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At least 19 records

BioWatch Sample Management System (SMS) Field Operator Guide

The BioWatch Sample Management System is software developed by Los Alamos National Laboratory to support the Department of Homeland Security BioWatch program. Field Operators use the software to keep track of samples and to provide information on the sample management process to other users and software programs within BioWatch. The information tracked about a sample includes the date and time the filter media is assembled in a filter holder, deployed to the field, placed in and removed from a collector, and received from the field, and identifies who performs each task. Field Operators can also use the software to prepare and print forms to document the chain-of-custody transfer of the samples. The BioWatch SMS Field Operator Guide provides easy-to-understand procedures for each task a Field Operator performs. This guide gives basic information about using the computer and other equipment, instructions about checking and editing data, and provides reference information, including appendices of error messages and solutions, words used interchangeably, and safety warnings plus a glossary and an index.

99 GENERAL AND MISCELLANEOUS↗

Irreducibility of the set of field operators in NC QFT

Irreducibility of the set of quantum field operators has been proved in noncommutative quantum field theory in the general case when time does not commute with spatial variables.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

An estimate of the NO(x) production rate in electrified clouds based on NO observations from the GTE/CITE 1 fall 1983 field operation

During the NASA GTE/CITE 1 fall 1983 airborne field operation the NASA Convair 990 penetrated the anvils of two active cumulonimbus clouds. While NO levels outside the anvils averaged about 20 parts per trillion per volume (pptv), the average NO inside the anvils was about 440 pptv. Extrapolation of this observation along with data on the amount of air typically advected out of cumulonimbus clouds and the total number of thunderclouds occurring over the globe at any moment, implies a rate of nitrogen fixation in electrified clouds of about 7 x 10 to the 6th trillion/yr. Although the data base used to make this estimate is quite limited, the approach differs from that used in previous studies of the global production of nitrogen oxides by lightning, and thus represents an independent assessment of the role of electrified clouds in the atmospheric nitrogen oxide budget.

Chameides, W. L.↗

Mod-2 wind turbine field operations experience

The Mod-2 wind turbine is now in a 2-year research/experimental operations phase which offers a unique opportunity to study the effects of single and multiple wind turbines interacting with each other, the power grid, and the environment. This paper addresses the field operations and research testing experienced at the Mod-2 Cluster Goodnoe Hills Research Test Site near Goldendale, WA. Field operation, both routine and nonroutine, are discussed as well as the role of the participating utility. Technical areas discussed pertain to system performance and loads. Specific research tests relating to acoustics, TV interference, and wake effects are also discussed.

Gordon, L. H.↗

Global Positioning System Simulator Field Operational Procedures

Global Positioning System (GPS) simulation is an important activity in the development or qualification of GPS signal receivers for space flight. Because a GPS simulator is a critical resource it is highly desirable to develop a set of field operational procedures to supplement the basic procedures provided by most simulator vendors. Validated field procedures allow better utilization of the GPS simulator in the development of new test scenarios and simulation operations. These procedures expedite simulation scenario development while resulting in scenarios that are more representative of the true design, as well as enabling construction of more complex simulations than previously possible, for example, spacecraft maneuvers. One difficulty in the development of a simulation scenario is specifying various modes of test vehicle motion and associated maneuvers requiring that a user specify some (but not all) of a few closely related simulation parameters. Currently this can only be done by trial and error. A stand-alone procedure that implements the simulator maneuver motion equations and solves for the motion profile transient times, jerk and acceleration would be of considerable value. Another procedure would permit the specification of some configuration parameters that would determine the simulated GPS signal composition. The resulting signal navigation message, for example, would force the receiver under test to use only the intended C-code component of the simulated GPS signal. A representative class of GPS simulation-related field operational procedures is described in this paper. These procedures were developed and used in support of GPS integration and testing for many successful spacecraft missions such as SAC-A, EO-1, AMSAT, VCL, SeaStar, sounding rockets, and by using the industry standard Spirent Global Simulation Systems Incorporated (GSSI) STR series simulators.

Kizhner, Semion↗

The Automation of Field Operations and Services (AFOS) within the NWS and its impact on aviation meteorology

Future program efforts in Automation of Field Operations and Services (AFOS) are presented. The AFOS concept involves extensive use of minicomputers, video display, and rapid communication to aid field personnel in their daily activities. Some of the predominant characteristics of AFOS are: (1) communications will be consolidated and streamlined, (2) the system is modular in structure, (3) it is not subject to catastrophic failure, (4) it can be implemented in phases adaptable to changing conditions and requirements. Aviation forecast products now available and future products are discussed.

