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At least 253 records · Page 14

Load Balancing Sequences of Unstructured Adaptive Grids

Mesh adaption is a powerful tool for efficient unstructured grid computations but causes load imbalance on multiprocessor systems. To address this problem, we have developed PLUM, an automatic portable framework for performing adaptive large-scale numerical computations in a message-passing environment. This paper makes several important additions to our previous work. First, a new remapping cost model is presented and empirically validated on an SP2. Next, our load balancing strategy is applied to sequences of dynamically adapted unstructured grids. Results indicate that our framework is effective on many processors for both steady and unsteady problems with several levels of adaption. Additionally, we demonstrate that a coarse starting mesh produces high quality load balancing, at a fraction of the cost required for a fine initial mesh. Finally, we show that the data remapping overhead can be significantly reduced by applying our heuristic processor reassignment algorithm.

Biswas, Rupak↗

The controlled growth method - A tool for structural optimization

An adaptive design variable linking scheme in a NLP based optimization algorithm is proposed and evaluated for feasibility of application. The present scheme, based on an intuitive effectiveness measure for each variable, differs from existing methodology in that a single dominant variable controls the growth of all others in a prescribed optimization cycle. The proposed method is implemented for truss assemblies and a wing box structure for stress, displacement and frequency constraints. Substantial reduction in computational time, even more so for structures under multiple load conditions, coupled with a minimal accompanying loss in accuracy, vindicates the algorithm.

Hajela, P.↗

Community-Engaged Modeling of Urban Flood Adaptation Pathways

Climate change is intensifying the hydrologic cycle, leading to more frequent and severe rainfall-driven (pluvial) flooding in urban areas. In the mid-Atlantic US cities, aging and under-designed stormwater infrastructure is increasingly strained by these events, resulting in recurring damage to property and disruptions to transportation networks. In this study, we combine community engagement with hydrologic modeling to develop and evaluate potential urban flood adaptation strategies. Over a three-year period, local technical experts and community representatives met regularly to discuss flooding concerns, identify priorities, and co-develop adaptation strategies. These discussions informed the development of an urban flooding model (EPA Storm Water Management Model) for the Baltimore Harbor watershed, the focus location of this study. The flooding model integrates complex surface and subsurface stormwater infrastructure data, local expert knowledge, and community insights. We simulate stakeholder-prioritized adaptations, such as green and gray infrastructure strategies. Model results demonstrate that enhanced infrastructure maintenance is the most effective adaptation for reducing flood depths, but has varied effects across the watershed, and can increase flooding in some locations. Spatially concentrated greening provides limited benefit to the watershed as a whole, but moderate benefit in community priority areas. Together, these adaptations have the potential to reduce flood depths by as much as 58% in some locations, greatly reducing property damage and mobility impacts, primary concerns of stakeholders. Future work will implement robust optimization tools to search for adaptations which meet stakeholder objectives and perform highly under varied future climate conditions. This work contributes to the expanding literature on collaborative modeling and demonstrates that community-engaged approaches can enhance model credibility and generate more actionable insights for communities seeking to strengthen climate resilience.

