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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 325 records · Page 18

Smart Monitoring and Diagnostic System (SMDS) for Packaged Air Conditioners and Heat Pumps for Small/Medium Commercial Buildings: Preparation for Commercialization: CRADA 478 [Abstract only]

This project will enable Pacific Northwest National Laboratory (PNNL) and industry partner, mCloud Technologies, to work collaboratively to ready the Smart Monitoring and Diagnostic System (SMDS) for commercial deployment and validate its performance under real-world conditions at field sites. This project will specifically focus on 1) implementing the SMDS algorithms in a scalable cloud-based software architecture, 2) designing new, innovative, complimentary commercial services based on the SMDS, 3) enhancing the SMDS energy and cost impact algorithms to reduce uncertainty in estimates, 4) determining the lower limits on SMDS performance degradation detection, 5) validating algorithm performance and default values of adjustable thresholds with existing data from controlled physical testing and from customer packaged air conditioners and heat pumps (commonly referred to as rooftop units or RTUs), 6) field testing to validate the system on multiple customer buildings in diverse environments, and 7) expanding field deployment to a larger set of mCloud’s customer buildings. Project results by validating, enhancing, and quantifying the performance of the SMDS will position mCloud, and potential future licensees, to implement the SMDS in commercial offerings that encourage and enable use of condition-based and predictive maintenance, leading to significant reductions in energy use and greenhouse gas emissions associated with space conditioning by RTUs. Furthermore, these enhancements will increase the value of the SMDS for users and increase the potential market for its use and impacts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

In-Flight Verification and Validation of Colloid Microthruster Performance

Colloid Micronewton Thrusters (CMNTs) use an electrospray to provide precision spacecraft position and pointing control. They were demonstrated in space for the first time as part of NASA’s Space Technology 7 (ST7) payload hosted by the European Space Agency’s (ESA’s) LISA Pathfinder (LPF) technology demonstration mission in January, 2016. CMNTs were the actuator in the disturbance reduction system (DRS) that provided drag-free operation of the LPF spacecraft, which will be necessary for future gravity wave observatories such as ESA’s Laser Interferometer Space Antenna (LISA) mission, currently in Phase A and scheduled for launch in 2034. The CMNT technology met performance requirements operating at 5-30 µN of thrust with 0.1 µN resolution and ≤0.1 µN/ÖHz thrust noise to deliver the required nanometer-level precision spacecraft control measured by the gravitational reference sensor (GRS) in the ESA LISA Technology Package (LTP). The performance of seven of the eight CMNTs in flight was consistent with ground test results, and as a system, all eight thrusters met mission-level performance requirements. The colloid microthruster performance model of thrust and thrust noise as a function of operational parameters (i.e. beam current, voltage, temperature, etc.) was validated in flight over a wide range of conditions. A model and simulation of the thruster control algorithm was developed and validated with flight data to predict thrust noise. This capability is important for future missions because it relates directly to the acceleration noise on the test masses, which provide the gravity wave measurements. The CMNT thruster model data and validation with LISA Pathfinder/ST7-DRS flight experiments are presented in this paper.

"O'Donnell, James"↗

hippynn Python Package

hippynn is a python package for defining, training, and applying neural networks to atomistic systems. In particular, it focuses on Hierarchical Interacting Particle Neural Networks (HIP-NNs), a deep learning architecture for atomistic systems. HIP-NNs take input data describing the properties of atomistic systems (often generated using ab-initio quantum mechanics) to learn fast and accurate models. A trained HIP-NN can predict potential energy surfaces, atomic charges, and more. hippynn uses PyTorch for portable high-performance code, including both CPU and GPU support. hippynn allows for extensive customization, including user-defined models and loss functions, to facilitate future research into extensions of HIP-NN as well as other atomistic deep learning models.

