SEARCH · Engineering Papers

Results for “task work”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 523 records · Page 29

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Annual Report on NCSP Technical Support task in BNL during FY25

This work reports on the investigations done during FY 25 in collaboration with one 2025 Summer undergraduate intern through the DOE SULI program. These efforts were partially funded by the Nuclear Criticality Safety Program through the Technical Support Succession Plan task. This project, developed by Matthew Molnar, aimed to apply the BNL’s machine-learning code to correct spin mis-assignments in neutron resonances, the Bayesian Resonance Reclassifier (BRR), to the odd-even nucleus 143 Nd. For this, the handling of spingroup classification had to be further investigated and improved.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2018

A View from ORNL: Scientific Data Research Opportunities in the Big Data Age

One of the core issues across computer and computational science today is adapting to, managing, and learning from the influx of "Big Data". In the commercial space, this problem has led to a huge investment in new technologies and capabilities that are well adapted to dealing with the sorts of human-generated logs, videos, texts, and other large-data artifacts that are processed and resulted in an explosion of useful platforms and languages (Hadoop, Spark, Pandas, etc.). However, translating this work from the enterprise space to the computational science and HPC community has proven somewhat difficult, in part because of some of the fundamental differences in type and scale of data and timescales surrounding its generation and use. We describe a forward-looking research and development plan which centers around the concept of making Input/Output (I/O) intelligent for users in the scientific community, whether they are accessing scalable storage or performing in situ workflow tasks. Much of our work is based on our experience with the Adaptable I/O System (ADIOS 1.X), and our next generation version of the software ADIOS 2.X [1].

Klasky, Scott↗

DOE OSTI2019

Aluminum Clad SNF: Technical Considerations and Challenges for Extended (>50 years) Dry Storage - 1900y

The U.S. Department of Energy (DOE) manages a significant inventory (>13 MTHM) of aluminum clad spent nuclear fuel (ASNF) using a combination of wet and dry storage at three primary sites; Hanford, Idaho National Laboratory (INL), and Savannah River Site (SRS). The majority of this ASNF is generated from U.S. and international research test reactors (RTR), examples include Advanced Test Reactor (ATR) at INL and High-Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL). The Obama Administration suspension of the Yucca Mountain repository, issuance of the January 2013 DOE 'Strategy for the Management and Disposal of Used Nuclear Fuel and High-Level Radioactive Waste,' delays in implementing the 'regionalization' SNF approach recommended in the 1995 'Department of Energy Programmatic Spent Nuclear Fuel Management and Idaho National Engineering Laboratory Environmental Restoration and Waste Management Programs Final Environmental Impact Statement,' and limited ASNF processing capability at SRS H-Canyon means that interim storage has become the de-facto strategy for managing ASNF. The 1995 Idaho Settlement Agreement requires the DOE to transfer all SNF stored at INL to interim dry storage prior to December 31, 2023 and wet storage capacity at the SRS is nearing capacity. This situation was recognized by the DOE Spent Nuclear Fuel Working Group (SNFWG) and at its June 2016 meeting formed a ASNF sub-working group comprised subject matter experts to evaluate this area and provide a report of findings. The ASNF sub-working group met many times over several month period to review the engineering and technical basis of existing and planned DOE ASNF dry storage facilities and additional studies on the behavior of ASNF under different conditions, including during reactor service. The ASNF sub-working group focused its review on RTR SNF. Based on these reviews, the ASNF sub-working group identified five knowledge gaps and technical data needs that should be addressed to ensure viability and safety of extended, greater than 50 years, sealed or vented interim dry storage of ASNF. These five areas include; behavior/chemistry of aluminum oxyhydroxide layer in dry storage, radiolytic gas generation properties of aluminum oxyhydroxide layers, effect of episodic breathing and radiolytic generation of corrosive gases during storage, performance of ASNF in existing dry storage systems, and effects of high temperature (>1000 C) drying on chemistry and behavior of aluminum oxyhydroxide layers. The ASNF sub-working group also recommended development of an action plan to identify technical and engineering activities needed to address the knowledge gaps and technical data needs. Results of the ASNF sub-working group are documented in 2017 report 'Aluminum Clad Spent Nuclear Fuel: Technical Considerations and Challenges for Extended (>50 years) Dry Storage,' DOE-ID/RPT-1575. The INL assembled a team comprised of twenty INL and Savannah River National Laboratory SNF management and subject matter experts to develop this action plan. Over the course of 2 months the team worked to develop the action plan. The plan identified and recommended six technical and engineering tasks needed to address the previously identified knowledge gaps and technical data needs. DOE Environmental Management Office of Technology Development is providing funding to the INL to execute these tasks. This paper will present and discuss the results of the ASNF sub-working group, tasks identified in the action plan, and experimental activities underway at INL and SRNL to address the action plan. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2016

