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At least 685 records · Page 38

The Effect of Information Feedback Upon Psychophysical Judgments

An analysis was made of the role of presentation schedules and information feedback on performance in a forced-choice signal detection task. The experimental results indicate that information feedback facilitates performance, but only for certain presentation schedules. The present study was designed to assess performance in a signal detection task under two conditions of information feedback. In the I-condition, S was told on each trial whether his detection response was correct or incorrect; in the !-condition S was given no feedback regarding the correctness of his response. The task involved a 2-response, forced-choice auditory detection problem. On each trial 2 temporal intervals were defined and S was required to report which interval he believed contained the signal; i. e., in one interval a tone burst in a background of white noise was presented, while the other interval contained only white noise. A trial will be denoted as s1 or s2, depending on whether the signal was embedded in the 1st or 2nd interval; the S's response will be denoted A1 or A2 to indicate which interval he reported contained the signal. The probability of an s1 trial will be denoted as y. In this study two values of y were used (.50 and.75) and, as indicated above, two conditions of information feedback. Thus there were 4 experimental conditions (501, · 50I, 751, 75I); each S was run under all 4 conditions. Method Gaussian noise was presented binaurally in S's headphones throughout a test session and the signal was a 1000-cps sinusoid tone; the tone was presented for 100 msec. including equal fall and rise times of 20 msec. The ratio of signal energy to noise power in a unit bandwidth was 2.9, and was constant throughout the study. The. S was seated before a stimulus display board. On each trial a red warning light was flashed for 100 msec. Two amber lights then came on successively each for 1 sec.; these lights defined the 2 observation intervals. The onset of the signal occurred 500 msec. after the onset of one of the observation intervals. After the second amber light went off, S indicated his response by pressing 1 of 2 wand switches under cards reading "1st interval" and "2nd interval." For the !-condition a green light flashed on above the correct response key after S's response; the green light was omitted in the !-condition. Each trial lasted 6 sec. The S's were 12 male college students with normal hearing. They were run for two practice sessions followed by 20 test sessions. Test sessions were run on consecutive days, 350 trials/day. Each day S ran on 1 of the 4 experimental conditions; in successive 4-day blocks S ran one day on each of the 4 experimental conditions in a random order. Thus, over 20 days each of the experimental conditions was repeated 5 times.

Atkinson, Richard C.↗

Exploring the Performance of Spark for a Scientific Use Case

We present an evaluation of the performance of a Spark implementation of a classification algorithm in the domain of High Energy Physics (HEP). Spark is a general engine for in-memory, large-scale data processing, and is designed for applications where similar repeated analysis is performed on the same large data sets. Classification problems are one of the most common and critical data processing tasks across many domains. Many of these data processing tasks are both computation- and data-intensive, involving complex numerical computations employing extremely large data sets. We evaluated the performance of the Spark implementation on Cori, a NERSC resource, and compared the results to an untuned MPI implementation of the same algorithm. While the Spark implementation scaled well, it is not competitive in speed to our MPI implementation, even when using significantly greater computational resources.

Sehrish, Saba↗

GPUs as boosters to analyze scalar and vector fields in quantum chemistry

We report that the analysis of scalar and vector fields in quantum chemistry is an essential task for the computational chemistry community, where such quantities must be evaluated rapidly to perform a particular study. For example, the atoms in molecules approach proposed by Bader has become popular; however, this method demands significant computational resources to compute the involved tasks in short times. In this article, we discuss the importance of graphics processing units (GPU) to analyze electron density, and related fields, implementing several scalar, and vector fields within the graphics processing units for atoms and molecules (GPUAM) code developed by a group of the Universidad Autónoma Metropolitana in México City. With this application, the quantum chemistry community can perform demanding computational tasks on a desktop, where CPUs and GPUs are used to their maximum capabilities. Lastly, the performance of GPUAM is tested in several systems and over different GPUs, where a GPU installed in a workstation converts it to a robust high-performance computing system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Issues in knowledge representation to support maintainability: A case study in scientific data preparation

