically by NDE and FEA

As an alternative to expensive and short-lived lead-acid batteries, composite flywheels are being developed to provide an uninterruptible power supply for advanced aerospace and industrial applications. Flywheels can help prevent irregularities in voltage caused by power spikes, sags, surges, burnout, and blackouts. Other applications include load-leveling systems for wind and solar power facilities, where energy output fluctuates with weather. Advanced composite materials are being considered for these components because they are significantly lighter than typical metallic alloys and have high specific strength and stiffness. However, much more research is needed before these materials can be fully utilized, because there is insufficient data concerning their fatigue characteristics and nonlinear behavior, especially at elevated temperatures. Moreover, these advanced types of structural composites pose greater challenges for nondestructive evaluation (NDE) techniques than are encountered with typical monolithic engineering metals. This is particularly true for ceramic polymer and metal matrix composites, where structural properties are tailored during the processing stages. Current efforts involving the NDE group at the NASA Glenn Research Center at Lewis Field are focused on evaluating many important structural components, including the flywheel system. Glenn's in-house analytical and experimental capabilities are being applied to analyze data produced by computed tomography (CT) scans to help assess the damage and defects of high-temperature structural composite materials. Finite element analysis (FEA) has been used extensively to model the effects of static and dynamic loading on aerospace propulsion components. This technique allows the use of complicated loading schemes by breaking the complex part geometry into many smaller, geometrically simple elements.

Abdul-Aziz, Ali↗

Design-Technology Co-Optimization for NVM-based Neuromorphic Processing Elements

An emerging use-case of machine learning (ML) is to train a model on a high-performance system and deploy the trained model on energy-constrained embedded systems. Neuromorphic hardware platforms, which operate on principles of the biological brain, can significantly lower the energy overhead of a machine learning inference task, making these platforms an attractive solution for embedded ML systems. In this paper, we present a design-technology tradeoff analysis to implement such inference tasks on the processing elements (PEs) of a Non-Volatile Memory (NVM)-based neuromorphic hardware. Through detailed circuit-level simulations at scaled process technology nodes, we show the negative impact of technology scaling on the information-processing latency, which impacts the quality-of-service (QoS) of an embedded ML system. At a finer granularity, the latency inside a PE depends on 1) the delay introduced by parasitic components on its current paths, and 2) the varying delay to sense different resistance states of its NVM cells. Based on these two observations, we make the following three contributions. First, on the technology front, we propose an optimization scheme where the NVM resistance state that takes the longest time to sense is set on current paths having the least delay, and vice versa, reducing the average PE latency, which improves the QoS. Second, on the architecture front, we introduce isolation transistors within each PE to partition it into regions that can be individually power-gated, reducing both latency and energy. Finally, on the system-software front, we propose a mechanism to leverage the proposed technological and architectural enhancements when implementing a machine-learning inference task on neuromorphic PEs of the hardware. Evaluations with a recent neuromorphic hardware architecture show that our proposed design-technology co-optimization approach improves both performance and energy efficiency of machine-learning inference tasks without incurring high cost-per-bit.

42 ENGINEERING↗

Multiphysics Simulation of the NASA SIRIUS-CAL Fuel Experiment in the Transient Test Reactor Using Griffin

After approximately 50 years, NASA is restarting efforts to develop nuclear thermal propulsion (NTP) for interplanetary missions. Building upon nuclear engine tests performed from the late 1950s to the early 1970s, the present research and testing focuses on advanced materials and fabrication methods. A number of transient tests have been performed to evaluate materials performance under high-temperature, high-flux conditions, with several more experiments in the pipeline for future testing. The measured data obtained from those tests are being used to validate the Griffin reactor multiphysics code for this particular type of application. Griffin was developed at Idaho National Laboratory (INL) using the MOOSE framework. This article describes the simulation results of the SIRIUS-CAL calibration experiment in the Transient Reactor Test Facility (TREAT). SIRIUS-CAL was the first transient test conducted on NASA fuels, and although the test was performed with a relatively low core peak power, the test specimen survived a temperature exceeding 900 K. Griffin simulations of the experiment successfully matched the reactor’s power transient after calibrating the initial control rod position to match the initial reactor period. The thermal-hydraulics model largely matches the time-dependent response of a thermocouple located within the experiment specimen to within the uncertainty estimate. However, the uncertainty range is significant and must be reduced in the future.

