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This report contains the summary of work accomplished during summer of 2000 by Mr. Chad Hammons, undergraduate senior student, Mississippi State University/ERC in support of NASA/MSFC mission pertinent to Altitude compensating nozzle concepts evaluations. In particular, the development of automatic grid generator applicable in conducting sensitivity analysis involving Aerospike engine is described.
One of NASA's key goals is to increase the safety and reduce the cost of space transportation. Thus, a key element of NASA's new Integrated Space Transportation Plan is to develop new propulsion, structures, and operations for future generations of reusable launch vehicles (RLVs). As part of this effort to develop the next RLV, the ClCT Program's Computing, Networking, and Information Systems (CNIS) Project is developing and demonstrating collaborative software technologies that use the collective power of the NASA Grid to accelerate spacecraft design. One of these technologies, called AeroDB, automates the execution and monitoring of computational fluid dynamics (CFD) parameter studies on the NASA Grid. About the NASA Grid The NASA Grid, or Information Power Grid,. is being developed to leverage the distributed resources of NASA's many computers. instruments, simulators, and data storage systems. The goal is to use these combined resources to sdve difficult NASA challenges, such as iimulating the entire flight of a space vehicle from ascent to descent.To realize the vision of the NASA Grid, the CNIS Project is developing the software framework and protocols for building domain-specific environments and interfaces, new Grid services based on emerging industry standards, and advanced networking and computing testbeds to support new Grid-based applications such as AeroDB.
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In the U.S., building sector is responsible for around 40% of total energy consumption and contributes about 40% of carbon emissions since 2012. Within the past several years, various optimization models and control strategies have been studied to improve buildings energy efficiency and reduce operational expenses under the constraints of satisfying occupants’ comfort requirements. However, the majority of these studies consider building electricity demand and thermal load being satisfied by unidirectional electricity flow from the power grid or on-site renewable energy generation to electrical and thermal home appliances. Opportunities for leveraging low grade heat for electricity have largely been overlooked due to impracticality at small scale. In 2016, a modular pumped hydro storage technology was invented in Oak Ridge National Laboratory, named Ground Level Integrated Diverse Energy Storage (GLIDES). In GLIDES, employing high efficiency hydraulic machinery instead of gas compressor/turbine, liquid is pumped to compress gas inside high-pressure vessel creating head on ground-level. This unique design eliminates the geographical limitation associated with existing state of the art energy storage technologies. It is easy to be scaled for building level, community level and grid level applications. Using this novel hydro-pneumatic storage technology, opportunities for leveraging low-grade heat in building can be economical. In this research, the potential of utilizing low-grade thermal energy to augment electricity generation of GLIDES is investigated. Since GLIDES relies on gas expansion in the discharge process and the gas temperature drops during this non-isothermal process, available thermal energy, e.g. from thermal storage, Combined Cooling, Heat and Power system (CCHP), can be utilized by GLIDES to counter the cooling effect of the expansion process and elevate the gas temperature and pressure and boost the roundtrip efficiency. Several groups of comparison experiments have been conducted and the experimental results show that a maximum 12.9% cost saving could be achieved with unlimited heat source for GLIDES, and a moderate 3.8% cost improvement can be expected when operated coordinately with CCHP and thermal energy storage in a smart building.
This presentation discusses the potential to link clean energy and chemicals for a wide range of applications: transportation, grid, industry, buildings, agriculture (cross-sector coupling).
With support from the Competitiveness Improvement Project's System Optimization Award, Carter Wind Energy aims to lower the cost of distributed wind technology and expand deployment. To do so, the company will improve the cost-effectiveness and reliability of midsize wind turbines for remote, off-grid power applications, creating new wind energy deployment opportunities worldwide. This fact sheet provides an overview of Carter Wind Energy's project, how the company will achieve the goals of the award, and how the project fits within the overall Competitiveness Improvement Project.
The electric grid is becoming increasingly cyber-physical with the addition of smart technologies, new communication interfaces, and automated grid-support functions. Because of this, it is no longer sufficient to only study the physical system dynamics, but the cyber system must also be monitored as well to examine cyber-physical interactions and effects on the overall system. To address this gap for both operational and security needs, cyber-physical situational awareness is needed to monitor the system to detect any faults or malicious activity. Techniques and models to understand the physical system (the power system operation) exist, but methods to study the cyber system are needed, which can assist in understanding how the network traffic and changes to network conditions affect applications such as data analysis, intrusion detection systems (IDS), and anomaly detection. In this paper, we examine and develop models of data flows in communication networks of cyber-physical systems (CPSs) and explore how network calculus can be utilized to develop those models for CPSs, with a focus on anomaly and intrusion detection. This provides a foundation for methods to examine how changes to behavior in the CPS can be modeled and for investigating cyber effects in CPSs in anomaly detection applications.
