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

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DOE OSTI2018

Improved Preparedness in Galveston County, Texas Final Report CRADA No. TC02275

LLNS, as manager and operator of Lawrence Livermore National Laboratory (LLNL), and UTMB have a multi-year, ongoing, collaborative effort. This effort aimed to improve preparedness in Galveston County, Texas region and, more generally, identifying improved methods to (a) understand and mitigate the hazards of a large industrial chemical release and (b) implement and adapt national response plans and guidance to meet local planning and response needs. This CRADA was one portion of that effort and was intended to support the Hydrofluoric Acid (HF) Incident Symposium. This annual symposium engages a wide variety of government, private, and non-profit groups to (a) increase the resiliency, and reduce the vulnerability, of communities at risk of being impacted by major releases of toxic industrial chemicals and (b) guide the development of policies and best practices to prevent and manage these events. This CRADA project was originally scheduled for six (6) months and consisted of five major tasks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Classic and Quantum Task-Based Intelligent Runtime for QIRs Running on Multiple QPUs

High-performance computing systems are rapidly evolving into heterogeneous platforms that fuse quantum accelerators with traditional classical processing units (CPUs) and graphical processing units (GPUs). This convergence calls for runtimes capable of managing both classical and quantum workloads in a unified manner. We introduce an intelligent, task-based runtime that marries the Intelligent RuntIme System (IRIS) asynchronous scheduler with a quantum programming stack through the Quantum Intermediate Representation Execution Engine (QIR-EE). Our design allows programs written in the quantum intermediate representation (QIR) to be dispatched concurrently to a variety of back-ends, including multiple quantum simulators and nascent quantum processors, enabling genuine hybrid execution on a single node. To illustrate its practicality, we partition a 4-qubit and 20-qubit circuit into three sub-circuits using quantum circuit cutting via the QCut library. Each sub-circuit is simulated independently by the QIR-EE driver within IRIS, after which a classical post-processing step merges the simulation results to recover the outcome of the original full-circuit computation. This case study demonstrates how finer task granularity can enable the parallel execution and lower the simulation burden per quantum task while preserving overall accuracy, highlighting the feasibility of our hybrid approach.

Miniskar, Narasinga Rao [ORNL] (ORCID:000000018259↗
DOE OSTI2023

On the feasibility of future colliders: report of the Snowmass'21 Implementation Task Force

Colliders are essential research tools for particle physics. Numerous future collider proposal were discussed in the course of the US high energy physics community strategic planning exercise Snowmass'21. The Implementation Task Force (ITF) has been established to evaluate the proposed future accelerator projects for performance, technology readiness, schedule, cost, and environmental impact. Corresponding metrics has been developed for uniform comparison of the proposals ranging from Higgs/EW factories to multi-TeV lepton, hadron and ep collider facilities, based on traditional and advanced acceleration technologies. Here, this article describes the metrics and approaches, and presents evaluations of future colliders performed by the ITF.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

ExaWorks software development kit: a robust and scalable collection of interoperable workflows technologies

Scientific discovery increasingly requires executing heterogeneous scientific workflows on high-performance computing (HPC) platforms. Heterogeneous workflows contain different types of tasks (e.g., simulation, analysis, and learning) that need to be mapped, scheduled, and launched on different computing. That requires a software stack that enables users to code their workflows and automate resource management and workflow execution. Currently, there are many workflow technologies with diverse levels of robustness and capabilities, and users face difficult choices of software that can effectively and efficiently support their use cases on HPC machines, especially when considering the latest exascale platforms. We contributed to addressing this issue by developing the ExaWorks Software Development Kit (SDK). The SDK is a curated collection of workflow technologies engineered following current best practices and specifically designed to work on HPC platforms. We present our experience with (1) curating those technologies, (2) integrating them to provide users with new capabilities, (3) developing a continuous integration platform to test the SDK on DOE HPC platforms, (4) designing a dashboard to publish the results of those tests, and (5) devising an innovative documentation platform to help users to use those technologies. Our experience details the requirements and the best practices needed to curate workflow technologies, and it also serves as a blueprint for the capabilities and services that DOE will have to offer to support a variety of scientific heterogeneous workflows on the newly available exascale HPC platforms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Comparison of Deterministic and Statistical Models for Water Quality Compliance Forecasting in the San Joaquin River Basin, California

