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At least 19 records

Dynamic instructions for Lock-out Tag-out

Lock-out tag-out (LOTO) instructions protect personnel from un-expected re-energization or start-up of equipment that is under maintenance. Even though there is rigorous training associated with LOTO activities, inci-dents still occur. Idaho National Laboratory is researching and developing dynamic LOTO instructions, which supports automatic place keeping, per-sonnel working on multiple instructions, and multiple work groups complet-ing the same instructions. Researchers identified user needs through subject matter expert interviews, observations, and classroom training. Failing to identify potential hazards during LOTO can cause injury or death to person-nel. Dynamic instructions can provide planning, incorporate supplemental documentation into the instruction, and improve instruction compliance. Combining these functions may lead to clearer, more applicable instructions which addresses the reason for compliance issues with current paper-based procedures.

99 GENERAL AND MISCELLANEOUS↗

Dynamic Instructions for Lock-out Tag-out

Lock-out tag-out (LOTO) instructions protect personnel from unex-pected re-energization or start-up of equipment that is under maintenance. Even though there is rigorous training associated with LOTO activities, incidents still occur. Idaho National Laboratory is researching and developing dynamic LOTO instructions, which supports automatic place keeping, personnel working on mul-tiple instructions, and multiple work groups completing the same instructions. Researchers identified user needs through subject matter expert interviews, ob-servations, and classroom training. Failing to identify potential hazards during LOTO can cause injury or death to personnel. Dynamic instructions help to guide the user seamlessly through the instructions. Combining planning and record keeping may lead to clearer, more applicable instructions which addresses the reason for compliance issues with current paper-based procedures.

99 - GENERAL AND MISCELLANEOUS↗

Dynamic Instructions for Nuclear Power Plant Field Workers

Most tasks conducted at a nuclear power plant are guided by a procedure in one way or another. Some tasks must be conducted by strictly adhering to the prescribed steps, while other tasks use the procedures as a reference guide. Traditionally, the procedure process in the nuclear industry has been paper heavy. In recent years however, the nuclear industry has considered adopting more dynamic solutions to improve the efficiency of their work management process, advance human and system performance, as well as reduce the cost of handling paper copies of documentation. As a first step, many nuclear utilities in the U.S. deployed solutions that electronically route the documents through the review and approval processes and where the worker in the field uses an electronic copy of the instruction or procedure on a handheld device. These electronic copies are very similar to the format of the paper instruction but do have some additional capabilities to capture recorded input and notes.

47 OTHER INSTRUMENTATION↗

The use of computers for instruction in fluid dynamics

Applications for computers which improve instruction in fluid dynamics are examined. Computers can be used to illustrate three-dimensional flow fields and simple fluid dynamics mechanisms, to solve fluid dynamics problems, and for electronic sketching. The usefulness of computer applications is limited by computer speed, memory, and software and the clarity and field of view of the projected display. Proposed advances in personal computers which will address these limitations are discussed. Long range applications for computers in education are considered.

Watson, Val↗

Dynamic Procedures Writer's Manual

This presentation provides the background information and introduction to a workshop with the goal to discuss a proposed standard for how to write dynamic procedures. The development of the proposed standard was conducted under the INL-led (Johanna Oxstrand) Work Digitalization Initiative. Mitch Burke (NextAxiom) and Steve McCord (Procedure Solution Management) are the authors of the proposed standard. They will lead the actual workshop.

47 OTHER INSTRUMENTATION↗

The effects of type of knowledge upon human problem solving in a process control task

The question of what the operator of a dynamic system needs to know was investigated in an experiment using PLANT, a simulation of a generic dynamic production process. Knowledge of PLANT was manipulated via different types of instruction, so that four different groups were created: (1) minimal instructions only; (2) minimal instructions and guidelines for operation (procedures); (3) minimal instructions and dynamic relationships (principles); and (4) minimal instructions, and procedures, and principles. Subjects controlled PLANT in a variety of situations which required maintaining production while also diagnosing familiar and unfamiliar failures. Despite the fact that these manipulations resulted in differences in subjects' Knowledge, as assessed via a written test at the end of the experiment, instructions had no effect upon achievement of the primary goal of production, or upon subjects' ability to diagnose unfamiliar failures. However, those groups receiving procedures controlled the system in a more stable manner. Possible reasons for the failure to find an effect of principles are presented, and the implications of these results for operator training and aiding are discussed.

