2015 NEPP Tasks Update for Ceramic and Tantalum Capacitors
This presentation provides a NASA Electronic Parts and Packaging (NEPP) program update on tantalum and ceramic capacitors.
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This presentation provides a NASA Electronic Parts and Packaging (NEPP) program update on tantalum and ceramic capacitors.
The DOE-supported project objectives are to: establish a national wind energy center (NWEC) at University of Houston and conduct research to address critical science and engineering issues for the development of future large MW-scale wind energy production systems, especially offshore wind turbines. The goals of the project are to: (1) establish a sound scientific/technical knowledge base of solutions to critical science and engineering issues for developing future MW-scale large wind energy production systems, (2) develop a state-of-the-art wind rotor blade research facility at the University of Houston, and (3) through multi-disciplinary research, introducing technology innovations on advanced wind-turbine materials, processing/manufacturing technology, design and simulation, testing and reliability assessment methods related to future wind turbine systems for cost-effective production of offshore wind energy. To achieve the goals of the project, the following technical tasks were planned and executed during the period from April 15, 2010 to October 31, 2014 at the University of Houston: (1) Basic research on large offshore wind turbine systems (2) Applied research on innovative wind turbine rotors for large offshore wind energy systems (3) Integration of offshore wind-turbine design, advanced materials and manufacturing technologies (4) Integrity and reliability of large offshore wind turbine blades and scaled model testing (5) Education and training of graduate and undergraduate students and post- doctoral researchers (6) Development of a national offshore wind turbine blade research facility The research program addresses both basic science and engineering of current and future large wind turbine systems, especially offshore wind turbines, for MW-scale power generation. The results of the research advance current understanding of many important scientific issues and provide technical information for solving future large wind turbines with advanced design, composite materials, integrated manufacturing, and structural reliability and integrity. The educational program have trained many graduate and undergraduate students and post-doctoral level researchers to learn critical science and engineering of wind energy production systems through graduate-level courses and research, and participating in various projects in center’s large multi-disciplinary research. These students and researchers are now employed by the wind industry, national labs and universities to support the US and international wind energy industry. The national offshore wind turbine blade research facility developed in the project has been used to support the technical and training tasks planned in the program to accomplish their goals, and it is a national asset which is available for used by domestic and international researchers in the wind energy arena.
Over the life of the Extravehicular Mobility Unit (EMU), numerous products detailing “how to build Extravehicular Activity (EVA) System hardware”, “how to interface with EVA System hardware” and “how to design hardware EVA will access and utilize” were generated to provide interoperability between a suited crewmember and the specified vehicle’s EVA task. Since the inception of these products, some have continued to receive updates due to the necessity of an on-going program while others remained unchanged for years and have led to discrepancies between the current accepted values and those considered outdated. For EVA-suited crewmember tasks beyond Low Earth Orbit (LEO), new vehicles need a single consolidated location for the best practices and lessons learned from the EVA Community. This paper outlines what common EVA compatibility design requirements are expected of an Exploration spacecraft that has interactions between the vehicle and an EVA suited crewmember for and an approach for standardizing EVA compatibility across various vehicles at various destinations. The approach of standardization allows for flexibility by tailoring the applicability to meet the EVA tasks required for that vehicle’s operation beyond Low Earth Orbit. This paper will also describe the broad difference between microgravity and partial gravity EVA compatibility and how those requirements were identified and will be informed.
This technology investigation was conducted to evaluate the feasibility of a number of thermal protection systems (TPS) concepts which are alternate candidates to the space shuttle baseline TPS. Four independent tasks were performed. Task 1 consisted of an in-depth evaluation of active structural cooling of the space shuttle orbiter. In Task 2, heat sink concepts for the booster were studied to identify and postulate solutions for design problems unique to heat sink TPS. Task 3 consisted of a feasibility demonstration test of a phase change material (PCM) incorporated into a reusable surface insulation (RSI) thermal protection system for the shuttle orbiter. In Task 4 the feasibility of heat pipes for stagnation region cooling was studied for the booster and the orbiter. Designs were developed for the orbiter leading edge and used in trade studies of leading edge concepts. At the time this program was initiated, a 2-stage fully reusable shuttle system was envisioned; therefore, the majority of the tasks were focused on the fully reusable system environments. Subsequently, a number of alternate shuttle system approaches, with potential for reduced shuttle system development funding requirements, were proposed. Where practicable, appropriate shifts in emphasis and task scoping were made to reflect these changes.