Model selection for water quality forecasting depends on many factors including analyst expertise and cost, stakeholder involvement and expected performance. Water quality forecasting in arid river basins is especially challenging given the importance of protecting beneficial uses in these environments and the livelihood of agricultural communities. In the agriculture-dominated San Joaquin River Basin of California, real-time salinity management (RTSM) is a state-sanctioned program that helps to maximize allowable salt export while protecting existing basin beneficial uses of water supply. The RTSM strategy supplants the federal total maximum daily load (TMDL) approach that could impose fines associated with exceedances of monthly and annual salt load allocations of up to $1 million per year based on average year hydrology and salt load export limits. The essential components of the current program include the establishment of telemetered sensor networks, a web-based information system for sharing data, a basin-scale salt load assimilative capacity forecasting model and institutional entities tasked with performing weekly forecasts of river salt assimilative capacity and scheduling west-side drainage export of salt loads. Web-based information portals have been developed to share model input data and salt assimilative capacity forecasts together with increasing stakeholder awareness and involvement in water quality resource management activities in the river basin. Two modeling approaches have been developed simultaneously. The first relies on a statistical analysis of the relationship between flow and salt concentration at three compliance monitoring sites and the use of these regression relationships for forecasting. The second salt load forecasting approach is a customized application of the Watershed Analysis Risk Management Framework (WARMF), a watershed water quality simulation model that has been configured to estimate daily river salt assimilative capacity and to provide decision support for real-time salinity management at the watershed level. Analysis of the results from both model-based forecasting approaches over a period of five years shows that the regression-based forecasting model, run daily Monday to Friday each week, provided marginally better performance. However, the regression-based forecasting model assumes the same general relationship between flow and salinity which breaks down during extreme weather events such as droughts when water allocation cutbacks among stakeholders are not evenly distributed across the basin. A recent test case shows the utility of both models in dealing with an exceedance event at one compliance monitoring site recently introduced in 2020.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Optimizing Performance on Trinity Utilizing Machine Learning, Proxy Applications and Scheduling Priorities

The sheer number of nodes continues to increase in today’s supercomputers, the first half of Trinity alone contains more than 9400 compute nodes. Since the speed of today’s clusters are limited by the slowest nodes, it more important than ever to identify slow nodes, improve their performance if it can be done, and assure minimal usage of slower nodes during performance critical runs. This is an ongoing maintenance task that occurs on a regular basis and, therefore, it is important to minimize the impact upon its users by assessing and addressing slow performing nodes and mitigating their consequences while minimizing down time. These issues can be solved, in large part, through a systematic application of fast running hardware assessment tests, the application of Machine Learning, and making use of performance data to increase efficiency of large clusters. Proxy applications utilizing both MPI and OpenMP were developed to produce data as a substitute for long runtime applications to evaluate node performance. Machine learning is applied to identify underperforming nodes, and policies are being discussed to both minimize the impact of underperforming nodes and increase the efficiency of the system. In this paper, I will describe the process used to produce quickly performing proxy tests, consider various methods to isolate the outliers, and produce ordered lists for use in scheduling to accomplish this task.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Performance of Heterogeneous Algorithm Scheduling in CMSSW

The CMS experiment started to utilize Graphics Processing Units (GPU) to accelerate the online reconstruction and event selection running on its High Level Trigger (HLT) farm in the 2022 data taking period. The projections of the HLT farm to the High-Luminosity LHC foresee a significant use of compute accelerators in the LHC Run 4 and onwards in order to keep the cost, size, and power budget of the farm under control. This direction of leveraging compute accelerators has synergies with the increasing use of HPC resources in HEP computing, as HPC machines are employing more and more compute accelerators that are predominantly GPUs today. In this work we review the features developed for the CMS data processing framework, CMSSW, to support the effective utilization of both compute accelerators and many-core CPUs within a highly concurrent task-based framework. We measure the impact of various design choices for the scheduling of heterogeneous algorithms on the event processing throughput, using the Run-3 HLT application as a realistic use case.