Morris, N. M.↗

Reaction processes at step edges on S-decorated Cu(111) and Ag(111) surfaces: MD analysis utilizing machine learning derived potentials

We report a variety of complexation, reconstruction, and sulfide formation processes can occur at step edges on the {111} surfaces of coinage metals (M) in the presence of adsorbed S under ultra-high vacuum conditions. Given the cooperative many-atom nature of these reaction processes, Molecular Dynamics (MD) simulation of the associated dynamics is instructive. However, only quite restricted Density Functional Theory (DFT)-level ab initio MD is viable. Thus, for M = Ag and Cu, we instead utilize the DeePMD framework to develop machine-learning derived potentials, retaining near-DFT accuracy for the M–S systems, which should have broad applicability. These potentials are validated by comparison with DFT predictions for various key quantities related to the energetics of S on M(111) surfaces. The potentials are then utilized to perform extensive MD simulations elucidating the above diverse restructuring and reaction processes at step edges. Key observations from MD simulations include the formation of small metal–sulfur complexes, especially MS 2 ; development of a local reconstruction at A-steps featuring an S-decorated {100} motif; and 3D sulfide formation. Additional analysis yields further information on the kinetics for metal–sulfur complex formation, where these complexes can strongly enhance surface mass transport, and on the propensity for sulfide formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

User's instructions for the Guyton circulatory dynamics model using the Univac 1110 batch and demand processing (with graphic capabilities)

The model presents a systems analysis of a human circulatory regulation based almost entirely on experimental data and cumulative present knowledge of the many facets of the circulatory system. The model itself consists of eighteen different major systems that enter into circulatory control. These systems are grouped into sixteen distinct subprograms that are melded together to form the total model. The model develops circulatory and fluid regulation in a simultaneous manner. Thus, the effects of hormonal and autonomic control, electrolyte regulation, and excretory dynamics are all important and are all included in the model.

Archer, G. T.↗

Smart Planning Support for Nuclear Power Plant Work Planners

Operation and Maintenance costs of a nuclear power plant account for 60% of overall plant costs due to the nuclear industry?s risk-adverse culture (World Nuclear Association, 2020). The industry relies on highly conservative estimates to avoid risk and brute force reactions to manage the unexpected and keep a plant running safely. This approach has kept plants operating safer than any other power source available over the last six decades (Ritchie, 2020). However, these conservative methods have cost the nuclear industry in market competitiveness. The solution? Transform the conservative approaches to accurate, efficient, and still safe data-driven approaches that leverage advanced technologies available in the digital age of operation. This project endeavored to identify two key aspects to successfully incorporate historical work execution data. First, where in the work management process is that information most pertinent? Next, what variables are key to informing the best strategy for organizing the upcoming work? The Smart Planner uses data collected by dynamic work instructions to provide a basis for suggesting requirements of similar, upcoming work packages. Further, it curbs inefficiencies of the work management process by analyzing the likelihood of discovery work, offering suggestions to build a contingency package. All this taking place as the work planner builds work packages that meet the predetermined scope of work to be performed.

99 GENERAL AND MISCELLANEOUS↗

Digitalization mapping and assessment process supporting ION strategic transformation activities