33 ADVANCED PROPULSION SYSTEMS↗

Stirling Technology Development at NASA GRC

The Department of Energy, Stirling Technology Company (STC), and NASA Glenn Research Center (NASA Glenn) are developing a free-piston Stirling convertor for a high efficiency Stirling Radioisotope Generator (SRG) for NASA Space Science missions. The SRG is being developed for multimission use, including providing electric power for unmanned Mars rovers and deep space missions. NASA Glenn is conducting an in-house technology project to assist in developing the convertor for space qualification and mission implementation. Recent testing of 55-We Technology Demonstration Convertors (TDCs) built by STC includes mapping of a second pair of TDCs, single TDC testing, and TDC electromagnetic interference and electromagnetic compatibility characterization on a nonmagnetic test stand. Launch environment tests of a single TDC without its pressure vessel to better understand the convertor internal structural dynamics and of dual-opposed TDCs with several engineering mounting structures with different natural frequencies have recently been completed. A preliminary life assessment has been completed for the TDC heater head, and creep testing of the IN718 material to be used for the flight convertors is underway. Long-term magnet aging tests are continuing to characterize any potential aging in the strength or demagnetization resistance of the magnets used in the linear alternator (LA). Evaluations are now beginning on key organic materials used in the LA and piston/rod surface coatings. NASA Glenn is also conducting finite element analyses for the LA, in part to look at the demagnetization margin on the permanent magnets. The world's first known integrated test of a dynamic power system with electric propulsion was achieved at NASA Glenn when a Hall-effect thruster was successfully operated with a free-piston Stirling power source. Cleveland State University is developing a multidimensional Stirling computational fluid dynamics code to significantly improve Stirling loss predictions and assist in identifying convertor areas for further improvements. This paper will update the status and results for these efforts.

Thieme, Lanny G.↗

Stirling Technology Development at NASA GRC

The Department of Energy, Stirling Technology Company (STC), and NASA Glenn Research Center (NASA Glenn) are developing a free-piston Stirling convertor for a high-efficiency Stirling Radioisotope Generator (SRG) for NASA Space Science missions. The SRG is being developed for multimission use, including providing electric power for unmanned Mars rovers and deep space missions. NASA Glenn is conducting an in-house technology project to assist in developing the convertor for space qualification and mission implementation. Recent testing, of 55-We Technology Demonstration Convertors (TDC's) built by STC includes mapping, of a second pair of TDC's, single TDC testing, and TDC electromagnetic interference and electromagnetic compatibility characterization on a nonmagnetic test stand. Launch environment tests of a single TDC without its pressure vessel to better understand the convertor internal structural dynamics and of dual-opposed TDC's with several engineering mounting structures with different natural frequencies have recently been completed. A preliminary life assessment has been completed for the TDC heater head, and creep testing of the IN718 material to be used for the flight convertors is underway. Long-term magnet aging tests are continuing to characterize any potential aging in the strength or demagnetization resistance of the magnets used in the linear alternator (LA). Evaluations are now beginning on key organic materials used in the LA and piston/rod surface coatings. NASA Glenn is also conducting finite element analyses for the LA, in part to look at the demagnetization margin on the permanent magnets. The world's first known integrated test of a dynamic power system with electric propulsion was achieved at NASA Glenn when a Hall-effect thruster was successfully operated with a free-piston Stirling power source. Cleveland State University is developing a multidimensional Stirling computational fluid dynamics code to significantly improve Stirling loss predictions and assist in identifying convertor areas for further improvements. This paper will update the status and results for these efforts.