Coupled-cluster methods provide highly accurate models of molecular structure through explicit numerical calculation of tensors representing the correlation between electrons. These calculations are dominated by a sequence of tensor contractions, motivating the development of numerical libraries for such operations. While based on matrix–matrix multiplication, these libraries are specialized to exploit symmetries in the molecular structure and in electronic interactions, and thus reduce the size of the tensor representation and the complexity of contractions. The resulting algorithms are irregular and their parallelization has been previously achieved via the use of dynamic scheduling or specialized data decompositions. We introduce our efforts to extend the Libtensor framework to work in the distributed memory environment in a scalable and energy-efficient manner. We achieve up to 240× speedup compared with the optimized shared memory implementation of Libtensor. We attain scalability to hundreds of thousands of compute cores on three distributed-memory architectures (Cray XC30 and XC40, and IBM Blue Gene/Q), and on a heterogeneous GPU-CPU system (Cray XK7). As the bottlenecks shift from being compute-bound DGEMM's to communication-bound collectives as the size of the molecular system scales, we adopt two radically different parallelization approaches for handling load-imbalance, tasking and bulk synchronous models. Nevertheless, we preserve a unified interface to both programming models to maintain the productivity of computational quantum chemists.
When I began my internship with the Granular Mechanics and Regolith Operations laboratory (GMRO), also known as Swamp Works, I was given the unique opportunity to shadow many teams working on various projects, and decide what projects I wanted to take part in. Before I go into details of my experiences at Swamp Works, I would like to take a moment to explain what I discovered Swamp Works to be. Swamp Works is a family of hardworking, dedicated, and driven people from various backgrounds and skill sets. These people all work to advance technologies and make science fiction science fact through means of rapid prototyping. They support and encourage failure as an option when learning new things, as long as lesson learned from said failure. In fact, their motto states "Fail, Fast, Forward." What this means is, not if but when one fails he or she must do so quickly and spring forward from the failure so that his or her progress is not delayed. With this acceptance, it provided me the confidence to dive into a multitude of projects working in various fields and with a wide range of skill sets. The first project I joined was Badger. My motivation for taking on this project was the opportunity I would have to obtain valuable experience working with 3D modeling and 3D printing technologies. Badger was a digging apparatus to be used in a highly dusty environment in a material known as Regolith. Regolith is a scientific term for the dirt or top soil found on planetary bodies. Regolith contains a large quantity of sediments less than lOppm and as a result poses a challenge of keeping it out of any cracks and crevices. Furthermore, regolith can create high levels of electrostatic energy, which can prove damaging to sensitive electrical hardware. With these characteristics in mind, I decided to take on the task of designing and manufacturing a dust proof cover for the sensitive electrical hardware. When I began this project, I did not have the slightest idea as to how to use 3D modeling software or a means of manufacturing a viable product. As I went along with variants of the design, I became very proficient with a 3D modeling program known as CREO 2.0. Upon completion of my 3D design, I then had the task of manufacturing and having, in my hands, a usable model. To do this I had to work with additive printing technologies also known as 3D printing. Through my experiences working with Badger, I realized that 3D modeling is the focal point in much of engineering. With this in mind, I have embraced this fact and decided to further my experience with this software so that I may become a more valuable asset to any firm later in my career. Mid-way through work with Badger, I picked up another project in which I found much interest. I ha~ the opportunity to work side by side with a materials and composites guru in manufacturing carbon composite coupons (test strips) for performing stress, strain, and