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At least 217 records · Page 12

Novel Module Architecture for Lower CapEx and Improved Recyclability for c-Si PV Modules

Photovoltaic (PV) energy production is currently increasing at a rate at which recycling is becoming necessary. A novel module architecture has been demonstrated that has potential for high value recycling for c-Si PV. This architecture eliminates the vacuum lamination process and cross-linked en capsulants. Functioning prototypes of c-Si have been fabricated for stress testing in collaboration with NREL. These modules are being tested against traditionally manufactured modules. Based on preliminary results, this module architecture is a potentially viable solution for improving the manufacturing cost and recyclability of PV modules while retaining module performance.

computer architecture↗

Elastic Resource Management for Deep Learning Applications in a Container Cluster

The increasing demand for learning from massive datasets is restructuring our economy. Effective learning, however, involves nontrivial computing resources. Most businesses utilize commercial infrastructure providers (e.g., AWS) to host their computing clusters in the cloud, where various jobs compete for available resources. While cloud resource management is a fruitful research field that has made many advances in production, such as Kubernetes and YARN, few efforts have been invested to further optimize the system performance, especially for deep learning (DL) training jobs in a container cluster. This work introduces FlowCon, a system that is able to monitor the individual evaluation functions of DL jobs at runtime, and thus to make placement decisions on resource allocations elastically. Here, we present a detailed design and implementation of FlowCon and conduct intensive experiments over various DL models. The results demonstrate that FlowCon significantly improves DL job completion time and resource utilization efficiency, compared to default systems. According to the results, FlowCon is able to improve the completion time by up to 68.8% and meanwhile, reduce the makespan by 18.0%, in the presence of various DL job workloads.

97 MATHEMATICS AND COMPUTING↗

InversionNet3D: Efficient and Scalable Learning for 3-D Full-Waveform Inversion

Seismic full-waveform inversion (FWI) techniques aim to find a high-resolution subsurface geophysical model provided with waveform data. Some recent effort in data-driven FWI has shown some encouraging results in obtaining 2-D velocity maps. However, due to high computational complexity and large memory consumption, the reconstruction of 3-D high-resolution velocity maps via deep networks is still a great challenge. Here, in this article, we present InversionNet3D (InvNet3D), an efficient and scalable encoder–decoder network for 3-D FWI. The proposed method employs group convolution in the encoder to establish an effective hierarchy for learning information from multiple sources while cutting down unnecessary parameters and operations at the same time. The introduction of invertible layers further reduces the memory consumption of intermediate features during training and, thus, enables the development of deeper networks with more layers and higher capacity as required by different application scenarios. Experiments on the 3-D Kimberlina dataset demonstrate that InvNet3D achieves state-of-the-art reconstruction performance with lower computational cost and lower memory footprint compared to the baseline.

58 GEOSCIENCES↗

Dynamic Adaptable Asynchronous Progress Model for MPI RMA Multiphase Applications

Casper is a process-based asynchronous progress model for MPI one-sided communication on multi-and many-core architectures. The one-sided communication is not truly one-sided in most MPI implementations: the target process still relies on software progress to complete incoming operations. Casper allows the user to specify an arbitrary number of cores dedicated to background ghost processes and transparently redirects the RMA operations to ghost processes by utilizing the PMPI redirection and MPI-3 shared-memory technologies. Although Casper benefits applications that suffer from lack of asynchronous progress, the operation redirection design might not support complex multiphase applications effectively, which often involve dynamically changing communication density and computing workloads. In this paper, we present an adaptive mechanism in Casper to address the limitation of static asynchronous progress in multiphase applications. For this we exploit two adaptive strategies, a user-guided strategy and a fully transparent and automatic strategy based on self-profiling and prediction, to dynamically reconfigure the asynchronous progress in Casper according to real-time performance characteristics during multiphase execution. We evaluate the adaptive approaches in both microbenchmarks and a real quantum chemistry application suite, NWChem, on the Cray XC30 supercomputer and an Intel Omni-Path cluster.