Thieme, Lanny G.↗

Jet Propulsion Laboratory: Annual Report 1999

The Jet Propulsion Laboratory, located in the foothills near Pasadena, California, is the nation's lead center for the robotic exploration of space. Intense activity in space missions was the hallmark of the Jet Propulsion Laboratory as a new generation of smaller, less expensive spacecraft were sent out from Earth. From late 1998 to mid-1999, JPL launched a craft testing a futuristic ion engine, an orbiter and lander bound for Mars, a mission to fly by a comet and return a sample of its dust to Earth, a small infrared telescope, and an Earth-circling satellite that uses radar to gauge winds over the oceans. This unprecedented schedule resulted in spectacular achievements, tempered by highly visible mission losses. Weighed together, the successes and failures dramatically underscored the difficulty and risk involved in the unique business of space science and exploration. Among the achievements, the ion-engine-powered Deep Space 1, comet-bound Stardust and Earth-orbiting SeaWinds were joined by such ongoing missions as Mars Global Surveyor, Galileo and Cassini in delivering on their promise and, in some cases, providing surprising new views of space and Earth. At the same time, mission teams were disappointed by the losses of an orbiter and lander at Mars, as well as a small infrared telescope. JPL worked closely with NASA to learn from these experiences and build successful future missions. The Laboratory also achieved a key goal by winning the International Organization of Standards' 'ISO 9001' certification - a standard shared by the world's best engineering organizations. As the year rolled to a close, clocks rolled over from 1999 to 2000. Operations teams at JPL and NASA watched with satisfaction as a major campaign of Year 2000 readiness paid off with no problems among the thousands of computer systems that support the Laboratory's missions. With that auspicious beginning, JPL was positioned to step into the 21st century and embark on even yet unimagined future explorations.

Jet Propulsion Laboratory (JPL)↗

Experimental and Numerical Investigation of a Miniature Additively Manufactured Vortex Tube

Ranque–Hilsch vortex tubes are simple devices that can produce a cooling effect using compressed air. A key advantage of vortex tubes is the lack of moving solid parts; however, their efficiencies are relatively low. The present study focuses on the development of a miniature variable-diameter tube using additive manufacturing. A metal-based 3D printing technique was utilized to fabricate this vortex tube monolithically. Computational fluid dynamics simulations employing software STAR-CCM + with a compressible Reynolds-Averaged Navier–Stokes (RANS) approach and the elliptic-blending lag k-epsilon turbulence model have been applied to model thermofluid processes inside the vortex tube, to good agreement with the experiment. In conclusion, a temperature decrease of 13.3 °C and a cooling power of approximately 4 W were experimentally achieved with a pressure ratio of 4 in the air at normal conditions. This result shows promise for the goal of utilizing additive manufacturing to design and build complex-geometry vortex tubes intended for use with cryogenic fluids.

08 HYDROGEN↗

Optimization and Evaluation of Energy Savings for Connected and Autonomous Off-Road Vehicles