High Performance Teams Enable Mission Success for SRNL - 16363

The accomplishment of the DOE EM mission of cleaning up the radioactive waste generated as a byproduct of the development and maintenance of nuclear materials over the last 60 years is a daunting task. SRNL specializes in working directly with the 'owners' of the cleanup challenges to identify the desired outcome and develop a solution that can be put into practice. 'We put science to work' is not just a 'tag line' rather it is a concise statement of our values and approach to applying science and engineering to the cleanup objectives. The management of radioactive waste poses multi-decade challenges to DOE EM and the Nation. The ability to harness the depth of knowledge, experience, expertise and passion for safely and effectively solving the technical challenges has reached a critical junction. Perhaps too late to be a natural and organic transition the industry finds itself critically devoid of resources to effectively and efficiently keep focused on the highest order task: cleanup. When project managers plan the resources necessary to perform the planned scope they typically are focused on financial, human, and industrial resources that would be beneficial to project execution. The critical shortage we will be evaluating is experienced and skilled leaders, mentors and coaches in the workforce. The production of educated scientists and engineers is a primary focus at all levels of educational institutions with Science Technology Engineering and Mathematics (STEM) focused curricula beginning in elementary school. The need for leaders who are skilled in inspiring organizational creativity, adept in harnessing and focusing individual energy while effectively communicating to the work force and the clientele equally compelling messages, has never been greater, or their absence in the workforce more ominous. Managers trained in the classical management theory (insert references here) are aging out of the workforce. In many cases these managers have not retained close connection to advancements in their primary field of study but rather have succumbed to the administrivia burdens that typify highly regulated work. The current technically trained workforce while interested in the 'perks' of management (i.e. visibility, pay increases, advancing status) are driven to keep close connection to their technical 'roots' as a fall-back plan should they need to change their career path either by choice or necessity. The challenge is how to achieve the productive hum of a finely tuned organizational model that blends executive vision and drive with technical leadership and excellence in execution. If any of these three tenets of a high performance team falters the ability to recover erodes the performance of the team and begins to weaken the cultural foundation essential to sustaining high performance work teams. At SRNL, recognition of the need to adapt the management dynamics and the business model and to harness the energy of the workforce to sustain - and in fact increase - the level of performance is a driving force in the transformation of the organization. Examples of changes in organizations structure, business systems and employee engagement are discussed as they relate to the impact on accomplishing the cleanup mission and fostering the next generation of great leaders and innovators. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Annual Report on NCSP Technical Support task in BNL during FY24

This work reports on the investigations done during FY 24 in collaboration with two 2024 Summer undergraduate interns through the DOE SULI and BNL SURP programs. These efforts were partially funded by the Nuclear Criticality Safety Program through the Technical Support Succession Plan task. The first project, developed by Ian Snider, focused on testing the impact of uncertainties in thermal cross sections for multiple materials in nuclear reactor simulations. The second project aimed implement concurrent into BNL’s machine-learning code to correct spin mis-assignments in neutron resonances, the Bayesian Resonance Reclassifier (BRR).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1999

Multimodal Preception and Multicriterion Control of Nested Systems: A Functional Visual Assessment Test for Human Health Maintenance and Countermeasure Evaluation - 3

Our theoretical and empirical research on the whole-body coordination during locomotion led to a Phase 1 SBIR grant from NASA JSC. The purpose of the SBIR grant was to design an innovative system for evaluating eye-head-trunk coordination during whole-body perturbations that are characteristic of locomotion. The approach we used to satisfy the Phase 1 objectives was based on a structured methodology for the development of human-systems technology. Accordingly the project was broken down into a number of tasks and subtasks. In sequence, the major tasks were: (1) identify needs for functional assessment of visual acuity under conditions involving whole-body perturbation within the NASA Space Medical Monitoring and Countermeasures (SMMaC) program and in other related markets; (2) analyze the needs into the causes and symptoms of impaired visual acuity under conditions involving whole-body perturbation; (3) translate the analyzed needs into technology requirements for the Functional Visual Assessment Test (FVAT); (4) identify candidate technology solutions and implementations of FVAT; and (5) prioritize and select technology solutions. The work conducted in these tasks is described in this final volume of the series on Multimodal Perception and Multicriterion Control of Nested Systems. While prior volumes (1 and 2) in the series focus on theoretical foundations and novel data-analytic techniques, this volume addresses technology that is necessary for minimally intrusive data collection and near-real-time data analysis and display.