The existing fleet of commercial nuclear power plants (NPPs) are an important asset in the nation’s portfolio of electrical generating resources. Their continued safe and reliable operation are critical to providing a large source of carbon-free electricity to power the nation’s economy. The United States Department of Energy’s (DOE) Light Water Reactor Sustainability (LWRS) Program develops the scientific bases, methods, and tools, for the continued safe and economical operation of the nation's commercial NPPs. The Plant Modernization Pathway within LWRS Program focuses on providing guidance to industry on the full-scale implementation of modernization solutions for NPPs that significantly reduce the technical and financial risks associated with modernization. This research is focused on helping the nuclear industry understand how to digitize and digitalize their NPPs so that they can design their modernization solutions to be scalable, sustainable, and integrated both laterally and horizontally within their organization. That is, this research creates a digital transformation in NPPs by reshaping cultural mindsets and by identifying business efficiencies. In partnership with industry, and using four previously established guiding principles for digitalization, this research supported NPP modernization through assessing readiness for digitalization as a means to achieve integrated operations for nuclear. Specifically, this research created an assessment to review an entire organization’s work processes to gather information about the digitalization health of the plant. The assessment tools were administered to plant employees, and the results were used to develop a digitalization plan. The survey assessment identified the optimal candidate processes that would most benefit from a digitalization initiative which were revealed through analytical frameworks. One analysis calculated mean digitalization health indicator scores for all endorsed activities which allowed the researchers to rank and color code the results for easy identification. Individual health indicator scores are also provided, should our industry partner wish to understand these findings according to their own organizational priorities, business considerations and desired end-state. The results were also analyzed from the perspective that organizations are comprised of different types of innovators (e.g., generators, optimizers, conceptualizers, and implementers), which differentially affects the organization’s ability to comprehend and adapt to change (i.e., opportunities to innovate). Understanding the relative composition of innovator types at an NPP allows them to gather insights into the strengths and weaknesses they have in innovating how work is performed. For the utility that partnered with this research team, the results showed that implementers make up the largest portion of respondents and conceptualizers the smallest portion. Knowing the proportion of innovator types gave this organization insights on how they can effectively implement their innovation solutions. Additionally, the results were analyzed from a technical, economic, and risk perspective to identify and quantify work reduction opportunities (WROs). Recognizing that not all cost-saving opportunities are the same, a Technical, Economic and Risk Assessment (TERA) was performed to evaluate WROs to identify areas of greatest potential and lowest risk. The key results from TERA included a digitalization opportunity score for each activity, and a calculation of potential cost savings. These two outputs formed the bases for calculating a priority index and rank for the activities/processes assessed. From the prioritization calculations, TERA can then help the utility 1) decide what digitalization priorities to invest money in implementing and then 2) calculates how much should be invested in the digitalization initiatives selected to achieve cost savings and/or an acceptable return on investment. Last, onsite interviews revealed several inefficiencies in the standard work processes that occur cross-departmentally that are due to the absence of digitized and digitalized processes. Examples of these include time spent scanning paper documents and then uploading the documents electronically, obtaining signatures, and searching for desired information. This represents a digital but not digitalized process. Over 15 opportunities to improve work processes were identified through this multi-method digitalization assessment. The various analytical assessments used (e.g., TERA, digitalization health indicator scores), as well as discussions with the utility partner, corroborated that all the opportunities identified had a strong potential to make work processes more efficient and to improve overall performance of the NPP.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

SimNet: Accurate and High-Performance Computer Architecture Simulation using Deep Learning

While cycle-accurate simulators are essential tools for architecture research, design, and development, their practicality is limited by an extremely long time-to-solution for realistic applications under investigation. This work describes a concerted effort, where machine learning (ML) is used to accelerate microarchitecture simulation. First, an ML-based instruction latency prediction framework that accounts for both static instruction properties and dynamic processor states is constructed. Then, a GPU-accelerated parallel simulator is implemented based on the proposed instruction latency predictor, and its simulation accuracy and throughput are validated and evaluated against a state-of-the-art simulator. Leveraging modern GPUs, the ML-based simulator outperforms traditional CPU-based simulators significantly.

97 MATHEMATICS AND COMPUTING↗

Methodology and Results of the Near-Earth Object (NEO) Human Space Flight (HSF) Accessible Targets Study (NHATS)