Off-road vehicles, such as wheel loaders, excavators, and harvesters, are extensively utilized across a wide range of industries, including construction, agriculture, and mining. These machines have become indispensable in supporting the day-to-day operational needs of a nation, playing a critical role in various sectors' infrastructure and productivity. However, despite their utility, off-road vehicles are significant consumers of fossil fuels, resulting in substantial emissions that contribute to environmental degradation. This highlights the pressing need for research and technological advancements aimed at improving their energy efficiency and reducing their carbon footprint. There are, however, two primary challenges that must be addressed to achieve these goals. First, off-road vehicles typically perform both driving and working tasks simultaneously, which introduces a high level of complexity into their overall dynamic systems. Analysis the interactions between these functions is challenging. Second, research into off-road vehicles is inherently interdisciplinary, demanding expertise across several domains such as fluid power systems, vehicle dynamics, control theory, optimization techniques, and real-world implementation. Recognizing these challenges, we proposed the project titled "Optimization and Evaluation of Energy Savings for Connected and Autonomous Off-Road Vehicles" as a comprehensive solution to enhance fuel efficiency while simultaneously improving productivity. This project specifically focuses on autonomous off-road vehicles, with particular attention to wheel loaders, and seeks to develop novel methods to optimize energy consumption without sacrificing operational performance. The project integrates real-time control algorithms, vehicle dynamics modeling, and co-optimization of powertrain system and vehicle system to achieve these goals. Our optimization strategy dynamically co-optimizes critical parameters at both the powertrain and vehicle levels, including vehicle speed, working tool movements, powertrain dynamics, and engine operations in real-time. To streamline this optimization process, we developed a vehicle model that captures the key dynamics while significantly enhancing computational efficiency. This allows the system to intelligently minimize fuel consumption, all while maintaining or even improving productivity through real-time calculations during various off-road operations. To validate the effectiveness of this energy optimization method, we introduced a state-of-the-art Hardware-in-the-Loop (HIL) testbed. This reconfigurable testbed seamlessly integrates the actual engine with virtual models of the wheel loader's subsystems, allowing for accurate emulation of real-world operational loads and environments. By simulating these conditions, the HIL testbed enables us to evaluate the wheel loader’s performance under diverse working scenarios, ensuring the developed solution is applicable in real-world operations. This testbed proved to be instrumental in validating the optimization algorithms and demonstrating the system's practical effectiveness. During the evaluation and testing phase, we employed the HIL testbed to rigorously assess the energy savings and productivity improvements generated by the optimized system. The results were highly encouraging, revealing that the automated wheel loader achieved over 30% fuel savings compared to traditional, human-operated cycles, with comparable or even enhanced levels of productivity. The insights gained from this HIL-based testing provided critical validation of our approach and highlighted the potential for deploying these optimized autonomous technologies in real-world off-road vehicles.

33 ADVANCED PROPULSION SYSTEMS↗

System Engineering on the Use for Ares I,V - the Simpler, the Better

The Ares I and Ares V Vehicles will utilize the J-2X rocket engine developed for NASA by the Pratt & Whitney Rocketdyne Company. The J-2X is an improved higher power version of the original J-2 engine used during the Apollo program. With higher power and updated requirements for safety and performance, the J-2X becomes a new engine using state-of-the-art design methodology, materials and manufacturing processes. The implementation of Systems Engineering (SE) principles enables the rapid J-2X development program to remain aligned with the ARES I and V vehicle programs, Meeting the aggressive development schedule is a challenge. Coordinating the best expertise thai NASA and PWR have to offer requires effectively utilizing resources at multiple sites. This presents formidable communication challenges. SE allows honest and open discussions of issues and problems. This simple idea is often overlooked in large and complex SE programs. Regular and effective meetings linking SE objectives to component designs are used to voice differences of opinions with customer and contractor in attendance so that the best mutual decisions can be made on the shortest possible schedule. Regular technical interchange meetings on secure program wide computer networks and CM processes are effective,in the "Controlled Change" process that exemplifies good SE. Good communication is a key effective SE implementation. The System of Systems approach is the vision of the Orion program which facilitates the establishment of dynamic SE processes at all levels including the engine. SE enables requirements evolution by facilitating organizational and process agility. Flow down and distribution of requirements is controlled by Allocation Reports which breakdown numerical design objectives (weight, reliability, etc.) into quanta goals for each component area. Linked databases of design and verification requirements helps eliminate redundancy and potential mistakes inherent m separated systems. Another tool, the Architecture Design Description, is being used to control J-2X system architecture and effectively communicate configuration changes to those involved in the design process. But the proof is in successful program accomplishment. The SE is the methodology being used to meet the challenge of completing J-2X engine certification 2 years ahead of any engine program ever developed at PWR. The Ares I SE system of systems has delivered according to expectations thus far. All major design reviews (SRR. PDR, CDR) have been successfully conducted to satisfy overall program objectives using SE as the basis for accomplishment. The paper describes SE tools and techniques utilized to achieve this success.