Gross, E. M.↗

Requirements for Computer Based-Procedures for Nuclear Power Plant Field Operators Results from a Qualitative Study

Although computer-based procedures (CBPs) have been investigated as a way to enhance operator performance on procedural tasks in the nuclear industry for almost thirty years, they are not currently widely deployed at United States utilities. One of the barriers to the wide scale deployment of CBPs is the lack of operational experience with CBPs that could serve as a sound basis for justifying the use of CBPs for nuclear utilities. Utilities are hesitant to adopt CBPs because of concern over potential costs of implementation, and concern over regulatory approval. Regulators require a sound technical basis for the use of any procedure at the utilities; without operating experience to support the use CBPs, it is difficult to establish such a technical basis. In an effort to begin the process of developing a technical basis for CBPs, researchers at Idaho National Laboratory are partnering with industry to explore CBPs with the objective of defining requirements for CBPs and developing an industry-wide vision and path forward for the use of CBPs. This paper describes the results from a qualitative study aimed at defining requirements for CBPs to be used by field operators and maintenance technicians.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Survey: Automated Field Operations and Services (AFOS)

The National Weather Service (NWS) is currently implementing a program for improving operations through automation of routine functions, improved communications capability, and improved management and presentation of data. The program, designated as Automation of Field Operations and Services (AFOS), uses high-speed data circuits, minicomputers, and dynamic display devices to rapidly collect, disseminate, and present data to forecasters and users on both a broadcast and a request basis. The initial system will be configured to serve facilities within the continental United States, Alaska, Hawaii, and Puerto Rico, with eventual expansion to provide international capability. This report discusses AFOS users, functions, and network and site configurations. The sections discuss current and future capability and workload in terms of the 10 data systems elements designated by NASA.

Source record↗

Sequim Bay Underwater UXO Prototype Demonstration Site: Field Operations Summary, 2020

This report provides a summary of Pacific Northwest National Laboratory’s (PNNL’s) activities to initiate Phase II development of the Sequim Bay Underwater UXO Prototype demonstration site (MR-2735) in 2020. Testbed development and field operations were conducted by PNNL’s Coastal and Marine Research Laboratory (MCRL) in support of the Strategic Environmental Research and Development Program (SERDP) and Environmental Security Technology Certification Program (ESTCP) underwater Munitions Response (MR) program. A series of standardized underwater unexploded ordnance (UXO) demonstration sites (“testbeds”) are being developed by SERDP/ESTCP to test, evaluate, and demonstrate technologies that can detect, geolocate, and classify proud and buried munitions in 0–35 m water depths. As a prototype demonstration site, Sequim Bay is a semi-enclosed marine waterbody containing sand and mud sediments with minimal clutter in 5–30 m water depths. MCRL is located at the entrance to Sequim Bay, where it provides operational, logistical, and facilities support for testbed activities.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Optimization of Water-Alternating-CO2 Injection Field Operations Using a Machine-Learning-Assisted Workflow