sheer analysis on. Being from a surfing, kiteboarding, and other water sport background I have always been interested in board design. With this in mind, it is no wonder why I found interest in such a project. I had the opportunity to refine Mold preparatory, composite layup, and composite curing techniques. Following manufacturing of these composite strips, I then performed various stress tests and logged my results. With these results, future teams could create lighter, stronger, and more cost effective composite structures for use in varieties of applications. After my experiences with materials and composites testing, I have obtained crucial appreciation for detailed documentation and analysis that material sciences involve. However, as interesting as composite materials testing has been, I do not feel this is where my future career lies. Another, more on the side, project I have been involved in is building a 626 cubic foot regolith containment chamber for doing full scale testing of robotic systems. This chamber is built of high strength aluminum scaffold materials, 80/20, and massive panels of Lexan. Once the chamber is completed, it is be filled with 120 tons of regolith and dubbed the largest regolith test chamber in the world. Through my experiences with building "Big Bin" as we called it, I discovered my demand for engaging and hands on activities. Through all of my incredible experiences working with the Swamp Works at Kennedy Space Center; I have obtained crucial knowledge, insights, and experiences that have fuelled, shaped, and will continue to drive me toward my ultimate goal of obtaining not only a degree in Engineering, but obtaining a job that I can call a career. I want to give much thanks to all of those who mentored me along my journey, and to all who made this opportunity a reality.
This Technical Memorandum provides a summary of current work accomplished under Technical Task Agreement (TTA) by the Marshall Space Flight Center (MSFC) regarding the International Space Station (ISS) Environmental Control and Life Support System (ECLSS). Current activities include ECLSS component design and development, computer model development, subsystem/integrated system testing, life testing, and general test support provided to the ISS program. Under ECLSS design, MSFC was responsible for the six major ECLSS functions, specifications and standard, component design and development, and was the architectural control agent for the ISS ECLSS. MSFC was responsible for ECLSS analytical model development. In-house subsystem and system level analysis and testing were conducted in support of the design process, including testing air revitalization, water reclamation and management hardware, and certain nonregenerative systems. The activities described herein were approved in task agreements between MSFC and NASA Headquarters Space Station Program Management Office and their prime contractor for the ISS, Boeing. These MSFC activities are in line to the designing, development, testing, and flight of ECLSS equipment planned by Boeing. MSFC's unique capabilities for performing integrated systems testing and analyses, and its ability to perform some tasks cheaper and faster to support ISS program needs, are the basis for the TTA activities.
Domestic production of high specific activity 60 Co was halted after a target rupture in 2012 at the Advanced Test Reactor (ATR). The Isotope Program (IP) within the US Department of Energy (DOE) Office of Science tasked a multilaboratory team of researchers and managers from Oak Ridge and Idaho National Laboratories with the redesign the radioisotope capsule. The objective of this effort was to create a more robust and reliable design, compared to the pre-2012 target. The team successfully completed this task to produce the DOE-IP cobalt (Co) production capsule design. Furthermore, 66 capsules were successfully fabricated by Oak Ridge National Laboratory (ORNL) and delivered to Idaho National Laboratory (INL) for irradiation in the ATR between January 2014 and October 2016. This paper describes the efforts of the team to prepare and disposition the two initial DOE-IP Co production capsules that were processed in March 2020. These efforts include performing accurate production predictions, experimentally validating predictions with assay measurements, shipping with the Orano-furnished Battelle Energy Alliance Research Reactor shipping package, and disassembling capsules at the isotope vendor site.