Kelly, William↗

liionpack: A Python package for simulating packs of batteries with PyBaMM

Electrification of transport and other energy intensive activities is of growing importance as it provides an underpinning method to reduce carbon emissions. With an increase in reliance on renewable sources of energy and a reduction in the use of more predictable fossil fuels in both stationary and mobile applications, energy storage will play a pivotal role and batteries are currently the most widely adopted and versatile form. Therefore, understanding how batteries work, how they degrade, and how to optimize and manage their operation at large scales is critical to achieving emission reduction targets. The electric vehicle (EV) industry requires a considerable number of batteries even for a single vehicle, sometimes numbering in the thousands if smaller cells are used, and the dynamics and degradation of these systems, as well as large stationary power systems, is not that well understood. As increases in the efficiency of a single battery become diminishing for standard commercially available chemistries, gains made at the system level become more important and can potentially be realised more quickly compared with developing new chemistries. Mathematical models and simulations provide a way to address these challenging questions and can aid the engineer and designers of batteries and battery management systems to provide longer lasting and more efficient energy storage systems.

25 ENERGY STORAGE↗

Input specific neural networks

Neural networks have emerged as powerful tools for mapping between inputs and outputs. However, their black-box nature limits the ability to encode or impose specific structural relationships between inputs and outputs. Many scientific and engineering problems, such as constitutive modeling in solid mechanics, require networks that can enforce convexity, monotonicity, or other structural constraints to ensure physical consistency. Here, we introduce the Input Specific Neural Network (ISNN), a new architecture that enables multiple, distinct constraints to be imposed on different input subsets for scalar-valued outputs. This framework unifies convex, monotone–convex, monotone, and arbitrary mappings within a single network for the first time. Two ISNN architectures with analytical first- and second-order derivatives are developed. We demonstrate the performance on synthetic toy problems, inverse problems in isotropic hyperelasticity, and finite element simulations. ISNNs achieve improved extrapolation behavior, require fewer invariant inputs than standard input convex networks for polyconvex potentials, and enable significant computational savings via manual differentiation. We also show how ISNNs can be used to learn structural relationships between inputs and outputs via a binary gating mechanism. Particularly, ISNNs are employed to model a homogenized anisotropic free energy potential in a decoupled multiscale setting. The network learns whether or not the potential should be modeled as polyconvex and retains only the relevant layers while using the minimum number of inputs. ISNNs provide a flexible foundation for embedding structural priors into neural networks, enhancing both interpretability and stability. They are broadly applicable across computational mechanics and other scientific domains requiring constrained functional relationships.

Jadoon, Asghar A. [Univ. of Texas, Austin, TX (Uni↗

Moltensaltpropnet

MoltenSaltPropnet is a physics-informed machine learning framework that aims to predict the thermophysical properties of molten fluoride and chloride salt mixtures, which are crucial for the design and safety of Generation IV molten salt reactors. The code processes data from the Molten-Salt Thermal Properties Database (MSTDB-TP) and the Janz compendium, converting critically evaluated correlations into fast, differentiable surrogate models for density, viscosity, thermal conductivity, and heat capacity across 448 distinct salt systems. The implementation consists of several key components: 1. Data Curation: The code parses and cleans the raw data, normalizing elemental mole fractions and extracting relevant regression coefficients for various thermophysical properties. 2. Feature Engineering: It generates fixed-length numerical descriptors that encapsulate the composition and temperature, incorporating polynomial interaction terms and dimensionality-reduction techniques to optimize model performance. 3. Coefficient Learning: Four different machine learning architectures are employed: a deep residual network (ResNet), a Kolmogorov–Arnold network (KAN), a sparsity-inducing neural network (SNN), and classical regression models. Each model learns to predict coefficients that define the temperature-dependent correlations for the thermophysical properties. 4. Property Reconstruction: The predicted coefficients are used to compute temperature-dependent property values, ensuring positivity and monotonic trends through a composite loss function that enforces physical constraints. 5. User Interface: An open-source web application enables users to filter the database, train task-specific models, and visualize the results, allowing for rapid exploration of candidate salt mixtures. MoltenSaltPropnet bridges the gap between limited experimental data and high-fidelity reactor simulations, providing a powerful tool for researchers in the field of molten salt reactors and advanced nuclear energy systems.