Bocci, Andrea↗
DOE OSTI2018

Toward a Synthetic Model for Distribution System Restoration and Crew Dispatch

Distribution service restoration (DSR) is critical for improving the resilience and reliability of modern distribution systems by strategically and sequentially energizing the system components and customer loads. Restoring electricity service to affected customers also requires multiple crews with different skill sets to perform multiple tasks that are procedurally interdependent with safety guaranteed. However, in existing DSR practices, switch operations and crew dispatch are scheduled separately, and their interdependence is not fully considered. As advanced technologies are enabling remote communication, control, and dispatch, utilities now desire an integrated DSR framework to achieve seamless coordination among multiple DSR tasks such as switch operation, crew dispatch, and component repair. In this paper, we introduce a synthetic model that integrates the service restoration model and the crew dispatch model based on a universal routing model. The proposed model can provide the estimated time of restoration for each load, the switching sequence for safely operating remotely/manually operated switches, and dispatch solutions for crews with different skill sets. The proposed synthetic model is formulated as a mixed-integer linear programming model, and its effectiveness is evaluated via the IEEE 123 bus test feeder and several large-scale test feeders (EPRI Ckt5, Ckt7, Ckt24, and IEEE 8500 node test feeder.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

PF-4 Seismic Performance Reassessment, Los Alamos National Laboratory, Project Charter and Integrated Project Team

This report presents the charter of the Integrated Project Team for conducting the PF-4 Seismic Performance Reassessment (P-SPRa) Project. The overall objective of the project is to compute the seismic performance of the PF-4 structure. The credited safety feature of the structure is to provide tertiary confinement of hazardous materials. This document highlights major tasks to be performed as part of the project. It includes a project schedule and a work breakdown structure dictionary. It also includes roles and responsibilities for key project personnel.

42 ENGINEERING↗
DOE OSTI2017

Integrating prediction, provenance, and optimization into high energy workflows

We propose a novel approach for efficient execution of workflows on distributed resources. The key components of this framework include: performance modeling to quantitatively predict workflow component behavior; optimization-based scheduling such as choosing an optimal subset of resources to meet demand and assignment of tasks to resources; distributed I/O optimizations such as prefetching; and provenance methods for collecting performance data. In preliminary results, these techniques improve throughput on a small Belle II workflow by 20%.

Schram, M.↗
DOE OSTI2017

Effective HTCondor-based monitoring system for CMS

The CMS experiment at the LHC relies on HTCondor and glideinWMS as its primary batch and pilot-based Grid provisioning systems, respectively. Given the scale of the global queue in CMS, the operators found it increasingly difficult to monitor the pool to find problems and fix them. The operators had to rely on several different web pages, with several different levels of information, and sift tirelessly through log files in order to monitor the pool completely. Therefore, coming up with a suitable monitoring system was one of the crucial items before the beginning of the LHC Run 2 in order to ensure early detection of issues and to give a good overview of the whole pool. Our new monitoring page utilizes the HTCondor ClassAd information to provide a complete picture of the whole submission infrastructure in CMS. The monitoring page includes useful information from HTCondor schedulers, central managers, the glideinWMS frontend, and factories. It also incorporates information about users and tasks making it easy for operators to provide support and debug issues.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

King City Asbestos Corporation (KCAC) Mine Carbon Mineralization Field Test (Final Combined Report)