Spangler, Ava [Pennsylvania State University] (ORC↗

Community-Informed Urban Flood Modeling for Impact Mitigation

Climate change is intensifying the hydrologic cycle, leading to more frequent and severe rainfall-driven (pluvial) flooding in urban areas. In the mid-Atlantic US cities, aging and under-designed stormwater infrastructure is increasingly strained by these events, resulting in recurring damage to property and disruptions to transportation networks. In this study, we combine community engagement with hydrologic modeling to develop and evaluate potential urban flood adaptation strategies. Over a three-year period, local technical experts and community representatives met regularly to discuss flooding concerns, identify priorities, and co-develop adaptation strategies. These discussions informed the development of an urban flooding model (EPA Storm Water Management Model) for the Baltimore Harbor watershed, the focus location of this study. The flooding model integrates complex surface and subsurface stormwater infrastructure data, local expert knowledge, and community insights. We simulate stakeholder-prioritized adaptations, such as green and gray infrastructure strategies. Model results demonstrate that enhanced infrastructure maintenance is the most effective adaptation for reducing flood depths, but has varied effects across the watershed, and can increase flooding in some locations. Spatially concentrated greening provides limited benefit to the watershed as a whole, but moderate benefit in community priority areas. Together, these adaptations have the potential to reduce flood depths by as much as 58% in some locations, greatly reducing property damage and mobility impacts, primary concerns of stakeholders. Future work will implement robust optimization tools to search for adaptations which meet stakeholder objectives and perform highly under varied future climate conditions. This work contributes to the expanding literature on collaborative modeling and demonstrates that community-engaged approaches can enhance model credibility and generate more actionable insights for communities seeking to strengthen climate resilience.

Baltimore MD↗

COSMOS 2044 Mission: Overview

The COSMOS 2044 spaceflight was the ninth Soviet-International joint mission dedicated to space biomedicine and the seventh in which the United States has participated. The unmanned Vostok vehicle carried 10 rats and two rhesus monkeys on its 14-day voyage. This spaceflight yielded an unprecedented bounty of data on physiological responses to the microgravity environment. The tissues studied and the numbers and types of studies performed by members of the international science community constituted a new record. Many of the results obtained by the approximately 80 American scientists who participated are reported in the series of COSMOS 2044 papers in this issue. Descriptions of the spaceflight and animal procedures are detailed elsewhere. The broad goals of the space biomedical program are threefold. The first is to characterize qualitatively and quantitatively the biological responses to the microgravity environment, be they adaptive or pathological. The second goal is to clarify the physiological-biochemical mechanisms mediating the responses to microgravity. The third goal of this program is to use the space environment as a tool to better understand adaptive and disease processes in terrestrial organisms.

Grindeland, R. E.↗

Integrating Oil Debris and Vibration Measurements for Intelligent Machine Health Monitoring

A diagnostic tool for detecting damage to gears was developed. Two different measurement technologies, oil debris analysis and vibration were integrated into a health monitoring system for detecting surface fatigue pitting damage on gears. This integrated system showed improved detection and decision-making capabilities as compared to using individual measurement technologies. This diagnostic tool was developed and evaluated experimentally by collecting vibration and oil debris data from fatigue tests performed in the NASA Glenn Spur Gear Fatigue Rig. An oil debris sensor and the two vibration algorithms were adapted as the diagnostic tools. An inductance type oil debris sensor was selected for the oil analysis measurement technology. Gear damage data for this type of sensor was limited to data collected in the NASA Glenn test rigs. For this reason, this analysis included development of a parameter for detecting gear pitting damage using this type of sensor. The vibration data was used to calculate two previously available gear vibration diagnostic algorithms. The two vibration algorithms were selected based on their maturity and published success in detecting damage to gears. Oil debris and vibration features were then developed using fuzzy logic analysis techniques, then input into a multi sensor data fusion process. Results show combining the vibration and oil debris measurement technologies improves the detection of pitting damage on spur gears. As a result of this research, this new diagnostic tool has significantly improved detection of gear damage in the NASA Glenn Spur Gear Fatigue Rigs. This research also resulted in several other findings that will improve the development of future health monitoring systems. Oil debris analysis was found to be more reliable than vibration analysis for detecting pitting fatigue failure of gears and is capable of indicating damage progression. Also, some vibration algorithms are as sensitive to operational effects as they are to damage. Another finding was that clear threshold limits must be established for diagnostic tools. Based on additional experimental data obtained from the NASA Glenn Spiral Bevel Gear Fatigue Rig, the methodology developed in this study can be successfully implemented on other geared systems.