Retamales, Mauricio Eduardo Tano [Idaho National L↗

Two Dimensional Viscoelastic Stress Analysis of a Prototypical JIMO Turbine Wheel

The designers of the Jupiter Icy Moons Orbiter (JIMO) are investigating the potential of nuclear powered-electric propulsion technology to provide deep space propulsion. In one design scenario a closed-Brayton-cycle power converter is used to convert thermal energy from a nuclear reactor to electrical power for the spacecraft utilizing an inert gas as the working fluid to run a turboalternator as described in L.S. Mason, "A Power Conversion for the Jupiter Icy Moons Orbiter," Journal of Propulsion and Power, vol. 20, no. 5, pp. 902-910. A key component in the turboalternator is the radial flow turbine wheel which may be fabricated from a cast superalloy. This turbine wheel is envisioned to run continuously over the life of the mission, which is anticipated to be about ten years. This scenario places unusual material requirements on the turbine wheel. Unlike the case of terrestrial turbine engines, fatigue, associated with start-up and shut-down of the engine, foreign-object damage, and corrosion issues are insignificant and thus creep issues become dominate. The purpose of this paper is to present estimates for creep growth of a prototypical JIMO turbine wheel over a ten year life. Since an actual design and bill of materials does not exist, the results presented in this paper are based on preliminary concepts which are likely to evolve over time. For this reason, as well as computational efficiency, a simplified 2-D, in lieu of a 3-D, viscoelastic, finite element model of a prototypical turbine wheel will be utilized employing material properties for the cast superalloy MAR-M247. The creep data employed in this analysis are based on preliminary data being generated at NASA Glenn Research Center.

Gayda, John↗

Spinoff 2010

Topics covered include: Burnishing Techniques Strengthen Hip Implants; Signal Processing Methods Monitor Cranial Pressure; Ultraviolet-Blocking Lenses Protect, Enhance Vision; Hyperspectral Systems Increase Imaging Capabilities; Programs Model the Future of Air Traffic Management; Tail Rotor Airfoils Stabilize Helicopters, Reduce Noise; Personal Aircraft Point to the Future of Transportation; Ducted Fan Designs Lead to Potential New Vehicles; Winglets Save Billions of Dollars in Fuel Costs; Sensor Systems Collect Critical Aerodynamics Data; Coatings Extend Life of Engines and Infrastructure; Radiometers Optimize Local Weather Prediction; Energy-Efficient Systems Eliminate Icing Danger for UAVs; Rocket-Powered Parachutes Rescue Entire Planes; Technologies Advance UAVs for Science, Military; Inflatable Antennas Support Emergency Communication; Smart Sensors Assess Structural Health; Hand-Held Devices Detect Explosives and Chemical Agents; Terahertz Tools Advance Imaging for Security, Industry; LED Systems Target Plant Growth; Aerogels Insulate Against Extreme Temperatures; Image Sensors Enhance Camera Technologies; Lightweight Material Patches Allow for Quick Repairs; Nanomaterials Transform Hairstyling Tools; Do-It-Yourself Additives Recharge Auto Air Conditioning; Systems Analyze Water Quality in Real Time; Compact Radiometers Expand Climate Knowledge; Energy Servers Deliver Clean, Affordable Power; Solutions Remediate Contaminated Groundwater; Bacteria Provide Cleanup of Oil Spills, Wastewater; Reflective Coatings Protect People and Animals; Innovative Techniques Simplify Vibration Analysis; Modeling Tools Predict Flow in Fluid Dynamics; Verification Tools Secure Online Shopping, Banking; Toolsets Maintain Health of Complex Systems; Framework Resources Multiply Computing Power; Tools Automate Spacecraft Testing, Operation; GPS Software Packages Deliver Positioning Solutions; Solid-State Recorders Enhance Scientific Data Collection; Computer Models Simulate Fine Particle Dispersion; Composite Sandwich Technologies Lighten Components; Cameras Reveal Elements in the Short Wave Infrared; Deformable Mirrors Correct Optical Distortions; Stitching Techniques Advance Optics Manufacturing; Compact, Robust Chips Integrate Optical Functions; Fuel Cell Stations Automate Processes, Catalyst Testing; Onboard Systems Record Unique Videos of Space Missions; Space Research Results Purify Semiconductor Materials; and Toolkits Control Motion of Complex Robotics.

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