Summary This paper will present a robust workflow to address multiobjective optimization (MOO) of carbon dioxide (CO2)-enhanced oil recovery (EOR)-sequestration projects with a large number of operational control parameters. Farnsworth unit (FWU) field, a mature oil reservoir undergoing CO2 alternating water injection (CO2-WAG) EOR, will be used as a field case to validate the proposed optimization protocol. The expected outcome of this work would be a repository of Pareto-optimal solutions of multiple objective functions, including oil recovery, carbon storage volume, and project economics. FWU’s numerical model is used to demonstrate the proposed optimization workflow. Because using MOO requires computationally intensive procedures, machine-learning-based proxies are introduced to substitute for the high-fidelity model, thus reducing the total computation overhead. The vector machine regression combined with the Gaussian kernel (Gaussian-SVR) is used to construct proxies. An iterative self-adjusting process prepares the training knowledge base to develop robust proxies and minimizes computational time. The proxies’ hyperparameters will be optimally designed using Bayesian optimization to achieve better generalization performance. Trained proxies will be coupled with multiobjective particle swarm Optimization (MOPSO) protocol to construct the Pareto-front solution repository. The outcomes of this workflow will be a repository containing Pareto-optimal solutions of multiple objectives considered in the CO2-WAG project. The proposed optimization workflow will be compared with another established methodology using a multilayer neural network (MLNN) to validate its feasibility in handling MOO with a large number of parameters to control. Optimization parameters used include operational variables that might be used to control the CO2-WAG process, such as the duration of the water/gas injection period, producer bottomhole pressure (BHP) control, and water injection rate of each well included in the numerical model. It is proved that the workflow coupling Gaussian-SVR proxies and the iterative self-adjusting protocol is more computationally efficient. The MOO process is made more rapid by squeezing the size of the required training knowledge base while maintaining the high accuracy of the optimized results. The outcomes of the optimization study show promising results in successfully establishing the solution repository considering multiple objective functions. Results are also verified by validating the Pareto fronts with simulation results using obtained optimized control parameters. The outcome from this work could provide field operators an opportunity to design a CO2-WAG project using as many inputs as possible from the reservoir models. The proposed work introduces a novel concept that couples Gaussian-SVR proxies with a self-adjusting protocol to increase the computational efficiency of the proposed workflow and to guarantee the high accuracy of the obtained optimized results. More importantly, the workflow can optimize a large number of control parameters used in a complex CO2-WAG process, which greatly extends its utility in solving large-scale MOO problems in various projects with similar desired outcomes.

Energy & Fuels↗

Mod-2 wind turbine field operations experiment

The three-machine, 7.5 MW Goodnoe Hills located near Goldendale, Washington and is now in a research/experimental operations phase that offers a unique opportunity to study the effects of single and multiple wind turbines interacting with each other, the power grid; and the environment. Following a brief description of the turbine and project history, this paper addresses major problem areas and research and development test results. Field operations, both routine and nonroutine, are discussed. Routine operation to date has produced over 13,379,000 KWh of electrical energy during 11,064 hr of rotation. Nonroutine operation includes suspended activities caused by a crack in the low speed shaft that necessitated a redesign and reinstallation of this assembly on all three turbines. With the world's largest cluster back in full operation, two of the turbines will be operated over the next years to determine their value as energy producer. The third unit will be used primarily for conducting research tests requiring configuration changes to better understand the wind turbine technology. Technical areas summarized pertain to system performance and enhancements. Specific research tests relating to acoustics, TV interference, and wake effects conclude the paper.

Gordon, L. H.↗

Reinforcement Learning-Based Oscillation Dampening: Scaling Up Single-Agent Reinforcement Learning Algorithms to a 100-Autonomous-Vehicle Highway Field Operational Test

In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smooth traffic flow in history as of 2023, uncovering the challenges and breakthroughs that come with developing RL controllers for automated vehicles. We delve into the fundamental concepts behind RL algorithms and their application in the context of self-driving cars, discussing the developmental process from simulation to deployment in detail, from designing simulators to reward function shaping. We present the results in both simulation and deployment, discussing the flow-smoothing benefits of the RL controller. From understanding the basics of Markov decision processes to exploring advanced techniques such as deep RL, our article offers a comprehensive overview and deep dive of the theoretical foundations and practical implementations driving this rapidly evolving field. We also showcase real-world case studies and alternative research projects that highlight the impact of RL controllers in revolutionizing autonomous driving. From tackling complex urban environments to dealing with unpredictable traffic scenarios, these intelligent controllers are pushing the boundaries of what automated vehicles can achieve. Furthermore, we examine the safety considerations and hardware-focused technical details surrounding deployment of RL controllers into automated vehicles. As these algorithms learn and evolve through interactions with the environment, ensuring their behavior aligns with safety standards becomes crucial. Here, we explore the methodologies and frameworks being developed to address these challenges, emphasizing the importance of building reliable control systems for automated vehicles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The Field Operations and Early Results of the South China Sea Monsoon Experiment (SCSMEX)

The South China Sea Monsoon Experiment (SCSMEX) is an international field experiment with the objective to better understand the key physical processes for the onset and evolution of the Asian summer monsoon in relation to fluctuation of the regional hydrologic cycle over Southeast Asian, southern East Asia, aiming at improving monsoon prediction. In this article, we present a description of the major meteorological observation platforms during the Intensive Observing Periods (IOP) of SCSMEX. We also provide highlights of early results and discussions of the role of SCSMEX in providing valuable in-situ data for calibration of satellite rainfall estimate from the Tropical Rainfall Measuring Mission (TRMM). Preliminary results indicate that there are distinctive stages in the onset of the South China Sea monsoon including possibly strong influences from extratropical systems as well as from convection over the Indian Ocean and the Bay of Bengal. There are some tantalizing evidence of complex interactions between the supercloud cluster development over the Indian Ocean, advancing southwest monsoon flow over the South China Sea, midlatitude disturbances and the western Pacific subtropical high, possibly contributing to the disastrous flood over Yangtze River Basin in China during June 1998.