Scientific data preparation is the process of extracting usable scientific data from raw instrument data. This task involves noise detection (and subsequent noise classification and flagging or removal), extracting data from compressed forms, and construction of derivative or aggregate data (e.g. spectral densities or running averages). A software system called PIPE provides intelligent assistance to users developing scientific data preparation plans using a programming language called Master Plumber. PIPE provides this assistance capability by using a process description to create a dependency model of the scientific data preparation plan. This dependency model can then be used to verify syntactic and semantic constraints on processing steps to perform limited plan validation. PIPE also provides capabilities for using this model to assist in debugging faulty data preparation plans. In this case, the process model is used to focus the developer's attention upon those processing steps and data elements that were used in computing the faulty output values. Finally, the dependency model of a plan can be used to perform plan optimization and runtime estimation. These capabilities allow scientists to spend less time developing data preparation procedures and more time on scientific analysis tasks. Because the scientific data processing modules (called fittings) evolve to match scientists' needs, issues regarding maintainability are of prime importance in PIPE. This paper describes the PIPE system and describes how issues in maintainability affected the knowledge representation used in PIPE to capture knowledge about the behavior of fittings.

Chien, Steve↗

Subjective Workload Assessment and Voluntary Control of Effort in a Tracking Task

A manual control tracking task was manipulated along two dimensions: (1) control order and (2) forcing function bandwidth. In the first phase of the experiment subjective workload assessments were collected. It was found that subjective assessments of workload were closely associated with performance in the case of increasing control order, but not in the case of increasing bandwidth. This was interpreted as indicating that subjective workload assessments are most appropriate for the study of increasing difficulty centered in response selection processes as opposed to response execution processes. In the second phase of the experiment the subjects were asked to voluntarily limit the effort they applied in the performance of the tracking task. The results indicate that the subjects were quite facile in doing this. However, comparison of these data to the findings of other studies that manipulated effort via dual-task biasing indicate that effort manipulation is much more potent in a single-task configuration. This finding is discussed in terms of multiple resource theories of attentional capacity. The utility of an analysis of covariance procedure in studying the relationships between subjective ratings and performance is highlighted.

Vidulich, M. A.↗

Digital processing of mesoscale analysis and space sensor data

The mesoscale analysis and space sensor (MASS) data management and analysis system on the research computer system is presented. The MASS data base management and analysis system was implemented on the research computer system which provides a wide range of capabilities for processing and displaying large volumes of conventional and satellite derived meteorological data. The research computer system consists of three primary computers (HP-1000F, Harris/6, and Perkin-Elmer 3250), each of which performs a specific function according to its unique capabilities. The overall tasks performed concerning the software, data base management and display capabilities of the research computer system in terms of providing a very effective interactive research tool for the digital processing of mesoscale analysis and space sensor data is described.

Hickey, J. S.↗

Design, analysis, and test verification of advanced encapsulation systems

Design sensitivities are established for the development of photovoltaic module criteria and the definition of needed research tasks. The program consists of three phases. In Phase I, analytical models were developed to perform optical, thermal, electrical, and structural analyses on candidate encapsulation systems. From these analyses several candidate systems will be selected for qualification testing during Phase II. Additionally, during Phase II, test specimens of various types will be constructed and tested to determine the validity of the analysis methodology developed in Phase I. In Phse III, a finalized optimum design based on knowledge gained in Phase I and II will be developed. All verification testing was completed during this period. Preliminary results and observations are discussed. Descriptions of the thermal, thermal structural, and structural deflection test setups are included.

Mardesich, N.↗

Analysis of a Multiprocessor Guidance Computer

The design of the next generation of spaceborne digital computers is described. It analyzes a possible multiprocessor computer configuration. For the analysis, a set of representative space computing tasks was abstracted from the Lunar Module Guidance Computer programs as executed during the lunar landing, from the Apollo program. This computer performs at this time about 24 concurrent functions, with iteration rates from 10 times per second to once every two seconds. These jobs were tabulated in a machine-independent form, and statistics of the overall job set were obtained. It was concluded, based on a comparison of simulation and Markov results, that the Markov process analysis is accurate in predicting overall trends and in configuration comparisons, but does not provide useful detailed information in specific situations. Using both types of analysis, it was determined that the job scheduling function is a critical one for efficiency of the multiprocessor. It is recommended that research into the area of automatic job scheduling be performed.