The overall objective of the KCAC carbon mineralization project is to determine the most successful approaches to CO 2 mineralization of asbestos-bearing serpentinite rocks and mine waste at the closed KCAC asbestos mine. The objectives of Budget Period 1 (BP1) are to characterize the site including, mineralogical and geochemical variability in site materials, baseline conditions including CO 2 flux and local climate, and to establish the designs for the second, experimental phase of the project. As described in Section 3 of this report, all tasks outlined in the Statement of Project Objective (SOPO) have been completed or are on schedule to be completed by the end of BP1. As described in Section 4, all success criteria and milestones have been met or will be met by the end of BP1. We conclude that the findings of BP1 strongly support moving to the second phase of the project to investigate methods to increase the rate of CO 2 mineralization. CO 2 flux monitoring during BP1 established an estimated baseline uptake of CO 2 over the 142,193 m 2 KCAC mine site of 147 and 179 metric tons CO 2 /yr using dynamic closed chamber and eddy covariance monitoring methods, respectively. Mineralogical analysis shows that the loose surficial waste material contains pyroaurite and minor hydromagnesite, indicating past carbon mineralization. Sediment samples at depths below 60 cm contained ~3 wt% brucite and localized high brucite contents of ~24 wt% were measured at depth, indicating significant unreacted material at relatively shallow depths. Together, these results demonstrate that despite prolonged exposure to the atmosphere, reactive material is still present and accessible and is naturally taking up atmospheric CO 2 . However, these natural rates are still well below rates that can be achieved by applying practices that can accelerate the CO 2 mineralization reaction. Designs for the Field-Testing Phase (BP2) of the project have been established, incorporating the findings of BP1. Based on results to date we have selected two methods to accelerate the rate of CO 2 mineralization, which we refer to as the Tilling Method and the Greenhouse Method. We hypothesize that these methods can increase the CO 2 mineralization rate by up to 5 times greater than the natural background rate measured in BP1. An Initial Lifecyle Assessment (LCA) and techno-economic analysis (TEA) were conducted for these two methods. The LCA concluded that the baseline version of the Greenhouse and Tilling methods at commercial scale are expected to achieve a CDR efficiency of 97% and 71%, respectively (cumulative, over 30 years of operation). Incorporating the net CO 2 removal rates calculated in the LCA, the TEA found the levelized, 30-year costs of the baseline Greenhouse and Tilling methods to be $\$$95/t-CO 2 and $\$$119/t-CO 2 , respectively, and that costs could be brought to well below $\$$100/t-CO 2 for either method by scaling up the volume of rock utilized. An initial EH&S Risk Assessment, evaluating the potential EH&S risks of the proposed carbon mineralization methods at commercial scale, was completed by LLNL EH&S professionals for these two methods.

58 GEOSCIENCES↗
DOE OSTI2018

Automated Glovebox Work-cell Design - 18370

Los Alamos National Laboratory (LANL) is the primary plutonium science and manufacturing facility in the United States supporting multiple national security programs. It is responsible for completing a high variety of small-batch manufacturing tasks requiring the handling and precision machining of Special Nuclear Materials (SNM). Given the myriad of tasks that must be completed in a limited workspace, LANL intends to utilize flexible, multi-use robotic work-cells capable of completing a variety of mission critical tasks in a single glovebox with no re-tooling needed between batch jobs. This approach would allow LANL more flexibility in its production schedule and to meet its future production and research objectives. In this paper, we present a system that integrates multiple sensors and other manufacturing peripherals into existing glovebox infrastructure. Currently, a technician can place an object in the work area where vision sensors and supervisory software identify the object and its pose and automatically determine which manufacturing task to complete. Pose uncertainty is addressed in real-time by the task planner, eliminating the need for fixtures. Grasps are validated using pressure sensors, payload sensors, and grasp quality metrics to ensure that objects are not dropped or damaged during manipulation. The robot, sensors, and peripherals are controlled using open-source software built utilizing ROS (Robot Operating System), which minimizes redevelopment and allows for re-use and extensibility. Established capabilities support vision, collision-free path planning, and more, minimizing development time. For this effort, particular attention was given to the integration of general peripheral devices (drill, chuck, etc.), which is critical to efficiently utilizing ROS in manufacturing environments. This integration is achieved with an in-development framework that allows for quick integration of peripherals, including I/O devices and motors. Contact tasks utilize the Generalized Contact Control Framework (GCCF) previously developed at UT Austin. GCCF allows application developers to easily define multiple contact control tasks for a single robot. This paper summarizes the key software components necessary to develop the multi-use work-cell including existing ROS components. UT-developed software for grasp validation, peripheral integration, and contact control is presented in more depth. Finally the glovebox system is demonstrated completing a set of tasks with no fixturing necessary. Primary tasks include surface preparation/ablation, drilling, press-fitting, and sorting, as well as supporting material transfer and inspection tasks. The glovebox work-cell reduces cost, operator dose, ergonomic issues, and time loss due to material transfer between gloveboxes that only support one task. If multiple glovebox work-cells are in use, they have the potential to eliminate bottlenecks and scale production capabilities beyond current limits. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Dark energy survey operations: years 4 and 5