Dempsey, Paula J.↗

Reinvention/reengineering of business and technical processes

The changing marketplace as evidenced by global competition is requiring American organizations to rethink, regroup, and redesign their processes. The umbrella of total quality management (TQM) includes many quality methods, techniques, tools, and approaches. There is no right way for every situation or circumstance. Adaptability and experimentation of several tools is necessary. Process management when properly applied can lead to continuous quality improvements. But some processes simply need to be discarded and new ones developed. This reengineering often results in vertical compression and job redesign and restructuring. Work activities must be designed around processes, not processes around work activities. Reengineering and process management do not stand alone--they support each other. Senior executive leadership and empowerment of workers at all organizational levels is vital for both short-term and long-term success.

Olsen, Eugene A.↗

Friction Stir Weld Application and Tooling Design for the Multi-purpose Crew Vehicle Stage Adapter

The Multi-Purpose Crew Vehicle (MPCV), commonly known as the Orion capsule, is planned to be the United States' next manned spacecraft for missions beyond low earth orbit. Following the cancellation of the Constellation program and creation of SLS (Space Launch System), the need arose for the MPCV to utilize the Delta IV Heavy rocket for a test launch scheduled for 2014 instead of the previously planned Ares I rocket. As a result, an adapter (MSA) must be used in conjunction with the MPCV to account for the variation in diameter of the launch vehicles; 5.5 meters down to 5.0 meters. Prior to ight article fabrication, a path nder (test article) will be fabricated to ne tune the associated manufacturing processes. The adapter will be comprised of an aluminum frustum (partial cone) that employs isogrid technology and circumferential rings on each end. The frustum will be fabricated by friction stir welding (FSW) three individual panels together on a Vertical Weld Tool (VWT) at NASA Marshall Space Flight Center. Subsequently, each circumferential ring will be friction stir welded to the frustum using a Robotic Weld Tool (RWT). The irregular geometry and large mass of the MSA require that extensive tooling preparation be put into support structures for the friction stir weld. The tooling on the VWT will be comprised of a set of conveyors mounted on pre-existing stanchions so that the MSA will have the ability to be rotated after each of the three friction stir welds. The tooling requirements to friction stir weld the rings with the RWT are somewhat more demanding. To support the mass of the MSA and resist the load of the weld tool, a system of mandrels will be mounted to stanchions and assembled in a circle. The goal of the paper will be to explain the design, fabrication, and assembly of the tooling, to explain the use of friction stir welding on the MSA path nder, and also to discuss the lessons learned and modi cations made in preparation for ight article fabrication in support of the 2014 launch of the Orion MPCV.

Alcorn, John↗

Load Balancing Unstructured Adaptive Grids for CFD Problems

Mesh adaption is a powerful tool for efficient unstructured-grid computations but causes load imbalance among processors on a parallel machine. A dynamic load balancing method is presented that balances the workload across all processors with a global view. After each parallel tetrahedral mesh adaption, the method first determines if the new mesh is sufficiently unbalanced to warrant a repartitioning. If so, the adapted mesh is repartitioned, with new partitions assigned to processors so that the redistribution cost is minimized. The new partitions are accepted only if the remapping cost is compensated by the improved load balance. Results indicate that this strategy is effective for large-scale scientific computations on distributed-memory multiprocessors.