Maltach, E. G.↗

Results and Analysis from Space Suit Joint Torque Testing

A space suit's mobility is critical to an astronaut's ability to perform work efficiently. As mobility increases, the astronaut can perform tasks for longer durations with less fatigue. Mobility can be broken down into two parts: range of motion (ROM) and torque. These two measurements describe how the suit moves and how much force it takes to move. Two methods were chosen to define mobility requirements for the Constellation Space Suit Element (CSSE). One method focuses on range of motion and the second method centers on joint torque. A joint torque test was conducted to determine a baseline for current advanced space suit joint torques. This test utilized the following space suits: Extravehicular Mobility Unit (EMU), Advanced Crew Escape Suit (ACES), I-Suit, D-Suit, Enhanced Mobility (EM)- ACES, and Mark III (MK-III). Data was collected data from 16 different joint movements of each suit. The results were then reviewed and CSSE joint torque requirement values were selected. The focus of this paper is to discuss trends observed during data analysis.

Matty, Jennifer↗

An optimal control model approach to the design of compensators for simulator delay

The effects of display delay on pilot performance and workload and of the design of the filters to ameliorate these effects were investigated. The optimal control model for pilot/vehicle analysis was used both to determine the potential delay effects and to design the compensators. The model was applied to a simple roll tracking task and to a complex hover task. The results confirm that even small delays can degrade performance and impose a workload penalty. A time-domain compensator designed by using the optimal control model directly appears capable of providing extensive compensation for these effects even in multi-input, multi-output problems.

Baron, S.↗

SRNL Report on Vendor Solicitation and Selective Ion-Electrode Testing

Effective operation of the Hanford Tank Waste Treatment and Immobilization Plant (WTP) will require information collected from sampling and/or monitoring to maintain environmental compliance, product quality, and operating efficiency. The U.S. Department of Energy (DOE) – Office of River Protection (ORP) recognizes the potential long-term benefit of developing real-time, in-line monitoring (RTIM) at the WTP to improve the current strategy of collecting tens of thousands of samples and analyzing them. In-line monitoring can decrease processing time associated with waiting for sample analysis, reduce workers’ exposure to radiation and chemical hazards, decrease secondary waste volumes, potentially improve product quality, and provide production support and enhance overall operational control. The Assistant Manager, WTP chartered an Integrated Technical Team (ITT), which includes personnel from the Savannah River National Laboratory (SRNL), Bechtel National, Inc., and DOE-ORP, to evaluate the capability and potential benefits of replacing routine sample collection requirements with real-time, in-line monitoring. The initial focus of the ITT is the Direct Feed Low Activity Waste (DFLAW) Program. This work scope is being performed in multiple phases. Phase 1 is Requirements and Opportunities Analysis, Phase 2 is Applications and Benefits Determination, and Phase 3 is Qualification and Demonstration. Phase 1 included 6 tasks and was completed by SRNL in 2017. The tasks in Phase 1 were: (1) determining the functional requirements for determining analytes and properties of streams, (2) determining the technical basis for process control, (3) determining the sampling points within the Low Activity Waste (LAW) facility and Effluent Management Facility (EMF), (4) data quality and management, (5) process control challenges, and (6) preparing a Preliminary Analysis Plan. DOE-ORP was briefed on the findings from the Phase 1 tasks and requested that Phase 2 work focus on establishing a basis for a materials balance approach that minimized process sampling. The Phase 2 work scope contains tasks to evaluate a materials balance only approach as well as continuing scoping evaluations for instruments that could be used for RTIM. The Phase 2 work scope was completed by both SRNL and Pacific Northwest National Laboratory (PNNL). The tasks performed in Phase 2 were: 1. Overall program administration and technical oversight 2. Evaluation of a Material Balance Approach, a. Evaluation of uncertainty of this approach compared to uncertainty of current methods b. Evaluation of automating the material balance within the framework of existing control software, c. Development of the methodology to obtain and evaluate data during cold commissioning to support a material balance approach, and d. Development of a framework to utilize during presentation of the revised approach to stakeholders and regulators. 3. Screening Evaluations of Instruments to Supplement the Material Balance Approach, a. AP-105 melter condensate evaluations, and b. Screening testing with simulants. 4. Evaluation of the current DFLAW feed qualification program to identify analytes that could be eliminated, a. Inorganic analytes, b. Radionuclides, and c. Organic analytes. This report describes the results of Task 3b, Screening testing with simulants. The Savannah River National Laboratory requested demonstrations of commercially available analytical instruments by the vendors or laboratory demonstration. The techniques tested included: Raman spectroscopy, Infrared spectroscopy (IR), laser induced breakdown spectroscopy (LIBS), X-Ray Fluorescence Spectroscopy (XRF), and ion-selective electrochemical probes. Additionally, the instrumentation would need to be durable enough to withstand the environment of the plant, preferably with little to no maintenance. The insertion point of the instrument would be dependent upon the instrumentation.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Multi-attribute subjective evaluations of manual tracking tasks vs. objective performance of the human operator