The Dark Energy Survey is a “stage III” dark energy experiment, performing an optical imaging survey to measure cos-mological equation of state parameters using four independent methods. The scope and complexity of the survey, originallyscheduled for 525 nights of observing spread over five years and combining a 5000 degree wide survey with a 10 field weeklytime-domain survey, introduced complex strategic and tactical scheduling problems that needed to be addressed. We beginwith an overview of the process used to develop DES strategy and tactics, from the inception of the project, to task forces thatstudied and developed strategy changes over the course of the survey, to the nightly pre-observing meeting in which imme-diate tactical issues were addressed. We then summarize the strategic choices made for each sub-survey, including metrics,scheduling considerations, choice of time domain fields and their sequences of exposures, and wide survey footprint andpointing layout choices. We go on to describe the detailed process that determined which specific exposures were taken atwhich specific times. We give a chronology of the strategic and tactical peculiarities of each year of observing, including theproposal and execution of a sixth year. We give an overview ofobstac, the implementation of the DES scheduler used to sim-ulate and evaluate strategic and tactical options, and automate exposure scheduling; and describe developments inobstacfor use after DES. Appendices describe further details of data quality evaluation,τ, andteff; airmass calculation; and model-ing of the seeing and sky brightness. The significant corpus of DES data indicates that the simple scaling relations for seeingas a function of wavelength and airmass derived from the Kolmogorov turbulence model work adequately for exposureplanning purposes: deviations from these relations are modest in comparison with short time-scale seeing variations

Gruendl, Robert A.↗
DOE OSTI2019

Dark Energy Survey’s Observation Strategy, Tactics, and Exposure Scheduler

The Dark Energy Survey is a “stage III” dark energy experiment, performing an optical imaging survey to measure cosmological equation of state parameters using four independent methods. The scope and complexity of the survey, originally scheduled for 525 nights of observing spread over five years and combining a 5000 degree wide survey with a 10 field weekly time-domain survey, introduced complex strategic and tactical scheduling problems that needed to be addressed. We begin with an overview of the process used to develop DES strategy and tactics, from the inception of the project, to task forces that studied and developed strategy changes over the course of the survey, to the nightly pre-observing meeting in which immediate tactical issues were addressed. We then summarize the strategic choices made for each sub-survey, including metrics, scheduling considerations, choice of time domain fields and their sequences of exposures, and wide survey footprint and pointing layout choices. We go on to describe the detailed process that determined which specific exposures were taken at which specific times. We give a chronology of the strategic and tactical peculiarities of each year of observing, including the proposal and execution of a sixth year. We give an overview of obstac, the implementation of the DES scheduler used to simulate and evaluate strategic and tactical options, and automate exposure scheduling; and describe developments in obstac for use after DES. Appendices describe further details of data quality evaluation, t, and teff; airmass calculation; and modeling of the seeing and sky brightness. The significant corpus of DES data indicates that the simple scaling relations for seeing as a function of wavelength and airmass derived from the Kolmogorov turbulence model work adequately for exposure planning purposes: deviations from these relations are modest in comparison with short time-scale seeing variations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