Lubbers, Nicolas↗

CostMAP: an open-source software package for developing cost surfaces using a multi-scale search kernel

Cost surfaces are a crucial aspect of route optimization and least cost path (LCP) calculations and are used in awide range of disciplines including computer science, landscape ecology, and energy-infrastructure modeling. Linear features introduce akey weakness to traditional routing calculations along cost surfaces because they cannot identify whether moving from acell to its adjacent neighbors constitutes crossing alinear barrier (increased cost) or following acorridor (reduced cost). Following and avoiding linear features can drastically change predicted routes. We introduce an approach to address this adjacency issue using asearch kernel that determines these critical barriers and corridors. We have built this method into anew Java-based open-source software package– CostMAP (cost surface multi-layer aggregation program)– which calculates cost surfaces and cost networks using the search kernel. CostMAP allows users to input multiple GIS data layers and to set weights and rules for developing aweighted-cost network. We compare CostMAP performance with traditional cost surface approaches and show significant performance gains– both following corridors and avoiding barriers– by modeling the movement of alarge terrestrial animal– the Baird’s Tapir (Tapirus bairdii)– in amovement ecology framework and by modeling pipeline routing for carbon capture and storage (CCS).

58 GEOSCIENCES↗

Computer method for design of acoustic liners for turbofan engines

A design package is presented for the specification of acoustic liners for turbofans. An estimate of the noise generation was made based on modifications of existing noise correlations, for which the inputs are basic fan aerodynamic design variables. The method does not predict multiple pure tones. A target attenuation spectrum was calculated which was the difference between the estimated generation spectrum and a flat annoyance-weighted goal attenuated spectrum. The target spectrum was combined with a knowledge of acoustic liner performance as a function of the liner design variables to specify the acoustic design. The liner design method at present is limited to annular duct configurations. The detailed structure of the liner was specified by combining the required impedance (which is a result of the previous step) with a mathematical model relating impedance to the detailed structure. The design procedure was developed for a liner constructed of perforated sheet placed over honeycomb backing cavities. A sample calculation was carried through in order to demonstrate the design procedure, and experimental results presented show good agreement with the calculated results of the method.

Minner, G. L.↗

A stochastic optimal feedforward and feedback control methodology for superagility

A new control design methodology is developed: Stochastic Optimal Feedforward and Feedback Technology (SOFFT). Traditional design techniques optimize a single cost function (which expresses the design objectives) to obtain both the feedforward and feedback control laws. This approach places conflicting demands on the control law such as fast tracking versus noise atttenuation/disturbance rejection. In the SOFFT approach, two cost functions are defined. The feedforward control law is designed to optimize one cost function, the feedback optimizes the other. By separating the design objectives and decoupling the feedforward and feedback design processes, both objectives can be achieved fully. A new measure of command tracking performance, Z-plots, is also developed. By analyzing these plots at off-nominal conditions, the sensitivity or robustness of the system in tracking commands can be predicted. Z-plots provide an important tool for designing robust control systems. The Variable-Gain SOFFT methodology was used to design a flight control system for the F/A-18 aircraft. It is shown that SOFFT can be used to expand the operating regime and provide greater performance (flying/handling qualities) throughout the extended flight regime. This work was performed under the NASA SBIR program. ICS plans to market the software developed as a new module in its commercial CACSD software package: ACET.

Halyo, Nesim↗

A Mesh-Free Method to Predictively Simulate Solid-to-Liquid Phase Transitions in Abnormal Thermal Environments

Particle methods in computational physics are useful for modeling the motion of fluids and solids subject to large deformations. Under these conditions, mesh-based approaches often fail due to decreasing element quality leading to inaccuracy and instability. The developed software package called Moab investigates and prototypes next-generation particle methods, focusing on rigorous error analysis and active error minimization strategies during the computation. The present work discusses examples calculations representative of real engineering problems with quantified and maximized accuracy while demonstrating the potential for meeting engineering performance requirements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Crowd Sourcing for Challenging Technical Problems and Business Model