Biswas, Rupak↗

MO-E-9A-01: Risk Based Quality Management: TG100 In Action

One of the goals of quality management in radiation therapy is to gain high confidence that patients will receive the prescribed treatment correctly. To accomplish these goals professional societies such as the American Association of Physicists in Medicine (AAPM) has published many quality assurance (QA), quality control (QC), and quality management (QM) guidance documents. In general, the recommendations provided in these documents have emphasized on performing device-specific QA at the expense of process flow and protection of the patient against catastrophic errors. Analyses of radiation therapy incidents find that they are most often caused by flaws in the overall therapy process, from initial consult through final treatment, than by isolated hardware or computer failures detectable by traditional physics QA. This challenge is shared by many intrinsically hazardous industries. Risk assessment tools and analysis techniques have been developed to define, identify, and eliminate known and/or potential failures, problems, or errors, from a system, process and/or service before they reach the customer. These include, but are not limited to, process mapping, failure modes and effects analysis (FMEA), fault tree analysis (FTA), and establishment of a quality management program that best avoids the faults and risks that have been identified in the overall process. These tools can be easily adapted to radiation therapy practices because of their simplicity and effectiveness to provide efficient ways to enhance the safety and quality of treatment processes. Task group 100 (TG100) of AAPM has developed a risk-based quality management program that uses these tools. This session will be devoted to a discussion of these tools and how these tools can be used in a given radiotherapy clinic to develop a risk based QM program. Learning Objectives: Learn how to design a process map for a radiotherapy process. Learn how to perform a FMEA analysis for a given process. Learn what Fault tree analysis is all about. Learn how to design a quality management program based upon the information obtained from process mapping, FMEA and FTA.

60 APPLIED LIFE SCIENCES↗

Percept User Manual.

This document is the main user guide for the Sierra/Percept capabilities including the mesh_adapt and mesh_transfer tools. Basic capabilities for uniform mesh refinement (UMR) and mesh transfers are discussed. Examples are used to provide illustration. Future versions of this manual will include more advanced features such as geometry and mesh smoothing. Additionally, all the options for the mesh_adapt code will be described in detail. Capabilities for local adaptivity in the context of offline adaptivity will also be included. This page intentionally left blank.

97 MATHEMATICS AND COMPUTING↗

Percept User Manual

This document is the main user guide for the Sierra/Percept capabilities including the mesh_adapt and mesh_transfer tools. Basic capabilities for uniform mesh refinement (UMR) and mesh transfers are discussed. Examples are used to provide illustration. Future versions of this manual will include more advanced features such as geometry and mesh smoothing. Additionally, all the options for the mesh_adapt code will be described in detail. Capabilities for local adaptivity in the context of offline adaptivity will also be included.

42 ENGINEERING↗

PLUM: Parallel Load Balancing for Adaptive Unstructured Meshes

Mesh adaption is a powerful tool for efficient unstructured-grid computations but causes load imbalance among processors on a parallel machine. We present a novel method called PLUM to dynamically balance the processor workloads with a global view. This paper presents the implementation and integration of all major components within our dynamic load balancing strategy for adaptive grid calculations. Mesh adaption, repartitioning, processor assignment, and remapping are critical components of the framework that must be accomplished rapidly and efficiently so as not to cause a significant overhead to the numerical simulation. A data redistribution model is also presented that predicts the remapping cost on the SP2. This model is required to determine whether the gain from a balanced workload distribution offsets the cost of data movement. Results presented in this paper demonstrate that PLUM is an effective dynamic load balancing strategy which remains viable on a large number of processors.

Oliker, Leonid↗

Offshore CO2 Saline Storage Calculator

The Offshore CO2 Saline Storage Calculator is a data-driven tool that applies the adapted DOE CO2 Methodology to calculate all potential distributions of offshore storage efficiency and resource potential at multiple spatial scales for saline formations. The tailored methodology include accounting for changing CO2 density with the overlying water column and sediment differences in unlithified, porous, and permeable offshore saline formations. The latest release of the tool and a tutorial are available in the tools public GitHub repository. We recommend testing out this application using data from the Petrophysical Well Log Interpretation Dataset, which spans the northern Gulf of Mexico and is available on EDX here: https://edx.netl.doe.gov/dataset/petrophysical-well-log-interpretation-dataset

calculator↗

Efficient Load Balancing and Data Remapping for Adaptive Grid Calculations

Mesh adaption is a powerful tool for efficient unstructured- grid computations but causes load imbalance among processors on a parallel machine. We present a novel method to dynamically balance the processor workloads with a global view. This paper presents, for the first time, the implementation and integration of all major components within our dynamic load balancing strategy for adaptive grid calculations. Mesh adaption, repartitioning, processor assignment, and remapping are critical components of the framework that must be accomplished rapidly and efficiently so as not to cause a significant overhead to the numerical simulation. Previous results indicated that mesh repartitioning and data remapping are potential bottlenecks for performing large-scale scientific calculations. We resolve these issues and demonstrate that our framework remains viable on a large number of processors.