CMS readiness for multi-core workload scheduling

In the present run of the LHC, CMS data reconstruction and simulation algorithms benefit greatly from being executed as multiple threads running on several processor cores. The complexity of the Run 2 events requires parallelization of the code to reduce the memory-per- core footprint constraining serial execution programs, thus optimizing the exploitation of present multi-core processor architectures. The allocation of computing resources for multi-core tasks, however, becomes a complex problem in itself. The CMS workload submission infrastructure employs multi-slot partitionable pilots, built on HTCondor and GlideinWMS native features, to enable scheduling of single and multi-core jobs simultaneously. This provides a solution for the scheduling problem in a uniform way across grid sites running a diversity of gateways to compute resources and batch system technologies. This paper presents this strategy and the tools on which it has been implemented. The experience of managing multi-core resources at the Tier-0 and Tier-1 sites during 2015, along with the deployment phase to Tier-2 sites during early 2016 is reported. The process of performance monitoring and optimization to achieve efficient and flexible use of the resources is also described.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

A Length Adaptive Algorithm-Hardware Co-design of Transformer on FPGA Through Sparse Attention and Dynamic Pipelining

Transformers are considered one of the most important deep learning models since 2018, in part because it establishes state-of-the-art (SOTA) records and could potentially replace existing Deep Neural Networks (DNNs). Despite the remarkable triumphs, the prolonged turnaround time of Transformer models is a widely recognized roadblock. The variety of sequence lengths imposes additional computing overhead where inputs need to be zero-padded to the maximum sentence length in the batch to accommodate the parallel computing platforms. This paper targets the field-programmable gate array (FPGA) and proposes a coherent sequence length adaptive algorithm–hardware co-design for Transformer acceleration. Particularly, we develop a hardware-friendly sparse attention operator and a length-aware hardware resource scheduling algorithm. The proposed sparse attention operator brings the complexity of attention-based models down to linear complexity and alleviates the off-chip memory traffic. The proposed length-aware resource hardware scheduling algorithm dynamically allocates the hardware resources to fill up the pipeline slots and eliminates bubbles for NLP tasks. Experiments show that our design has very small accuracy loss and has 80.2 × and 2.6 × speedup compared to CPU and GPU implementation, and 4 × higher energy efficiency than state-of-the-art GPU accelerator optimized via CUBLAS GEMM.

Peng, Hongwu↗
DOE OSTI2019

SECARB Project Overview Book

In 2003, the United States Department of Energy (DOE) issued awards initiating seven Regional Carbon Sequestration Partnerships (RCSP) spanning the United States and portions of Canada. Managed by DOE’s National Energy Technology Laboratory (NETL), the RCSPs currently represent more than 400 state agencies, universities, and private companies, spanning 43 states, three Native American Organizations, and four Canadian provinces. The Southern States Energy Board (SSEB) received an award on October 1, 2003, which established the Board’s overall management and administration of the Southeast Regional Carbon Sequestration Partnership, or SECARB. The geographical region currently includes 13 states and a network of more than 100 stakeholders. The Nation’s leading scientists, university researchers, national laboratories, industrial representatives, environmental organizations, and many others have taken a proactive approach at identifying and characterizing the most promising options for technology deployment and carbon dioxide (CO2) utilization and storage (CCUS) for the Southeast. The results obtained during these injections will be important to the future commercialization of CCUS technologies and the continued use of fossil fuels as a significant energy source in a manner that is environmentally responsible. Each of the six SECARB project locations has been locally coordinated by its own field team. The field teams assume responsibility for the technical scope of work, local education and outreach, permitting, monitoring, verification, and accounting (MVA), and maintaining the validation test’s schedule and budget. Each team contributes new information to the continued characterization of the region. In addition, a task is dedicated to integrating field data and filling gaps in regional characterization data sets. Data and tools developed in the Continued Characterization task are incorporated into a relational database and geographic information system (GIS). All field tests, the continued characterization project, and the cross-cutting functions are designed to support the DOE roadmap by validating technologies and identifying locations throughout the region that could support full-scale CCUS deployment opportunities. Detailed fact sheets for the SECARB projects are available on the SECARB website at www.secarbon.org (see “Projects” tab).

RCSP↗