In situ processing aims to alleviate the growing gap between computation and I/O capabilities by performing data processing close to the data source. In situ processing is widely used to process data generated by multiple data sources, including observation data from edge devices or scientific observational facilities and the simulation data generated by scientific computation on a high-performance computing (HPC) platform. For a scientific workflow that is run on an HPC platform and composed of a simulation program and an in situ data analytics or visualization (abbreviated as ana/vis) task, there is an implicit assumption that the computing resources assigned to the workflow keep static during the workflow execution. However, with the converging trend between the HPC and cloud computing platform, running the in situ ana/vis task in an elastic way is promising to decrease its overhead and improve its resource utilization rate. Resource elasticity represents the ability to change resource configurations such as the number of computing nodes/processes during workflow execution. An elastic job may dynamically adjust resource configurations; it may use a few resources at the beginning and more resources toward the end of the job when interesting data appear. However, it is hard to predict a priori how many computing nodes/processes need to be added/removed during the workflow execution to adapt to changing workflow needs. How to efficiently guide elasticity operations, such as growing or shrinking the number of processes used for in situ analysis during workflow execution, is an open-ended research question. In this article, we present adaptive elasticity policies that adopt workflow runtime information collected during workflow execution to predict how to trigger the addition/removal of processes in order to minimize in situ processing overhead. Taking in situ visualization tasks as an example, we integrate the presented elasticity policies into a staging-based elastic workflow and evaluate its efficiency in multiple elasticity scenarios. Compared with the situation without elasticity or with a static elasticity policy that uses a fixed number of processes for each rescaling operation, the adaptive elasticity policy can save overhead in finding a proper resource configuration and improve resource utilization efficiency. Furthermore, one experiment illustrates that the adaptive elasticity policy saves 41% of core-hours compared with the situation without the resource elasticity.
The so-called Internet of Things concept has captured much attention recently as ordinary devices are connected to the Internet for monitoring and control purposes. One enabling technology is the proliferation of low-cost, single board computers with built-in network interfaces. Some of these are capable of hosting full-fledged operating systems that provide rich programming environments. Taken together, these features enable inexpensive solutions for even traditional tasks such as the one presented here for electrical power monitoring and outage reporting.
Large-scale parallel applications with complex global data dependencies beyond those of reductions pose significant scalability challenges in an asynchronous runtime system. Internodal challenges include identifying the all-to-all communication of data dependencies among the nodes. Intranodal challenges include gathering together these data dependencies into usable data objects while avoiding data duplication. This paper addresses these challenges within the context of a large-scale, industrial coal boiler simulation using the Uintah asynchronous many-task runtime system on GPU architectures. We show significant reduction in time spent analyzing data dependencies through refinements in our dependency search algorithm. Multiple task graphs are used to eliminate subsequent analysis when task graphs change in predictable and repeatable ways. Using a combined data store and task scheduler redesign reduces data dependency duplication ensuring that problems fit within host and GPU memory. Furthermore, these modifications did not require any changes to application code or sweeping changes to the Uintah runtime system. We report results running on the DOE Titan system on 119K CPU cores and 7.5K GPUs simultaneously. Our solutions can be generalized to other task dependency problems with global dependencies among thousands of nodes which must be processed efficiently at large scale.
Code optimization is an intricate task that is getting more complex as computing systems evolve. Managing the program optimization process, including the implementation and evaluation of code variants, is tedious, inefficient, and errors are likely to be introduced in the process. Moreover, because each platform typically requires a different sequence of transformations to fully harness its computing power, the optimization process complexity grows as new platforms are adopted. To address these issues, systems and frameworks have been proposed to automate the code optimization process. They, however, have not been widely adopted and are primarily used by experts with deep knowledge about underlying architecture and compiler intricacies. This article describes the requirements that we believe necessary for making automatic performance tuning more broadly used, especially in complex, long-lived high-performance computing applications. Besides discussing limitations of current systems and strategies to overcome these, we describe the design of a system that is able to semi-automatically generate efficient platform-specific code. In the proposed system, the code optimization is programmer-guided, separately from application code, on an external file in what we call optimization programming. The language to program the optimization process is able to represent complex collections of transformations and, as a result, generate efficient platform-specific code. A database manages different optimized versions of code regions, providing a pragmatic approach to performance portability, and the framework itself has separate components, allowing the optimized code to be used on systems without installing all of the modules required for the code generation. We present experiments on two different platforms to illustrate the generation of efficient platform-specific code that performs comparable to hand-optimized, vendor-provided code.