Crowd sourcing may be defined as the act of outsourcing tasks that are traditionally performed by an employee or contractor to an undefined, generally large group of people or community (a crowd) in the form of an open call. The open call may be issued by an organization wishing to find a solution to a particular problem or complete a task, or by an open innovation service provider on behalf of that organization. In 2008, the Space Life Sciences Directorate (SLSD), with the support of Wyle Integrated Science and Engineering, established and implemented pilot projects in open innovation (crowd sourcing) to determine if these new internet-based platforms could indeed find solutions to difficult technical challenges. These unsolved technical problems were converted to problem statements, also called "Challenges" or "Technical Needs" by the various open innovation service providers, and were then posted externally to seek solutions. In addition, an open call was issued internally to NASA employees Agency wide (10 Field Centers and NASA HQ) using an open innovation service provider crowd sourcing platform to post NASA challenges from each Center for the others to propose solutions). From 2008 to 2010, the SLSD issued 34 challenges, 14 externally and 20 internally. The 14 external problems or challenges were posted through three different vendors: InnoCentive, Yet2.com and TopCoder. The 20 internal challenges were conducted using the InnoCentive crowd sourcing platform designed for internal use by an organization. This platform was customized for NASA use and promoted as NASA@Work. The results were significant. Of the seven InnoCentive external challenges, two full and five partial awards were made in complex technical areas such as predicting solar flares and long-duration food packaging. Similarly, the TopCoder challenge yielded an optimization algorithm for designing a lunar medical kit. The Yet2.com challenges yielded many new industry and academic contacts in bone imaging, microbial detection and even the use of pharmaceuticals for radiation protection. The internal challenges through NASA@Work drew over 6000 participants across all NASA centers. Challenges conducted by each NASA center elicited ideas and solutions from several other NASA centers and demonstrated rapid and efficient participation from employees at multiple centers to contribute to problem solving. Finally, on January 19, 2011, the SLSD conducted a workshop on open collaboration and innovation strategies and best practices through the newly established NASA Human Health and Performance Center (NHHPC). Initial projects will be described leading to a new business model for SLSD.

Davis, Jeffrey R.↗

Incorporating Oxygen Uncoupling Kinetics into Computational Fluid Dynamic Simulations of a Chemical Looping System

Chemical looping with oxygen uncoupling (CLOU) is a carbon-capture technology that utilizes a metal oxide as an oxygen carrier to separate oxygen from air and releases gaseous O 2 into a reactor where fuel is fed. Earlier experimental and simulated work has been performed on systems less than 1 MW. Previous work has been limited to one-dimensional kinetic simulations. Literature kinetics were modified to work in a Barracuda-VR simulation package. A simplified spreadsheet model was used to verify the Barracuda-VR simulation adaption of the kinetics to previously published results. The simulated kinetics, literature models, and raw data matched well. The adapted kinetics were then incorporated into a 10 kW dual bubbling bed CLOU system three-dimensional simulation. The simulations predicted carbon capture efficiency similar to that reported previously for similar systems. The solid circulation rate, temperature profile, and gas concentration profiles followed the expected trends. The overall three-dimensional simulation of kinetics showed reasonable results for what has been previously reported.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

By Hand or Not By-Hand: A Case Study of Alternative Approaches to Parallelize CFD Applications

While parallel processing promises to speed up applications by several orders of magnitude, the performance achieved still depends upon several factors, including the multiprocessor architecture, system software, data distribution and alignment, as well as the methods used for partitioning the application and mapping its components onto the architecture. The existence of the Gorden Bell Prize given out at Supercomputing every year suggests that while good performance can be attained for real applications on general purpose multiprocessors, the large investment in man-power and time still has to be repeated for each application-machine combination. As applications and machine architectures become more complex, the cost and time-delays for obtaining performance by hand will become prohibitive. Computer users today can turn to three possible avenues for help: parallel libraries, parallel languages and compilers, interactive parallelization tools. The success of these methodologies, in turn, depends on proper application of data dependency analysis, program structure recognition and transformation, performance prediction as well as exploitation of user supplied knowledge. NASA has been developing multidisciplinary applications on highly parallel architectures under the High Performance Computing and Communications Program. Over the past six years, the transition of underlying hardware and system software have forced the scientists to spend a large effort to migrate and recede their applications. Various attempts to exploit software tools to automate the parallelization process have not produced favorable results. In this paper, we report our most recent experience with CAPTOOL, a package developed at Greenwich University. We have chosen CAPTOOL for three reasons: 1. CAPTOOL accepts a FORTRAN 77 program as input. This suggests its potential applicability to a large collection of legacy codes currently in use. 2. CAPTOOL employs domain decomposition to obtain parallelism. Although the fact that not all kinds of parallelism are handled may seem unappealing, many NASA applications in computational aerosciences as well as earth and space sciences are amenable to domain decomposition. 3. CAPTOOL generates code for a large variety of environments employed across NASA centers: MPI/PVM on network of workstations to the IBS/SP2 and CRAY/T3D.