Riccio, Gary E.↗

NASA NTRS2016

NASA Advanced Explorations Systems: Advancements in Life Support Systems

The NASA Advanced Exploration Systems (AES) Life Support Systems (LSS) project strives to develop reliable, energy-efficient, and low-mass spacecraft systems to provide environmental control and life support systems (ECLSS) critical to enabling long duration human missions beyond low Earth orbit (LEO). Highly reliable, closed-loop life support systems are among the capabilities required for the longer duration human space exploration missions assessed by NASA's Habitability Architecture Team (HAT). The LSS project is focused on four areas: architecture and systems engineering for life support systems, environmental monitoring, air revitalization, and wastewater processing and water management. Starting with the international space station (ISS) LSS systems as a point of departure (where applicable), the mission of the LSS project is three-fold: 1. Address discrete LSS technology gaps 2. Improve the reliability of LSS systems 3. Advance LSS systems towards integrated testing on the ISS. This paper summarized the work being done in the four areas listed above to meet these objectives. Details will be given on the following focus areas: Systems Engineering and Architecture- With so many complex systems comprising life support in space, it is important to understand the overall system requirements to define life support system architectures for different space mission classes, ensure that all the components integrate well together and verify that testing is as representative of destination environments as possible. Environmental Monitoring- In an enclosed spacecraft that is constantly operating complex machinery for its own basic functionality as well as science experiments and technology demonstrations, it's possible for the environment to become compromised. While current environmental monitors aboard the ISS will alert crew members and mission control if there is an emergency, long-duration environmental monitoring cannot be done in-orbit as current methodologies rely largely on sending environmental samples back to Earth. The LSS project is developing onboard analysis capabilities that will replace the need to return air and water samples from space for ground analysis. Air Revitalization- The air revitalization task is comprised of work in carbon dioxide removal, oxygen generation and recovery and trace contamination and particulate control. The CO2 Removal and associated air drying development efforts under the LSS project are focused both on improving the current SOA technology on the ISS and assessing and examining the viability of other sorbents and technologies available in academia and industry. The Oxygen Generation and Recovery technology development area encompasses several sub-tasks in an effort to supply O2 to the crew at the required conditions, to recover O2 from metabolic CO2, and to recycle recovered O2 back to the cabin environment. Current state-of-the-art oxygen generation systems aboard space station are capable of generating or recovering approximately 40% of required oxygen; for exploration missions this percentage needs to be greatly increased. A spacecraft cabin trace contaminant and particulate control system serves to keep the environment below the spacecraft maximum allowable concentration (SMAC) for chemicals and particulates. Both passive (filters) and active (scrubbers) methods contribute to the overall TC & PC design. Work in the area of trace contamination and particulate control under the LSS project is focused on making improvements to the SOA TC & PC systems on ISS to improve performance and reduce consumables. Wastewater Processing and Water Management- A major goal of the LSS project is the development of water recovery systems to support long duration human exploration beyond LEO. Current space station wastewater processing and water management systems distill urine and wastewater to recover water from urine and humidity condensate in the spacecraft at a approximately 74% recovery rate. For longer, farther missions into deep space, that recovery rate must be greatly increased so that astronauts can journey for months without resupply cargo ships from Earth.

Shull, Sarah A.↗

NASA NTRS1993

Indirect decentralized repetitive control

Learning control refers to controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work, the authors presented a theory of indirect decentralized learning control based on use of indirect adaptive control concepts employing simultaneous identification and control. This paper extends these results to apply to the indirect repetitive control problem in which a periodic (i.e., repetitive) command is given to a control system. Decentralized indirect repetitive control algorithms are presented that have guaranteed convergence to zero tracking error under very general conditions. The original motivation of the repetitive control and learning control fields was learning in robots doing repetitive tasks such as on an assembly line. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the desired trajectory. Decentralized repetitive control is natural for this application because the feedback control for link rotations is normally implemented in a decentralized manner, treating each link as if it is independent of the other links.