97 MATHEMATICS AND COMPUTING↗

Enabling Scalable and Extensible Memory-mapped Datastores in Userspace

Exascale workloads are expected to incorporate data-intensive processing in close coordination with traditional physics simulations. These emerging scientific, data-analytics and machine learning applications need to access a wide variety of datastores in flat files and structured databases. Programmer productivity is greatly enhanced by mapping datastores into the application process's virtual memory space to provide a unified “in-memory” interface. Currently, memory mapping is provided by system software primarily designed for generality and reliability. However, scalability at high concurrency is a formidable challenge on exascale systems. Also, there is a need for extensibility to support new datastores potentially requiring HPC data transfer services. In this article, we present UMap , a scalable and extensible userspace service for memory-mapping datastores. Furthermore, through decoupled queue management, concurrency aware adaptation, and dynamic load balancing, UMap enables application performance to scale even at high concurrency. We evaluate UMap in data-intensive applications, including sorting, graph traversal, database operations, and metagenomic analytics. Our results show that UMap as a userspace service outperforms an optimized kernel-based service across a wide range of intra-node concurrency by 1.22-1.9 × . We performed two case studies to demonstrate UMap 's extensibility. First, a new datastore residing in remote memory is incorporated into UMap as an application-specific plugin. Second, we present a persistent memory allocator Metall built atop UMap for unified storage/memory.

97 MATHEMATICS AND COMPUTING↗

IRIS: A Performance-Portable Framework for Cross-Platform Heterogeneous Computing

From edge to exascale, computer architectures are becoming more heterogeneous and complex. The systems typically have fat nodes, with multicore CPUs and multiple hardware accelerators such as GPUs, FPGAs, and DSPs. This complexity is causing a crisis in programming systems and performance portability. Several programming systems are working to address these challenges, but the increasing architectural diversity is forcing software stacks and applications to be specialized for each architecture. As we show, all of these approaches critically depend on their software framework for discovery, execution, scheduling, and data orchestration. To address this challenge, we believe that a more agile and proactive software framework is essential to increase performance portability and improve user productivity. To this end, we have designed and implemented IRIS: a performance-portable framework for cross-platform heterogeneous computing. IRIS can discover available resources, manage multiple diverse programming platforms (e.g., CUDA, Hexagon, HIP, Level Zero, OpenCL, OpenMP) simultaneously in the same execution, respect data dependencies, orchestrate data movement proactively, and provide for user-configurable scheduling. To simplify data movement, IRIS introduces a shared virtual device memory with relaxed consistency among different heterogeneous devices. IRIS also adds an automatic kernel workload partitioning technique using the polyhedral model so that it can resize kernels for a wide range of devices. Our evaluation on three architectures, ranging from Qualcomm Snapdragon to a Summit supercomputer node, shows that IRIS improves portability across a wide range of diverse heterogeneous architectures with negligible overhead.

97 MATHEMATICS AND COMPUTING↗

Preserving Command Line Workflow for a Package Management System using ASCII DAG Visualization

Package managers provide ease of access to applications by removing the time-consuming and sometimes completely prohibitive barrier of successfully building, installing, and maintaining the software for a system. A package dependency contains dependencies between all packages required to build and run the target software. Package management system developers, package maintainers, and users may consult the dependency graph when a simple listing is insufficient for their analyses. However, users working in a remote command line environment must disrupt their workflow to visualize dependency graphs in graphical programs, possibly needing to move files between devices or incur forwarding lag. Such is the case for users of Spack, an open source package management system originally developed to ease the complex builds required by supercomputing environments. To preserve the command line workflow of Spack, we develop an interactive ASCII visualization for its dependency graphs. Through interviews with Spack maintainers, we identify user goals and corresponding visual tasks for dependency graphs. We evaluate the use of our visualization through a command line-centered study, comparing it to the system's two existing approaches. We observe that despite the limitations of the ASCII representation, our visualization is preferred by participants when approached from a command line interface workflow.

97 MATHEMATICS AND COMPUTING↗

CMed: Crowd Analytics for Medical Imaging Data

In this work, we present a visual analytics framework, CMed, for exploring medical image data annotations acquired from crowdsourcing. CMed can be used to visualize, classify, and filter crowdsourced clinical data based on a number of different metrics such as detection rate, logged events, and clustering of the annotations. CMed provides several interactive linked visualization components to analyze the crowd annotation results for a particular video and the associated workers. Additionally, all results of an individual worker can be inspected using multiple linked views in our CMed framework. We allow a crowdsourcing application analyst to observe patterns and gather insights into the crowdsourced medical data, helping him/her design future crowdsourcing applications for optimal output from the workers. We demonstrate the efficacy of our framework with two medical crowdsourcing studies: polyp detection in virtual colonoscopy videos and lung nodule detection in CT thin-slab maximum intensity projection videos. We also provide experts' feedback to show the effectiveness of our framework. Lastly, we share the lessons we learned from our framework with suggestions for integrating our framework into a clinical workflow.