A computational method to deal with the multidimensional nature of tracking and/or monitoring tasks is developed. Operator centered variables, including the operator's perception of the task, are considered. Matrix ratings are defined based on multidimensional scaling techniques and multivariate analysis. The method consists of two distinct steps: (1) to determine the mathematical space of subjective judgements of a certain individual (or group of evaluators) for a given set of tasks and experimental conditionings; and (2) to relate this space with respect to both the task variables and the objective performance criteria used. Results for a variety of second-order trackings with smoothed noise-driven inputs indicate that: (1) many of the internally perceived task variables form a nonorthogonal set; and (2) the structure of the subjective space varies among groups of individuals according to the degree of familiarity they have with such tasks.

Siapkaras, A.↗

The effects of motion and g-seat cues on pilot simulator performance of three piloting tasks

Data are presented that show the effects of motion system cues, g-seat cues, and pilot experience on pilot performance during takeoffs with engine failures, during in-flight precision turns, and during landings with wind shear. Eight groups of USAF pilots flew a simulated KC-135 using four different cueing systems. The basic cueing system was a fixed-base type (no-motion cueing) with visual cueing. The other three systems were produced by the presence of either a motion system or a g-seat, or both. Extensive statistical analysis of the data was performed and representative performance means were examined. These data show that the addition of motion system cueing results in significant improvement in pilot performance for all three tasks; however, the use of g-seat cueing, either alone or in conjunction with the motion system, provides little if any performance improvement for these tasks and for this aircraft type.

Showalter, T. W.↗

MapsTorch : automatic differentiation for X-ray fluorescence data analysis

X-ray fluorescence (XRF) is a popular spectroscopy technique for elemental analysis. Spectrum fitting and parameter tuning are at the core of XRF analysis and are conventionally manually intensive, especially for synchrotron experiments involving large amounts of diverse samples. This work introduces the automatic differentiation (AD) technique to XRF and an open-source package called MapsTorch. By transforming an analytical model of the XRF spectrum into a differentiable computation graph with AD, MapsTorch enables robust optimization of parameters and elemental intensities. We evaluate MapsTorch by conducting computational experiments on a large number of historical synchrotron XRF datasets and compare its performance with the currently practiced fitting tool NLopt. The results show that MapsTorch consistently achieves high-quality fits and often leads to better fitting quality than NLopt, particularly in tasks such as initial spectrum fitting and elemental intensity refinement. The robust performance of MapsTorch paves the way for developing automated and high-throughput XRF data analysis workflows to handle the increasing data volumes expected from next-generation synchrotron facilities.

X-ray fluorescence↗

Operational Analytics Studies for ATLAS Distributed Computing: Data Popularity Forecast and Utilization of the WLCG Centers

Operational analytics is the direction of research related to the analysis of the current state of computing processes and the prediction of future states in order to anticipate imbalances and take timely measures to stabilize a complex system. There are two relevant areas in ATLAS Distributed Computing that are currently the focus of studies: user physics analysis including the forecast of popularity of data samples among users, and evaluating WLCG centers for their readiness to process user analysis payloads. Studying these areas is challenging due to the complexity involved, as it requires a comprehensive understanding of numerous boundary conditions typically found in large-scale distributed computing infrastructures. Forecasts of data popularity are problematic without the categorization of user tasks by their types (data transformation or physics analysis), which do not always appear on the surface but may induce noise, which introduces significant distortions for predictive analysis. Evaluating the WLCG resources by their analysis workloads is also a challenging task as it is necessary to find a balance between the workload of the resource, its performance, the waiting time for jobs on it, as well as the volume of jobs that it processes. This is especially difficult in a heterogeneous computing environment, where legacy resources are used along with modern high-performance machines. We will look at these areas of research in detail and discuss what tools and methods are used in our work, demonstrating results already obtained.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Fuel Thermo-physical Characterization Project. Fiscal Year 2014 Final Report