Lee, Soo Cheol↗

DOE OSTI2020

Modeling Photovoltaics Innovation and Deployment Dynamics

PV’s historically rapid cost reduction is exceptional among technologies. Further cost reductions could play a major role in increasing deployment in the future. To enable such cost reductions, new modeling frameworks are needed to understand the determinants of innovation in PV. In this project, we study the mechanisms driving PV module and system cost reductions, delving deeply into the specific technological innovations that have occurred in the past and the policies that encouraged them, and also opportunities for future cost reduction and widespread deployment. The project contributes new fundamental insight on the determinants of technological innovation by developing novel methods and insights that are generalizable and can therefore be applied to other technologies. The results will allow policy makers, engineers, and other stakeholders to better prioritize their efforts and investments in the future. The project is organized around four journal articles as described below. The first article [1] identifies ‘low-level’ (e.g. conversion efficiency improvement) and ‘high- level’ (e.g. R&D efforts) mechanisms of cost reduction in PV systems (Tasks 1-4). This work builds on a previous DOE grant, where we developed a framework for technological innovation leading to PV module cost reduction [2]. We advance a method to disentangle the contributions of physical (‘hardware’) and non-physical (‘soft technology’) changes. Our results uncover reasons behind the relatively slow evolution of soft technology and can inform new innovation approaches to these technologies. The second article [3] identifies specific engineering or institutional innovations that enabled the low-level mechanisms of cost reduction in PV module and balance-of-systems (BOS) (Tasks 5, 9, 10). We identify 85 innovations and connect them to the cost variables they affected. By developing an innovations typology, this study shows the differences between the types of innovations affecting PV modules and BOS components. Finally, by analyzing the industry origins of innovations, this study also finds that PV was well-positioned within an ecosystem of continuously advancing technologies. The third article [4] studies prospective cost reduction opportunities (Task 10). We explore how design approaches that emphasize standardization and automation, such as plug-and-play PV systems, can create cost reduction opportunities by reducing interactions and speeding up activities with high process costs. We show that this can lead to cost reduction in cost components with the most untapped opportunity for improvement such as installation labor, overhead, electrical BOS, and customer acquisition. The fourth article [5] analyzes how various policies supporting PV deployment and R&D contributed to PV’s cost improvement by enabling high-level mechanisms, specific innovations, and ultimately low-level mechanisms of cost reduction (Tasks 8, 13, 14). We investigate examples from different countries and connect these policies to quantifiable cost change mechanisms. Our study sheds light on the roles that different nations played over time, through a diverse set of policy approaches.

14 SOLAR ENERGY↗

NASA NTRS1972

Experiments evaluating compliance and force feedback effect on manipulator performance

The performance capability was assessed of operators performing simulated space tasks using manipulator systems which had compliance and force feedback varied. Two manipulators were used, the E-2 electromechanical man-equivalent (force, reach, etc.) master-slave system and a modified CAM 1400 hydraulic master-slave with 100 lbs force capability at reaches of 24 ft. The CAM 1400 was further modified to operate without its normal force feedback. Several experiments and simulations were performed. The first two involved the E-2 absorbing the energy of a moving mass and secondly, guiding a mass thru a maze. Thus, both work and self paced tasks were studied as servo compliance was varied. Three simulations were run with the E-2 mounted on the CAM 1400 to evaluate the concept of a dexterous manipulator as an end effector of a boom-manipulator. Finally, the CAM 1400 performed a maze test and also simulated the capture of a large mass as the servo compliance was varied and with force feedback included and removed.

Kugath, D. A.↗

DOE OSTI2016

Coordinated joint motion control system with position error correction

Disclosed are an articulated hydraulic machine supporting, control system and control method for same. The articulated hydraulic machine has an end effector for performing useful work. The control system is capable of controlling the end effector for automated movement along a preselected trajectory. The control system has a position error correction system to correct discrepancies between an actual end effector trajectory and a desired end effector trajectory. The correction system can employ one or more absolute position signals provided by one or more acceleration sensors supported by one or more movable machine elements. Good trajectory positioning and repeatability can be obtained. A two joystick controller system is enabled, which can in some cases facilitate the operator's task and enhance their work quality and productivity.