Yan, Jerry C.↗

Predicting and Managing Lighting and Visibility for Human Operations in Space

Lighting is critical to human visual performance. On earth this problem is well understood and solutions are well defined and executed. Because the sun rises and sets on average every 45 minutes during Earth orbit, humans working in space must cope with ~ extremely dynamic lighting conditions varying from very low light conditions to severe glare and contrast conditions. For critical operations, it is essential that lighting conditions be predictable and manageable. Mission planners need to detelmine whether low-light video cameras are required or whether additional luminaires, or lamps, need to be flown . Crew and flight directors need to have up to date daylight orbit time lines showing the best and worst viewing conditions for sunlight and shadowing. Where applicable and possible, lighting conditions need to be part of crew training. In addition, it is desirable to optimize the quantity and quality of light because of the potential impacts on crew safety, delivery costs, electrical power and equipment maintainability for both exterior and interior conditions. Addressing these issues, an illumination modeling system has been developed in the Space Human Factors Laboratory at ASA Johnson Space Center. The system is the integration of a physically based ray-tracing package ("Radiance"), developed at the Lawrence Berkeley Laboratories, a human factors oriented geometric modeling system developed by NASA and an extensive database of humans and their work environments. Measured and published data has been collected for exterior and interior surface reflectivity; luminaire beam spread distribution, color and intensity and video camera light sensitivity and has been associated with their corresponding geometric models. Selecting an eye-point and one or more light sources, including sun and earthshine, a ~ snapshot of the light energy reaching the surfaces or reaching the eye point is computed. This energy map is then used to extract the required information needed for useful predictions. Using a validated, comprehensive illumination model integrated with empirically derived data, predictions of lighting and viewing conditions have been successfully used for Shuttle and Space Station planning and assembly operations. It has successfully balanced the needs for adequate human performance with the utili zation of resources. Keywords: Modeling, ray tracing, luminaires, refl ectivity, luminance, illuminance.

Maida, James C.↗

Structural and magnetic phase transition in samarium hydrogen system SmH{sub x} (x=1, 2, 3)

We report ab-initio calculations for the structural and magnetic phase transition of SmH{sub x} (x= 1, 2, 3) using the Vienna ab-initio simulation package (VASP). The non-spin polarized (NSP) and spin polarized (SP) calculations are performed for these hydrides at normal and high pressure. It is found that these compounds are stable in ferromagnetic state at normal pressure. The calculated lattice parameters and bulk modulus of these hydrides are in good agreement with the available experimental results. A pressure-induced structural phase transition from cubic to hexagonal phase in SmH and SmH{sub 2} and hexagonal to cubic phase in SmH{sub 3} is predicted. A pressure-induced ferromagnetic to nonmagnetic phase transition is observed in SmH, SmH{sub 2} and SmH{sub 3} at the pressures of 104 GPa, 76 GPa and 81 GPa respectively. Ferromagnetism is quenched in mono, di and tri hydrides at high pressures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Perfect crystal propagator for physical optics simulations with Synchrotron Radiation Workshop

Until now, a treatment of dynamical diffraction from perfect crystals has been missing in the "Synchrotron Radiation Workshop" (SRW) wavefront propagation computer code despite the widespread use of crystals on X-ray synchrotron beamlines. Now a special propagator" module for calculating dynamical diffraction from a perfect crystal in the Bragg case has been written in C++, integrated into the SRW C/C++ library and made available for simulations using the Python interface of SRW. The propagator performs local processing of the frequency-domain electric field in the angular representation. A 2-D Fast Fourier Transform is used for changing the field representation from/to the coordinate representation before and after applying the crystal propagator. This ensures seamless integration of the new propagator with the existing functionalities of the SRW package, allows compatibility with existing propagators for other optical elements, and enables the simulation of complex beamlines transporting partially coherent X-rays. The code has been benchmarked by comparison with predictions made by plane-wave and spherical-wave dynamical diffraction theory. Test simulations for a selection of X-ray synchrotron beamlines are also shown.