Oliker, Leonid↗

Portable Slot-Sizing Tool

Portable milling tool consisting of air-motor-driven cutter held in adjustable moving slide made possible local removal of chromium plating in close-tolerance, onsite remachining and sizing of half-hole slots on longeron bridges. Made from commercially available parts, including air motor capable of variable speeds up to 900 rpm, ball end mill, revolving handle, two miter gears, and ball slide. Adaptation of portable sizing tool useful for field modification of such large equipment as trucks, aircraft, and ships.

Zuver, Nelson T.↗

Photovoltaic Analysis and Response Support (PARS) Platform for Solar Situational Awareness and Resiliency Services

The project's primary objective is to develop a digital-twin based Photovoltaic (PV) Analysis and Response Support (PARS) platform, which aims to provide real-time situational awareness and optimal response plans. This platform is designed to enhance the performance of hybrid PV systems, making them competitive with or even superior to conventional generation resources. The PARS platform enabled the project team to develop and evaluate an extensive suite of grid support functionalities for the hybrid PV systems to enhance grid performance, across key areas including visibility, dispatchability, security, resilience, and reliability. Given the global push toward achieving 100% clean energy by 2035, there is a significant increase in the integration of inverter-based resources (IBRs) throughout the energy grid. Effectively managing the inherent variability and uncertainty associated with IBRs is crucial for ensuring cost-effectiveness, reliability, and security in both the main grid and islanded microgrids. Constrained to a limited array of IEEE test systems or standard feeder models, traditional IBR modeling struggles to assimilate new field data, accurately reflect system dynamics, and adapt to the evolving energy landscape. In our project, we embraced a Digital Twin (DT) strategy for crafting the PARS platform. A digital twin acts as a precise virtual counterpart of a physical system, built on historical data and continuously honed with real-time insights. This enables the high-fidelity DT to accurately mirror current system operations and forecast future scenarios. Consequently, the PARS platform becomes an ideal environment for testing and refining monitoring, control, power, and energy management algorithms designed to boost hybrid PV system performance. The defining feature of the PARS platform, distinguishing it from other advanced simulation tools, is its exceptional adaptability. This is achieved by employing actual network topologies and utilizing real-time field data for fine-tuning and calibration, ensuring a close emulation of real-world conditions. The project deliverables include: 1) High-fidelity IBR models and tools for real-time parameterization, utilizing real-time field measurements to refine IBR models for enhanced accuracy and performance; 2) Grid-forming and Grid-following capabilities to deliver resilience services, including blackstart, voltage and frequency support, cold-load pick-up, power reserves, and three-phase load balancing across grid-connected and microgrid settings; 3) Machine learning-based forecasting tools and methods for generating synthetic data and topologies, creating diverse and realistic simulation environments for evaluating varied operational scenarios; 4) Advanced microgrid power and energy management algorithms for optimizing the integration and operation of PV, storage, and demand response resources within both feeder and community scales. The power grid data sets are provided by four utility companies in North Carolina and the New York Power Administration. Acting as industry advisors, our industry partners communicated stakeholder needs and regulatory standards to the research teams, aiding technology transfer by incorporating the developed methodologies into their daily operations. This collaboration ensures that the PARS platform, functioning as a power system digital twin, enhances our understanding of IBR dynamic behaviors and enables the development and evaluation of IBR control functions that match or exceed the capabilities of conventional synchronous generators.

14 SOLAR ENERGY↗