42 ENGINEERING↗

DOE OSTI2021

Anomaly Attribution with Likelihood Compensation

This paper addresses the task of explaining anomalous predictions of a black-box regression model. When using a black-box model, such as one to predict building energy consumption from many sensor measurements, we often have a situation where some observed samples may significantly deviate from their prediction. It may be due to a sub-optimal black-box model, or simply because those samples are outliers. In either case, one would ideally want to compute a responsibility score indicative of the extent to which an input variable is responsible for the anomalous output. In this work, we formalize this task as a statistical inverse problem: Given model deviation from the expected value, infer the responsibility score of each of the input variables. We propose a new method called likelihood compensation (LC), which is founded on the likelihood principle and computes a correction to each input variable. To the best of our knowledge, this is the first principled framework that computes a responsibility score for real valued anomalous model deviations. We apply our approach to a real-world building energy prediction task and confirm its utility based on expert feedback.

Idé, Tsuyoshi↗

DOE OSTI2017

Development/Modernization of an Advanced Non-Light Water Reactor Probabilistic Risk Assessment

In 2015, GE Hitachi Nuclear Energy (GEH) teamed with Argonne National Laboratory (Argonne) to perform Research and Development (R&D) of next-generation Probabilistic Risk Assessment (PRA) methodologies for the modernization of an advanced non-Light Water Reactor (non-LWR) PRA. This effort built upon a PRA developed in the early 1990s for GEH’s Power Reactor Inherently Safe Module (PRISM) Sodium Fast Reactor (SFR). The work had four main tasks: internal events development modeling the risk from the reactor for hazards occurring at-power internal to the plant; an all hazards scoping review to analyze the risk at a high level from external hazards such as earthquakes and high winds; an all modes scoping review to understand the risk at a high level from operating modes other than at-power; and risk insights to integrate the results from each of the three phases above. To achieve these objectives, GEH and Argonne used and adapted proven PRA methodologies and techniques to build a modern non-LWR all hazards/all modes PRA. The teams also advanced non-LWR PRA methodologies, which is an important outcome from this work. This report summarizes the project outcomes in two major phases. The first phase presents the methodologies developed for non-LWR PRAs. The methodologies are grouped by scope, from Internal Events At-Power (IEAP) to hazards analysis to modes analysis. The second phase presents details of the PRISM PRA model which was developed as a validation of the non-LWR methodologies. The PRISM PRA was performed in detail for IEAP, and at a broader level for hazards and modes. In addition to contributing methodologies, this project developed risk insights applicable to non-LWR PRA, including focus-areas for future R&D, and conclusions about the PRISM design.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Industrial Assessment Center Program (Final Report)

This report summarizes the activities of the Industrial Assessment Center (IAC) at San Francisco State University (SFSU) under the Award No. DE-EE0007705 for the period of October 1, 2016 through September 30, 2021. The work performed under the award and related achievements are summarized per task in the statement of the work in the award.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2012

Two Dimensional Heat Transfer around Penetrations in Multilayer Insulation

The objective of this task was to quantify thermal losses involving integrating MLI into real life situations. Testing specifically focused on the effects of penetrations (including structural attachments, electrical conduit/feedthroughs, and fluid lines) through MLI. While there have been attempts at quantifying these losses both analytically and experimentally, none have included a thorough investigation of the methods and materials that could be used in such applications. To attempt to quantify the excess heat load coming into the system due to the integration losses, a calorimeter was designed to study two dimensional heat transfer through penetrated MLI. The test matrix was designed to take as many variables into account as was possible with the limited test duration and system size. The parameters varied were the attachment mechanism, the buffer material (for buffer attachment mechanisms only), the thickness of the buffer, and the penetration material. The work done under this task is an attempt to measure the parasitic heat loads and affected insulation areas produced by system integration, to model the parasitic loads, and from the model produce engineering equations to allow for the determination of parasitic heat loads in future applications. The methods of integration investigated were no integration, using a buffer to thermally isolate the strut from the MLI, and temperature matching the MLI on the strut. Several materials were investigated as a buffer material including aerogel blankets, aerogel bead packages, cryolite, and even an evacuated vacuum space (in essence a no buffer condition).