47 OTHER INSTRUMENTATION↗

PyJMAK: An Open-Source Python Toolkit for Modeling Solid-State Metallurgical Phase Transformations

Accurate prediction of metallurgical phase transformations is an essential basis for autonomous optimization and rapid part qualification. Several methods can be used to estimate the evolution of phase fractions such as JMAK kinetics-based models, phase-field models, thermodynamic models, and data-driven machine learning models. Thermodynamic and phase-field-based methodologies solve multiphysics equations requiring numerous calibration parameters and significant computational resources. As a result, the computation domain is limited to a point or on order of micron-meters. The data-driven models rely on large datasets from experiments and simulations. While the JMAK model only provides information about phase fraction evolution, it can predict this evolution in near real-time using thermal history and thermodynamic data without restriction on the domain. JMAK models have been popularly used by researchers to model phase transformations occuring during additive manufacturing or over arbitrary temperature profiles. Commercial proprietary software such as Abaqus and Ansys or closed-source in-house implementations offer the ability to model JMAK based kinetics to predict phase transformation. However, these software packages are not open-source or freely available for use and development in conjunction with manufacturing machines, sensors, and machine learning algorithms. In addition, the use of the model is restricted by a license token. In contrast, given temperature profiles at multiple points in the domain, this Python-based PyJMAK model can compute phase evolution in parallel due to its stand-alone modular, voxel-based structure, and it can be executed on high-performance computing resources without any license restrictions.

Prabhune, Bhagya [Oak Ridge National Laboratory (O↗

Qualification of the Tropical Rainfall Measuring Mission Solar Array Deployment System

The Tropical Rainfall Measuring Mission (TRMM) solar arrays are placed into orbital configuration by a complex deployment system. Its two wings each comprise twin seven square solar panels located by a twelve foot articulated boom. The four spring-driven hinge lines per wing are rate-limited by viscous dampers. The wings are stowed against the spacecraft kinematically, and released by five pyrotechnically-actuated mechanisms. Since deployment failure would be catastrophic, a total of 17 deployment tests were completed to qualify the system for the worst cast launch environment. This successful testing culminated in the flawless deployment of the solar arrays on orbit, 15 minutes after launch in November 1997. The custom gravity negation system used to perform deployment testing is modular to allow its setup in several locations, including the launch site in Japan. Both platform and height can be varied, to meet the requirements of the test configuration and the test facility. Its air pad floatation system meets tight packaging requirements, allowing installation while stowed against the spacecraft without breaking any flight interfaces, and avoiding interference during motion. This system was designed concurrently with the deployment system, to facilitate its installation, to aid in the integration of the flight system to the spacecraft, while demonstrating deployment capabilities. Critical parameters for successful testing were alignment of deployment axes and tables to gravity, alignment of table seams to minimize discontinuities, and minimizing pressure drops in the air supply system. Orbital performance was similar to that predicted by ground testing.

Lawrence, Jon↗

Hybrid Propulsion In-Situ Resource Utilization Test Facility Results

Hybrid rockets present a promising alternative to conventional chemical propulsion systems for In-Situ Resource Utilization (ISRU) and in-space applications. While they have many benefits for these applications, there are still many small details that require research before they can be adopted into flight systems. A flexible test facility was developed at JPL to test operation of hybrid motors at small scale (5 cm outer diameter fuel grains) over a range of conditions. Specifically, this paper studies two of the major advantages: low temperature performance and throttling. Paraffin-based hybrid rockets are predicted to have good performance at low temperatures. This could significantly decrease the overall system mass by minimizing the thermal conditioning required for Mars or outer planet applications. Therefore, the coefficient of thermal expansion and glass transition of paraffin are discussed. Additionally, deep throttling has been considered for several applications. This was a natural starting point for hotfire testing using the hybrid propulsion ISRU test facility. Additionally, short length to diameter ratio (L/D) fuel grains are tested to determine if these systems can be packaged into geometrically constrained spaces.

Karp, Ashley Chandler↗

Machine Learning Surrogates of a Fuel Matrix Degradation Process Model for Performance Assessment of a Nuclear Waste Repository

Spent nuclear fuel repository simulations are currently not able to incorporate detailed fuel matrix degradation (FMD) process models due to their computational cost, especially when large numbers of waste packages breach. The current paper uses machine learning to develop artificial neural network and k-nearest neighbor regression surrogate models that approximate the detailed FMD process model while being computationally much faster to evaluate. Further, using fuel cask temperature, dose rate, and the environmental concentrations of CO 3 2- , O 2 , Fe 2+ , and H 2 as inputs, these surrogates show good agreement with the FMD process model predictions of the UO 2 degradation rate for conditions within the range of the training data. A demonstration in a full-scale shale repository reference case simulation shows that the incorporation of the surrogate models captures local and temporal environmental effects on fuel degradation rates while retaining good computational efficiency.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