The Office of Material Management and Minimization (M3) Reactor Conversion Fuel Thermo-Physical Characterization Project at Pacific Northwest National Laboratory (PNNL) was tasked with using PNNL facilities and processes to receive irradiated low enriched uranium–molybdenum (LEU-Mo) fuel plate samples and perform analysis in support of the M3 Reactor Conversion Program. This work is in support of the M3 Reactor Conversion Fuel Development Pillar that is managed by Idaho National Laboratory. The primary research scope was to determine the thermo-physical properties as a function of temperature and burnup. Work conducted in Fiscal Year (FY) 2014 complemented measurements performed in FY 2013 on four additional irradiated LEU-Mo fuel plate samples. Specifically, the work in FY 2014 investigated the influence of different processing methods on thermal property behavior, the absence of aluminum alloy cladding on thermal property behavior for additional model validation, and the influence of higher operating surface heat flux / more aggressive irradiation conditions on thermal property behavior. The model developed in FY 2013 and refined in FY 2014 to extract thermal properties of the U-Mo alloy from the measurements conducted on an integral fuel plate sample (i.e., U-Mo alloy with a thin Zr coating and clad in AA6061) continues to perform very well. Measurements conducted in FY 2014 on samples irradiated under similar conditions compare well to measurements performed in FY 2013. In general, there is no gross influence of fabrication method on thermal property behavior, although the difference in LEU-Mo foil microstructure does have a noticeable influence on recrystallization of grains during irradiation. Samples irradiated under more aggressive irradiation conditions, e.g., higher surface heat flux, revealed lower thermal conductivity when compared to samples irradiated at moderate surface heat fluxes, with the exception of one sample. This report documents thermal property measurements conducted in FY 2014 and compares results to values obtained from literature and measurements performed in FY 2013, where applicable, along with appropriate discussion.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Aluminum Spent Fuel Performance in Dry Storage Task 4 Aluminum Oxide Sampling of ATR Dry Stored Fuel

Milestone report on sampling of long-term dry-stored ATR spent fuel elements. It describes tooling, sample acquisition methods and analysis of the aluminum oxide samples by scanning electron microscopy, thermogravimetric analysis, X-ray diffraction and transmission electron microscopy. The observations provide input to projections on controls necessary for maintaining the integrity of the fuel during extended interim storage.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Real-Time Optimization Workflow Status Update

Economically optimal and safe operation of integrated energy systems (IES) requires optimization at many different time scales. A real-time optimization (RTO) workflow will attempt to maximize revenue and minimize operational costs on a time scale of minutes to hours. Such a workflow requires the use of a digital twin (DT), which is a virtual representation of a physical system. The DT is updated using real-time data from the physical system, and serves as a model in an optimization framework. The optimization results are then sent back to the physical system to complete the loop. This report details the progress made in developing building blocks for a DT/RTO framework. The Risk Analysis Virtual Environment (RAVEN) platform within the Framework for Optimization of Resources and Economics (FORCE) tool suite can perform many of the tasks required for building a DT and performing RTO. The first item of this report details RAVEN enhancements that enable RAVEN workflows to be run in various environments. Data communication between the physical system and its DT is essential for successful RTO. This includes preprocessing real-time data, loading data into a data warehouse, and querying the stored data. The second section of this report describes the progress made in implementing an adapter in Python in order for Deep Lynx to handle the data communication. Typical dispatch optimization frameworks are built on linear programming (LP). The prototype RTO workflow developed in this report uses an LP problem as a part of a receding-horizon- or economic model predictive control (EMPC) based optimization. The third section of this report details the framework of an RTO workflow in which the system consists of a simple electrical storage device. A DT can be built from a reduced-order model (ROM). Integrating a ROM into a typical LP optimization framework has been challenging because most optimization packages require the user to write algebraic expressions for the system model. The final section of this report shows how an externally built RAVEN ROM can be integrated in an RTO framework by using the Python package Pyomo. This demonstrates the RTO workflow capability from a software-only perspective and is an important step in demonstrating the capability to implement an RTO workflow for a physical system.

97 MATHEMATICS AND COMPUTING↗