Near-Earth Asteroids (NEAs) have been identified by the current administration as potential destinations for human explorers during the mid-2020s. While the close proximity of these objects' orbits to Earth's orbit creates a risk of highly damaging or catastrophic impacts, it also makes some of these objects particularly accessible to spacecraft departing Earth, and this presents unique opportunities for solar system science and humanity's first ventures beyond cislunar space. Planning such ambitious missions first requires the selection of potentially accessible targets from the growing population of nearly 7,800 NEAs. To accomplish this, NASA is conducting the Near-Earth Object (NEO) Human Space Flight (HSF) Accessible Targets Study (NHATS). Phase I of the NHATS was executed during September of 2010, and Phase II was completed by early March of 2011. The study is ongoing because previously undetected NEAs are being discovered constantly, which has motivated an effort to automate the analysis algorithms in order to provide continuous monitoring of NEA accessibility. The NHATS analysis process consists of a trajectory filter and a minimum maximum estimated size criterion. The trajectory filter employs the method of embedded trajectory grids to compute all possible ballistic round-trip mission trajectories to every NEA in the Jet Propulsion Laboratory (JPL) Small-Body Database (SBDB) and stores all solutions that satisfy the trajectory filter criteria. An NEA must offer at least one qualifying trajectory solution to pass the trajectory filter. The Phase II NHATS filter criteria were purposely chosen to be highly inclusive, requiring Earth departure date between January 1st, 2015 and December 31st, 2040, total round-trip flight time <= 450 days, stay time at the NEA >= 8 days, Earth departure C(sub 3) energy <= 60 km(exp 2)/s(exp 2), total mission delta-v <= 12 km/s (including an Earth departure maneuver from a 400 km altitude circular parking orbit), and a maximum atmospheric re-entry speed of 12 km/s. After determining which NEAs offer at least one trajectory solution meeting the criteria, the estimated size constraint is then imposed whereby those NEAs may only be considered NHATS- qualifying NEAs if their maximum estimated size is >= 30 m. This corresponds to an absolute magnitude H <= 26.5 with an assumed albedo p = 0:05. The following is a brief high-level summary of the Phase II study results. Of the 7,665 NEAs in the SBDB as of February 3rd, 2011, 765 NEAs passed the trajectory filter and yielded a total of 79,157,604 trajectory solutions. The trajectory solutions for each NEA are post-processed into Pork Chop Contour (PCC) plots which show total mission delta-v as a function of Earth departure date and total mission duration. Although the PCC plots necessarily compress a very multi-dimensional design space into a two-dimensional plot, they permit rapid assessment of the breadth and quality of an NEA's available Earth departure season and clearly indicate the regions of the trajectory design space which warrant further analysis and optimization. The PCC plot for the NEA with the greatest number of NHATS-qualifying trajectory solutions, 2000 SG-344, is shown. Of the 765 NEAs which passed the Phase II trajectory filter, a total of 590 NEAs also satisfied the further constraint of maximum estimated size >= 30 m. The distributions of osculating heliocentric orbital semi-major axis (a), eccentricity (e), and inclination (i), for those 590 NEAs are shown. Note that the semi-latus rectum used is equal to alpha (1-e(exp 2)). To further our understanding of round-trip trajectory accessibility dynamics, it is instructive to examine the distribution of the NHATS-Qualifying NEAs according to orbit classification. NEAs are grouped into four orbit families: Atiras (aphelion < 0.983 AU), Atens (aphelion > 0.983 AU, alpha < 1.0 AU), Apollos (perihelion < 1.017 AU, alpha > 1.0 AU), and Amors (1.017 < perihelion < 1.3 AU). Of the 765 NEAhich satisfied the NHATS trajectory criteria, none are Atiras, 193 are Atens (31% of known Atens), 456 are Apollos (11% of known Apollos), and 116 are Amors (4% of known Amors). While Apollos comprise 60% of the NEAs which pass the NHATS trajectory filter and Atens comprise only 25%, the percentages according to orbit family are perhaps more relevant. Note that only 11% of known Apollos passed the trajectory filter while 31% of known Atens passed. These simple statistics alone strongly suggest that Aten orbits possess features which tend to enhance their round-trip trajectory accessibility as compared to Apollos or Amors. This is significant because Atens' orbits cause them to spend considerable time in Earth's daytime sky, making them difficult to discover and track using ground-based observing assets. In this paper we will detail the NHATS analysis algorithms, present and analyze all NHATS results to date, and discuss aspects of HSF mission architecture design for future NEA missions.

Barbee, Brent↗

Teachers’ Beliefs and Their Influence on Math Instructions for Gifted English Learners

The dynamic interplay between teachers’ beliefs and practices significantly impact the quality of instruction and the trajectory of talent development in young students. This case study explores the beliefs and practices of two elementary teachers instructing gifted ELs in mathematics. The constant comparison method was used to analyze data collected from classroom observations, semi-structured interviews, and field notes. Three factors were found to affect the (in)consistency between teachers’ expressed beliefs and observed practices: compatibility among core and peripheral beliefs, knowledge about evidence-based practices, and classroom management skills. Students exhibit higher levels of participation, communication, and engagement in critical thinking skills when their teacher embraces constructive perspectives in teaching mathematics, demonstrates pedagogical expertise, and employs a proactive classroom management approach. Conversely, students encounter restricted opportunities to independently construct their own understanding of mathematics when their teacher holds maladaptive beliefs about teaching mathematics, has limited knowledge of evidence-based practices, and has an authoritarian classroom management style. These findings underscore the need for a new approach to professional development (PD) that encourages teachers to critically examine the connection between their beliefs and instructional practices and their impact on the student’s mathematical talent development.

Yang, Jenny (ORCID:0000000296905466)↗

Use of a personal computer for dynamical engineering illustrations in a classroom and over an instructional TV network

A personal computer has been used to illustrate physical phenomena and problem solution techniques in engineering classes. According to student evaluations, instruction of concepts was greatly improved through the use of these illustrations. This paper describes the class of phenomena that can be effectively illustrated, the techniques used to create these illustrations, and the techniques used to display the illustrations in regular classrooms and over an instructional TV network. The features of a personal computer required to apply these techniques are listed. The capabilities of some present personal computers are discussed and a forecast of the capabilities of future personal computers is presented.