Johnson, Wesley L.↗

NASA NTRS1994

Investigations into mirror fabrication metrology analysis

This final report describes the work performed under this delivery order from June 1993 through August 1994. The scope of work included three distinct tasks in support of the AXAF-I program. The objective of the first task was to perform investigations of the grinding and polishing characteristics of the zerodur material by fabricating several samples. The second task was to continue the development of the integrated optical performance modeling software for AXAF-I. The purpose of third and final task was to develop and update the database of AXAF technical documents for an easy and rapid access. The MSFC optical and metrology shops were relocated from the B-wing of Building 4487 to Room BC 144 of Building 4466 in the beginning of this contract. This included dismantling, packing, and moving the equipment from its old location, and then reassembling it at the new location. A total of 65 zerodur samples, measuring 1 inch x 2 inches x 6 inches were ground and polished to a surface figure of lambda/10 p-v, and a surface finish of 5A rms were fabricated for coating tests. A number of special purpose tools and metal mirrors were also fabricated to support various AXAF-I development activities. In the metrology area, the ZYGO Mark 4 interferometer was relocated and also upgraded with a faster and more powerful processor. Surface metrology work was also performed on the coating samples and other optics using ZYGO interferometer and WYKO profilometer. A number of new features have been added to the GRAZTRACE program to enhance its analysis and modeling capabilities. A number of new commands have been added to the command mode GRAZTRACE program to provide a better control to the user on the program execution and data manipulation. Some commands and parameter entries have been reorganized for a uniform format. The command mode version of the convolution program CONVOLVE has been developed. An on-line help system and a user's manual have also been developed for the benefit of the users. The database of AXAF technical documents continues to progress. The titles, company name, date, and location of over 390 documents have been entered in this database. This database provides both a data search and retrieval function, and a data adding function. These functions allow a user to quickly search the data files for documents or add new information. A detailed user's guide has also been prepared. This user guide includes a document classification guide, a list of abbreviations, and a list of acronyms, which have been used in compiling this database of AXAF-I technical documents.

Dimmock, John O.↗

DOE OSTI2022

Deep Learning Based Superconducting Radio-Frequency Cavity Fault Classification at Jefferson Laboratory

This work investigates the efficacy of deep learning (DL) for classifying C100 superconducting radio-frequency (SRF) cavity faults in the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. CEBAF is a large, high-power continuous wave recirculating linac that utilizes 418 SRF cavities to accelerate electrons up to 12 GeV. Recent upgrades to CEBAF include installation of 11 new cryomodules (88 cavities) equipped with a low-level RF system that records RF time-series data from each cavity at the onset of an RF failure. Typically, subject matter experts (SME) analyze this data to determine the fault type and identify the cavity of origin. This information is subsequently utilized to identify failure trends and to implement corrective measures on the offending cavity. Manual inspection of large-scale, time-series data, generated by frequent system failures is tedious and time consuming, and thereby motivates the use of machine learning (ML) to automate the task. This study extends work on a previously developed system based on traditional ML methods (Tennant and Carpenter and Powers and Shabalina Solopova and Vidyaratne and Iftekharuddin, Phys. Rev. Accel. Beams, 2020, 23, 114601), and investigates the effectiveness of deep learning approaches. The transition to a DL model is driven by the goal of developing a system with sufficiently fast inference that it could be used to predict a fault event and take actionable information before the onset (on the order of a few hundred milliseconds). Because features are learned, rather than explicitly computed, DL offers a potential advantage over traditional ML. Specifically, two seminal DL architecture types are explored: deep recurrent neural networks (RNN) and deep convolutional neural networks (CNN). We provide a detailed analysis on the performance of individual models using an RF waveform dataset built from past operational runs of CEBAF. In particular, the performance of RNN models incorporating long short-term memory (LSTM) are analyzed along with the CNN performance. Furthermore, comparing these DL models with a state-of-the-art fault ML model shows that DL architectures obtain similar performance for cavity identification, do not perform quite as well for fault classification, but provide an advantage in inference speed.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Bringing heterogeneity to the CMS software framework

The advent of computing resources with co-processors, for example Graphics Processing Units (GPU) or Field-Programmable Gate Arrays (FPGA), for use cases like the CMS High-Level Trigger (HLT) or data processing at leadership-class supercomputers imposes challenges for the current data processing frameworks. These challenges include developing a model for algorithms to offload their computations on the co-processors as well as keeping the traditional CPU busy doing other work. The CMS data processing framework, CMSSW, implements multithreading using the Intel Threading Building Blocks (TBB) library, that utilizes tasks as concurrent units of work. In this paper we will discuss a generic mechanism to interact effectively with non-CPU resources that has been implemented in CMSSW. In addition, configuring such a heterogeneous system is challenging. In CMSSW an application is configured with a configuration file written in the Python language. The algorithm types are part of the configuration. The challenge therefore is to unify the CPU and co-processor settings while allowing their implementations to be separate. We will explain how we solved these challenges while minimizing the necessary changes to the CMSSW framework. We will also discuss on a concrete example how algorithms would offload work to NVIDIA GPUs using directly the CUDA API.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