Lau, K. M.↗

"Reinforcement Learning Based Oscillation Dampening: Scaling up Single-Agent RL algorithms to a 100 AV highway field operational test"

In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smooth traffic flow in history as of 2023, uncovering the challenges and breakthroughs that come with developing RL controllers for automated vehicles. We delve into the fundamental concepts behind RL algorithms and their application in the context of self-driving cars, discussing the developmental process from simulation to deployment in detail, from designing simulators to reward function shaping. We present the results in both simulation and deployment, discussing the flow-smoothing benefits of the RL controller. From understanding the basics of Markov decision processes to exploring advanced techniques such as deep RL, our article offers a comprehensive overview and deep dive of the theoretical foundations and practical implementations driving this rapidly evolving field. We also showcase real-world case studies and alternative research projects that highlight the impact of RL controllers in revolutionizing autonomous driving. From tackling complex urban environments to dealing with unpredictable traffic scenarios, these intelligent controllers are pushing the boundaries of what automated vehicles can achieve. Furthermore, we examine the safety considerations and hardware-focused technical details surrounding deployment of RL controllers into automated vehicles. As these algorithms learn and evolve through interactions with the environment, ensuring their behavior aligns with safety standards becomes crucial. We explore the methodologies and frameworks being developed to address these challenges, emphasizing the importance of building reliable control systems for automated vehicles.

Jang, Kathy↗

Field operations with cesium clocks in HF navigation systems

Networks of HF phase comparison marine navigation stations employing cesium clocks are discussed. The largest permanent network is in the Gulf of Mexico where some fourteen base stations are continuously active and others are activated as needed. These HF phase comparison systems, which operate on a single transmission path, require a clock on the mobile unit as well. Inventory consists of upwards of 70 clocks from two different manufacturers. The maintenance of this network as an operating system requires a coordinated effort involving clock preparation, clock environment control, station performance monitoring and field service.

Christy, E. H.↗

Design, performance, and field operation of twisting heliostats for 3,000-sun concentration and high temperature

The idea is to combine the solar energy reflected from a field of many heliostats to obtain a single focus of high concentration and high power. We exploit a new type of “twisting” heliostat” in which as the mount is moved to track the sun through the day, the reflector shape is twisted to maintain a focused image of the sun’s disc on the target, through the day over a wide range of angles of incidence. By combining the light reflected by many twisting heliostats into a single focus, we are not only able to accomplish but also maintain very high concentration and temperature through the day, with higher efficiency than has previously been possible with conventional heliostats having a fixed shape. A circular field of twisting heliostats is used to power a single intense focus atop a central tower. The light from all the heliostats is relayed to an upward facing receiver at the focus via a central Cassegrain secondary reflector located above the receiver. In a specific design targeting 1 MW of power, a 100 m diameter field arrays 431 twisting heliostats, each with a 7 m2 reflector. The secondary reflector ,7.2 m in diameter, is located 24 m above the heliostat field, bringing sunlight with annual average power of 1 MW to a circular focus 0.8 m in diameter, at a concentration averaging 3,000 suns.

14 SOLAR ENERGY↗

Multi-Center Traffic Management Advisor Operational Field Test Results

The Multi-Center Traffic Management Advisor (McTMA) is a research prototype system which seeks to bring time-based metering into the mainstream of air traffic control (ATC) operations. Time-based metering is an efficient alternative to traditional air traffic management techniques such as distance-based spacing (miles-in-trail spacing) and managed arrival reservoirs (airborne holding). While time-based metering has demonstrated significant benefit in terms of arrival throughput and arrival delay, its use to date has been limited to arrival operations at just nine airports nationally. Wide-scale adoption of time-based metering has been hampered, in part, by the limited scalability of metering automation. In order to realize the full spectrum of efficiency benefits possible with time-based metering, a much more modular, scalable time-based metering capability is required. With its distributed metering architecture, multi-center TMA offers such a capability.

Farley, Todd↗