The Exascale Computing Project (ECP) Co-design Center for Particle Applications (CoPA) is addressing the challenges for particle applications to run on upcoming exascale computing architectures. This includes short- and long-range molecular dynamics (MD), particle-in-cell (PIC), and quantum molecular dynamics (QMD). This document addresses $\mathcal{O}(N)$ QMD. The goal of this CoPA team is to develop $\mathcal{O}(N)$ linear scaling methods for QMD optimized for new and next generation architectures. This will provide the capability to simulate larger systems and run for longer timeframes than is possible today. Focus is initially on the density matrix construction. This requires efficient matrix formats and linear algebra operations for distributed architectures. A significant reduction in the wallclock time for an MD timestep is necessary to achieve practical large scale QMD. Equally challenging is to develop scalable distributed implementations. This requires the exploration of efficient data formats (dense, sparse, etc.), data decomposition and distribution across compute nodes using block- and graph-based methods. Traditional programming models such as MPI/OpenMP, hybrid MPI/OpenMP/Accelerator, as well as asynchronous task-based models will be explored to achieve maximum parallelism. Parallelism at the level of a matrix operation, solver, and/or application needs to be explored to gain the most benefit on new and emerging architectures. This report serves as a “living document” of the additions and enhancements throughout the ECP CoPA project for $\mathcal{O}(N)$ QMD. The following sections address the applications we are working with, the quantum chemistry libraries (BML and PROGRESS), and our co-design exploration through the use of a proxy application.
Under the CTAP Statement of Work, Sandia was tasked with providing technical assistance to Dine College to create a testing program to determine hazardous contaminant levels in donated hand sanitizer. Sandia will loan instrumentation, provide a procedure, and act as technical advisor. The challenge for on-site testing lies in a balance of testing capability/speed, complexity, and cost of operations. Instruments that allow fastest and least expensive operation will be validated for performance for this sample problem (hand sanitizer w/ poisonous methanol or 1-propanol). The objective of this project is to enable Dine College personnel to perform on-site testing.
To assist both the advanced reactor industry and U.S. Nuclear Regulatory Commission (NRC) in the pursuit of reactor design and licensing, the U.S. Department of Energy (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program has established a mechanistic source term (MST) research project under the Multiphysics Applications technical area. As part of this effort, an MST mod/sim development pathway was developed in FY21 under the NEAMS program, which outlines the high-level objectives and near-term tasks necessary to achieve the project objectives. One such recommended task was the assessment of a previously developed thermodynamic database to model radionuclide vaporization from liquid sodium pools (specifically in the context of MST analyses), which is the focus of this topic report. As such, a thermodynamic database was created in FactSage for liquid sodium pools containing oxygen and relevant elements which represent radionuclides pertinent to MST analyses. The database was demonstrated in calculating vapor fraction curves for each element in the system at concentrations relevant to SFR MST.
This presentation represents a review of the background research conducted by NETL to apply artificial intelligence, i.e. auto-recursive algorithms and data analytics to detect leaks in utility scale boilers and laboratory power systems. The new project being funded by the Advanced Sensors and Controls Program is part of the Field Work Proposal funded in EY21 as Task 53 to demonstrate the application of these techniques on a utility scale power system.
The Earth Resources Laboratory Data Analysis System provides a valuable research tool in the evaluation of multispectral, radiometric, photographic, and passive microwave imagery data. The system has been in operational use for several months and has performed quite well. Emphasis on versatility of both the hardware and software design facilitates system expansion to many specialized data analysis tasks. The many independent software handlers provide building blocks for major processing programs.
Comprehensive safety program requirements are defined and a methodology for implementing the defined safety tasks in support of the design, development, manufacturing, testing and flight phases of the ultraviolet spectrometer experiment is presented.