97 MATHEMATICS AND COMPUTING↗

A User-Centered Design Study in Scientific Visualization Targeting Domain Experts

The development of usable visualization solutions is essential for ensuring both their adoption and effectiveness. User-centered design principles, which involve users throughout the entire development process, have been shown to be effective in numerous information visualization endeavors. We describe how we applied these principles in scientific visualization over a two year collaboration to develop a hybrid in situ/post hoc solution tailored towards combustion researcher needs. Lastly, we examine the importance of user-centered design and lessons learned over the design process in an effort to aid others seeking to develop effective scientific visualization solutions.

97 MATHEMATICS AND COMPUTING↗

Guidelines for Home Energy Professionals Project: Multifamily Job Task Analyses Needs Assessment

This report describes the efforts carried out to determine whether there is a need to develop separate, multifamily-specific JTAs for the four proposed job categories. The multifamily SWS market committee considered these job designations to be the best candidates for developing JTAs and certification blueprints, as well as having the greatest potential for promoting job growth in the multifamily home performance industry.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Global Threat Reduction Initiative Fuel Thermo-Physical Characterization Project: Sample Management Plan

This sample management plan provides guidelines for sectioning, preparation, acceptance criteria, analytical path, and end-of-life disposal for the fuel element segments utilized in the Global Threat Reduction Initiative (GTRI), Fuel Thermo-Physical Characterization Project. The Fuel Thermo-Physical Characterization Project is tasked with analysis of irradiated Low Enriched Uranium (LEU) Molybdenum (U-Mo) fuel element samples to support the GTRI conversion program. Sample analysis may include optical microscopy (OM), scanning electron microscopy (SEM) fuel-surface interface analysis, gas pycnometry (density) measurements, laser flash analysis (LFA), differential scanning calorimetry (DSC), thermogravimetry and differential thermal analysis with mass spectroscopy (TG /DTA-MS), Inductively Coupled Plasma Spectrophotometry (ICP), alpha spectroscopy, and Thermal Ionization Mass Spectroscopy (TIMS). The project will utilize existing Radiochemical Processing Laboratory (RPL) operating, technical, and administrative procedures for sample receipt, processing, and analyses. Test instructions (TIs), which are documents used to provide specific details regarding the implementation of an existing RPL approved technical or operational procedure, will also be used to communicate to staff project specific parameters requested by the Principal Investigator (PI). TIs will be developed, reviewed, and issued in accordance with the latest revision of the RPL-PLN-700, RPL Operations Plan. Additionally, the PI must approve all project test instructions and red-line changes to test instructions.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE-RCT-0003641 Final Technical Report

This program studied novel concepts for an Axial Flux Reluctance Machine to capture energy from marine hydrokinetic sources and compared their attributes to a Radial Flux Reluctance Machine which was designed under a prior Department of Energy program for the same application. Detailed electromagnetic and mechanical analyses were performed to determine the validity of the concept and to provide a direct comparison with the existing conventional Radial Flux Switched Reluctance Machine designed during the Advanced Wave Energy Conversion Project, DE-EE0003641. The alternate design changed the machine topology so that the flux that is switched flows axially rather than radially and the poles themselves are long radially, as opposed to the radial flux machine that has pole pieces that are long axially. It appeared possible to build an axial flux machine that should be considerably more compact than the radial machine. In an “apples to apples” comparison, the same rules with regard to generating magnetic force and the fundamental limitations of flux density hold, so that at the heart of the machine the same torque equations hold. The differences are in the mechanical configuration that limits or enhances the change of permeance with rotor position, in the amount of permeable iron required to channel the flux via the pole pieces to the air-gaps, and in the sizing and complexity of the electrical winding. Accordingly it was anticipated that the magnetic component weight would be similar but that better use of space would result in a shorter machine with accompanying reduction in housing and support structure. For the comparison the pole count was kept the same at 28 though it was also expected that the radial tapering of the slots between pole pieces would permit a higher pole count machine, enabling the generation of greater power at a given speed in some future design. The baseline Radial Flux Machine design was established during the previous DOE program. Its characteristics were tabulated for use in comparing to the Axial Flux Machine. Three basic conceptual designs for the Axial Flux Machine were considered: (1) a machine with a single coil at the inner diameter of the machine, (2) a machine with a single coil at the outside diameter of the machine, and (3) a machine with a coil around each tooth. Slight variations of these basic configurations were considered during the study. Analysis was performed on these configurations to determine the best candidate design to advance to preliminary design, based on size, weight, performance, cost and manufacturability. The configuration selected as the most promising was the multi-pole machine with a coil around each tooth. This configuration provided the least complexity with respect to the mechanical configuration and manufacturing, which would yield the highest reliability and lowest cost machine of the three options. A preliminary design was performed on this selected configuration. For this first ever axial design of the multi rotor configuration the 'apples to apples' comparison was based on using the same length of rotor pole as the axial length of rotor pole in the radial machine and making the mean radius of the rotor in the axial machine the same as the air gap radius in the radial machine. The tooth to slot ratio at the mean radius of the axial machine was the same as the tooth to slot ratio of the radial machine. The comparison between the original radial flux machine and the new axial flux machine indicates that for the same torque, the axial flux machine diameter will be 27% greater, but it will have 30% of the length, and 76% of the weight. Based on these results, it is concluded that an axial flux reluctance machine presents a viable option for large generators to be used for the capture of wave energy. In the analysis of Task 4, below, it is pointed out that our selection of dimensional similarity for the 'apples to apples' comparison did not produce an optimum axial flux design. There is torque capability to spare, implying we could reduce the magnetic structure, but the winding area, constrained by the pole separation at the inner pole radius has a higher resistance than desirable, implying we need more room for copper. The recommendation is to proceed via one cycle of optimization and review to correct this unbalance and then proceed to a detailed design phase to produce manufacturing drawings, followed by the construction of a prototype to test the performance of the machine against predicted results.