JPL, in a partnership with an industrial consortium, is currently engaged in the investigation of reliability and quality issues if ball grid array (BGA) packages as they may be applied to space flight electronics. Performing tests to determine the solder joint reliability of assemblies using BGAs under temperature cycling has proved to be a real challenge for test engineers.
The purpose of this report is to arm relevant decision makers with the initial layer of information they need to understand energy storage and to make informed policy, regulatory, and investment decisions around grid-connected energy storage. While many of the case studies presented in this report are based on experiences from the U.S. and Europe, the lessons learned can be applied to power sectors in emerging economies. Importantly, this report covers topics related grid-connected energy storage for power sector applications. The term “grid-connected” implies that the storage system is interconnected to a centralized power system. Topics related to off-grid, micro-grid and mini-grid energy storage applications are not covered in this report, nor are procurement practices for energy storage.
A new two-dimensional approximate Riemann solver has been developed that obtains fluxes on grid faces via wave decomposition. By utilizing information propagation in the velocity-difference directions rather than in the grid-normal directions, this flux function more appropriately interprets and hence more sharply resolves shock and shear waves when they lie oblique to the grid. The model uses five waves to describe the difference in states at a grid face. Two acoustic waves, one shear wave, and one entropy wave propagate in the direction defined by the local velocity difference vector, while the fifth wave is a shear wave that propagates at a right angle to the other four. Test cases presented include a shock reflecting off a wall, a pure shear wave, supersonic flow over an airfoil, and viscous separated airfoil flow. Results using the new model give significantly sharper shock and shear contours than a grid-aligned solver. Navier-Stokes computations over an aifoil show reduced pressure distortions in the separated region as a result of the grid-independent upwinding.
This issue of the ASME Journal of Engineering for Sustainable Buildings and Cities (JESBC) is fully dedicated to peer-reviewed papers specific to technologies and applications of Grid-interactive Efficient Buildings (GEBs). As defined by a series of publications by the U.S. Department of Energy (DOE) and outlined in Part 1 of the editorial of JESBC August 2020 issue, GEBs are efficient, connected, smart, and flexible buildings. This GEB special issue covers some technologies and applications for grid-connected buildings and communities. Some of technologies included in the special issue are dynamic insulation systems for building envelopes, building integrated fuel cells, and rooftop PV systems. Furthermore, the issue outlines the designs and cost-benefits of net-zero energy (NZE) buildings and carbon neutral communities in the United States.
MAG3D (multiblock adaptive grid, 3D) is a 3D solution-adaptive grid generation code which redistributes grid points to improve the accuracy of a flow solution without increasing the number of grid points. The code is applicable to structured grids with a multiblock topology. It is independent of the original grid generator and the flow solver. The code uses the coordinates of an initial grid and the flow solution interpolated onto the new grid. MAG3D uses a numerical mapping and potential theory to modify the grid distribution based on properties of the flow solution on the initial grid. The adaptation technique is discussed, and the capability of MAG3D is demonstrated with several internal flow examples. Advantages of using solution-adaptive grids are also shown by comparing flow solutions on adaptive grids with those on initial grids.
The variable resolution stretched grid (SG) version of the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS) incorporating the GEOS SG-GCM, is used for regional analysis, forecast, and climate applications. The region of interest with enhanced horizontal resolution, mostly used in experiments, is a rectangle over the U.S. The SG-DAS is capable of reproducing regional mesoscale fields, patterns and diagnostics that are not produced by the medium uniform resolution run with the same amount of grid points as for the SG. The SG-DAS regional analyses and diagnostics are used for: validation of regional climate simulation experiments produced with the SG-GCM for the U.S. 1988 summer drought; and are planned to be used for atmospheric chemistry transport experiments. Also, a case study is conducted on a super-typhoon development in December 1997. The SG-DAS appears to be a viable candidate for a variety of regional studies and applications.
The application of various Fourier filtering techniques in a coarse resolution grid point model and the poor simulation of the nonlinear effects responsible for change in the mean zonal flow is discussed. The poor simulation results in spurious energy and momentum transfers. An operational filter, a second order filter on a staggered grid, a fourth order filter on a nonstaggered grid, and a biharmonic diffusion filter were considered.
A directional-split, modular, user-friendly grid point distribution code is applied to several test problems. The code is self-adaptive in the sense that grid point spacing is determined by user-specified constants denoting maximum and minimum grid spacings and constants relating the relative influence of smoothness and orthogonality. Estimates of truncation error, in terms of flow-field gradients and/or geometric features, are used to determine the point distribution. Points are redistributed along grid lines in a specified direction in an elliptic manner over a user-specified subdomain, while orthogonality and smoothness are controlled in a parabolic (marching) manner in the remaining directions. Multidirectional adaption is achieved by sequential application of the method in each coordinate direction. The flow-field solution is redistributed onto the newly distributed grid points after each unidirectional adaption by a simple one-dimensional interpolation scheme. For time-accurate schemes such interpolation is not necessary and time-dependent metrics are carried in the fluid dynamic equations to account for grid movement.