Watson, V. R.↗

An ICAI architecture for troubleshooting in complex, dynamic systems

Ahab, an intelligent computer-aided instruction (ICAI) program, illustrates an architecture for simulator-based ICAI programs to teach troubleshooting in complex, dynamic environments. The architecture posits three elements of a computerized instructor: the task model, the student model, and the instructional module. The task model is a prescriptive model of expert performance that uses symptomatic and topographic search strategies to provide students with directed problem-solving aids. The student model is a descriptive model of student performance in the context of the task model. This student model compares the student and task models, critiques student performance, and provides interactive performance feedback. The instructional module coordinates information presented by the instructional media, the task model, and the student model so that each student receives individualized instruction. Concept and metaconcept knowledge that supports these elements is contained in frames and production rules, respectively. The results of an experimental evaluation are discussed. They support the hypothesis that training with an adaptive online system built using the Ahab architecture produces better performance than training using simulator practice alone, at least with unfamiliar problems. It is not sufficient to develop an expert strategy and present it to students using offline materials. The training is most effective if it adapts to individual student needs.

Fath, Janet L.↗

Towards generic memory forensic framework for programmable logic controllers

A Programmable Logic Controller (PLC) is a microprocessor-based controller that is used to automate physical processes in critical infrastructure and various other industries and manufacturing sectors. Initially, PLCs were completely isolated from the Internet, and cyber security was not incorporated at the time of development. The introduction of industry 4.0 and the evolution of ICS systems to communicate over public IP addresses from the Internet enhanced productivity and efficiency, but Internet connectivity exposed the systems and their vulnerabilities, which led to an increase in cyber attacks. When a system is sabotaged/compromised, security analysts need to get to the root cause of the attack as quickly as possible to recover the system. To do so, memory forensic analysis is critical to provide a unique insight into the run-time memory activities and extract a reliable source of evidence. In this paper, we analyze the memory structure of the Schneider Electric Modicon M221 PLC. To build a memory profile, we reverse engineer the communication protocol and conduct differential analysis to gain knowledge about the structure of the memory and the low-level representation of control logic instructions. We then identify dynamic and static memory regions by modifying different project fields and conducting differential analysis, which allows us to identify boundaries of critical memory structures and extract important forensic artifacts that can be found in the memory. The Python implementation of the memory profile can help reduce the time and effort required for manual analysis in case of cyber incident or system failure.

97 MATHEMATICS AND COMPUTING↗

ARETE: Accurate Error Assessment via Machine Learning-Guided Dynamic-Timing Analysis

Nanometer circuits are increasingly prone to timing errors, escalating the need for fault injection frameworks to accurately evaluate their impact on applications. Here in this paper, we propose ARETE, a novel cross-layer, fault-injection framework that combines dynamic-binary instrumentation with machine learning-guided dynamic-timing analysis. ARETE enables accurate fault-injection into any application by estimating the location of the injecting errors via dynamic-timing analysis. To accelerate fault-injection, we develop a novel, data-aware, machine learning-based mechanism that dynamically pre-selects the error-prone instructions and limits the application of the costly dynamic-timing analysis only to them. To evaluate ARETE's accuracy, our fully automated toolflow is configured to support fault-injection based on detailed post-layout gate-level simulations as well as via existing workload-agnostic error models. Our results for various workloads, including an autonomous-driving library, show that the location and time of injected errors performed by ARETE, is 89.9% consistent with fault-injection based on full gate-level simulation. On average, ARETE executes 84.6x faster than gate-level simulation and at a cost of 3.4% loss in the program output quality estimation. When compared to the existing statistical fault-injection tools that are based on workload-agnostic error models, ARETE improves the accuracy of fault-injection rate and output quality estimation by 143.9% and 40.4% on average, respectively.

97 MATHEMATICS AND COMPUTING↗

Cooperative intelligent robotics in space III; Proceedings of the Meeting, Boston, MA, Nov. 16-18, 1992

The present volume on cooperative intelligent robotics in space discusses sensing and perception, Space Station Freedom robotics, cooperative human/intelligent robot teams, and intelligent space robotics. Attention is given to space robotics reasoning and control, ground-based space applications, intelligent space robotics architectures, free-flying orbital space robotics, and cooperative intelligent robotics in space exploration. Topics addressed include proportional proximity sensing for telerobots using coherent lasar radar, ground operation of the mobile servicing system on Space Station Freedom, teleprogramming a cooperative space robotic workcell for space stations, and knowledge-based task planning for the special-purpose dextrous manipulator. Also discussed are dimensions of complexity in learning from interactive instruction, an overview of the dynamic predictive architecture for robotic assistants, recent developments at the Goddard engineering testbed, and parallel fault-tolerant robot control.

Erickson, Jon D.↗