16 TIDAL AND WAVE POWER↗

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Report for Task 10: Controllability and Observability Analysis (Deliverable D7))

It is common to have less than full observability for distribution systems, as the number of available measurements are not sufficient. Considering increasing penetration of distributed energy resources (DERs), it is imperative to understand and control distribution systems better. Developed for the transmission system, the original numerical observability analysis methods were based on the canonical DC Power Flow (DC-PF) model. However, the DC-PF model is ill-suited for the distribution system in which line resistance to reactance (R/X) ratios can be near unity. In this report, we apply the non-iterative Observability Test (OT) and Observable Island Identification Procedure (OIIP) in to the gain matrix from the distribution system state estimator. Because sensors are few in distribution systems, pseudo-measurements based on historical load profiles and zero-injection virtual measurements are often employed to ensure observability. However, both the observability and the accuracy of the state estimates are uncertain when historical data is limited/unavailable.

42 ENGINEERING↗

Exxon Mobil-NETL Testing of DAC Materials

This joint initiative is aimed at extending our understanding of real DAC testing conditions at the NETL DAC testbed facility. Of particular focus will be: • Small Scale testing of powdered and formulated materials (supplied by ExxonMobil) to evaluate various performance metrics under DAC process cycles • Pilot scale testing of formulated materials at larger scales ExxonMobil will work with NETL to shake down equipment, validate testing methods, and define best practices for data analysis. Three tasks are proposed: 1. Validation of multi-cycle test data on powdered and formulated materials to benchmark various performance metrics of these materials. 2. Steam regeneration of powdered samples at small scale to define baseline performance under commercially relevant conditions. 3. Pilot scale testing of larger formulated materials to test commercially relevant samples under actual process cycles.

36 MATERIALS SCIENCE↗

PROVIDING PLANT DATA ANALYTICS THROUGH A SEAMLESS DIGITAL ENVIRONMENT

As technology continues to evolve and become more integrated into a worker’s daily routine in the Nuclear Power industry the need for easy access to data becomes a priority. Not only does the need for data increase but the amount of data collected increases. In most cases the data is collected and stored in various software applications, many of which are legacy systems, which do not offer any other option to access the data except through the application’s user interface. Furthermore the data gets grouped in “silos” according to work function and not necessarily by subject. Hence, in order to access all the information needed for a particular task or analysis one may have to access multiple applications to gather all the data needed. The industry and the research community have identified the need for a digital architecture and more importantly the need for a Seamless Digital Environment. An SDE provides a means to access multiple applications, gather the data points needed, conduct the analysis requested, and present the result to the user with minimal or no effort by the user. In addition, the nuclear utilities have identified the need for research focused on data analytics. The effort should develop and evaluate use cases for data mining and analytics for employing information from plant sensors and database for use in developing improved business analytics. Idaho National Laboratory is leading such effort, which is conducted in close collaboration with vendors, nuclear utilities, Institute of Nuclear Power Operations, and Electric Power Research Institute. The goal of the study is to research potential approaches to building an analytics solution for equipment reliability, on a small scale, focusing on either a single piece of equipment or a single system. The analytics solution will likely consist of a data integration layer, predictive and machine learning layer and the user interface layer that will display the output of the analysis in a straight forward, easy to consume manner. This paper will describe the study and the initial results.

47 OTHER INSTRUMENTATION↗