Recent technology developments and a systems engineering design approach have led to the development of a practical battery-free solar refrigerator as a spin-off of NASA's aerospace refrigeration research. Off-grid refrigeration is a good application of solar photovoltaic (PV) power if thermal storage is incorporated and a direct connection is made between the cooling system and the PV panel. This was accomplished by integrating water as a phase-change material into a well insulated refrigerator cabinet and by developing a microprocessor based control system that allows direct connection of a PV panel to a variable speed compressor. This second innovation also allowed peak power-point tracking from the PV panel and elimination of batteries from the system. First a laboratory unit was developed to prove the concept and then a commercial unit was produced and deployed in a field test. The laboratory unit was used to test many different configurations including thermoelectric, Stirling and vapor compression cooling systems. The final configuration used a vapor compression cooling cycle, vacuum insulation, a passive condenser, an integral evaporator/ thermal storage tank, two 77 watt PV panels and the novel controller mentioned above. The system's only moving part was the variable speed BD35 compressor made by Danfoss. The 365 liter cabinet stayed cold with as little as 274 watt-hours per day average PV power. Battery-free testing was conducted for several months with very good results. The amount of thermal storage, size of compressor and power of PV panels connected can all be adjusted to optimize the design for a given application and climate. In the commercial unit, the high cost of the vacuum insulated refrigerator cabinet and the stainless steel thermal storage tank were addressed in an effort to make the technology commercially viable. This unit started with a 142 liter, mass-produced chest freezer cabinet that had the evaporator integrated into its inner walls. Its compressor was replaced with a Danfoss DC compressor slightly larger than the one used in the laboratory unit. The control system was integrated onto a single electronics card and packaged with its starting capacitors. The water for thermal storage was placed behind a liner that was made to fit inside the original factory liner. The original condenser was also augmented with additional surface area to improve performance. PV panels with a total rated power of 180 watts were used. The unit was tested with very successful results in an outside ambient environment, demonstrating its potential for widespread use in many off-grid applications for solar refrigeration.
Self-adaptive mesh refinement dynamically matches the computational demands of a solver for partial differential equations to the activity in the application's domain. In this paper we present two C++ class libraries, P++ and AMR++, which significantly simplify the development of sophisticated adaptive mesh refinement codes on (massively) parallel distributed memory architectures. The development is based on our previous research in this area. The C++ class libraries provide abstractions to separate the issues of developing parallel adaptive mesh refinement applications into those of parallelism, abstracted by P++, and adaptive mesh refinement, abstracted by AMR++. P++ is a parallel array class library to permit efficient development of architecture independent codes for structured grid applications, and AMR++ provides support for self-adaptive mesh refinement on block-structured grids of rectangular non-overlapping blocks. Using these libraries, the application programmers' work is greatly simplified to primarily specifying the serial single grid application and obtaining the parallel and self-adaptive mesh refinement code with minimal effort. Initial results for simple singular perturbation problems solved by self-adaptive multilevel techniques (FAC, AFAC), being implemented on the basis of prototypes of the P++/AMR++ environment, are presented. Singular perturbation problems frequently arise in large applications, e.g. in the area of computational fluid dynamics. They usually have solutions with layers which require adaptive mesh refinement and fast basic solvers in order to be resolved efficiently.
GRIDGEN is a government domain software package for interactive generation of multiple block grids around general configurations. Though it has been freely available since 1989, it has not been widely embraced by the internal flow community due to a misconception that it was designed for external flow use only. In reality GRIDGEN has always worked for internal flow applications, and GRIDGEN ongoing enhancements are increasing the quality of and efficiency with which grids for external and internal flow problems may be constructed. The software consists of four codes used to perform the four steps of the grid generation process. GRIDBLOCK is first used to decompose the flow domain into a collection of component blocks and then to establish interblock connections and flow solver boundary conditions. GRIDGEN2D is then used to generate surface grids on the outer shell of each component block. GRIDGEN3D generates grid points on the interior of each block, and finally GRIDVUE3D is used to inspect the resulting multiple block grid. Three of these codes (GRIDBLOCK, GRIDGEN2D, and GRIDVUE3D) are highly interactive and graphical in nature, and currently run on Silicon Graphics, Inc., and IBM RS/6000 workstations. The lone batch code (GRIDGEN3D) may be run on any of several Unix based platforms. Surface grid generation in GRIDGEN2D is being improved with the addition of higher order surface definitions (NURBS and parametric surfaces input in IGES format and bicubic surfaces input in PATRAN Neutral File format) and double precision mathematics. In addition, two types of automation have been added to GRIDGEN2D that reduce the learning curve slope for new users and eliminate work for experienced users. Volume grid generation using GRIDGEN3D has been improved via the addition of an advanced hybrid control function formulation that provides both orthogonality and clustering control at the block faces and clustering control on the block interior.