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This slide presentation contains a brief discussion of nuclear transport codes widely used in the space radiation community for shielding and scientific analyses. Seven radiation transport codes that are addressed. The two general methods (i.e., Monte Carlo Method, and the Deterministic Method) are briefly reviewed.
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Large-scale evacuations from major cities during no-notice events - such as chemical or radiological attacks, hazardous material spills, or earthquakes - have an obvious impact on large regions rather than on just the directly affected area. The scope of impact includes the accommodation of emergency evacuation traffic throughout a very large area; the planning of resources to respond appropriately to the needs of the affected population; the placement of medical supplies and decontamination equipment; and the assessment and determination of primary escape routes, as well as routes for incoming emergency responders. Compared to events with advance notice, such as evacuations based on hurricanes approaching an affected area, the response to no-notice events relies exclusively on pre-planning and general regional emergency preparedness. Another unique issue is the lack of a full and immediate understanding of the underlying threats to the population, making it even more essential to gain extensive knowledge of the available resources, the chain of command, and established procedures. Given the size of the area affected, an advanced understanding of the regional transportation systems is essential to help with the planning for such events. The objectives of the work described here (carried out by Argonne National Laboratory) is the development of a multi-modal regional transportation model that allows for the analysis of different evacuation scenarios and emergency response strategies to build a wealth of knowledge that can be used to develop appropriate regional emergency response plans. The focus of this work is on the effects of no-notice evacuations on the regional transportation network, as well as the response of the transportation network to the sudden and unusual demand. The effects are dynamic in nature, with scenarios changing potentially from minute to minute. The response to a radiological or chemical hazard will be based on the time-delayed dispersion of such materials over a large area, with responders trying to mitigate the immediate danger to the population in a variety of ways that may change over time (e.g., in-place evacuation, staged evacuations, and declarations of growing evacuation zones over time). In addition, available resources will be marshaled in unusual ways, such as the repurposing of transit vehicles to support mass evacuations. Thus, any simulation strategy will need to be able to address highly dynamic effects and will need to be able to handle any mode of ground transportation. Depending on the urgency and timeline of the event, emergency responders may also direct evacuees to leave largely on foot, keeping roadways as clear as possible for emergency responders, logistics, mass transport, and law enforcement. This RTSTEP project developed a regional emergency evacuation modeling tool for the Chicago Metropolitan Area that emergency responders can use to pre-plan evacuation strategies and compare different response strategies on the basis of a rather realistic model of the underlying complex transportation system. This approach is a significant improvement over existing response strategies that are largely based on experience gained from small-scale events, anecdotal evidence, and extrapolation to the scale of the assumed emergency. The new tool will thus add to the toolbox available to emergency response planners to help them design appropriate generalized procedures and strategies that lead to an improved outcome when used during an actual event.
This spreadsheet allows the user to calculate parameters relevant to techno-economic performance of a two-step absorption process to transport low temperature geothermal heat some distance (1-20 miles) for use in building air conditioning. The parameters included are (1) energy density of aqueous LiBr and LiCl solutions, (2) transportation cost of trucking solution, and (3) equipment cost for the required chillers and cooling towers in the two-step absorption approach. More information is available in the included public report: "A Technical and Economic Analysis of an Innovative Two-Step Absorption System for Utilizing Low-Temperature Geothermal Resources to Condition Commercial Buildings"
RadSim is being developed to provide the capability to simulate radiation source emissions, interpolate results from radiation transport tools into a common format to prepare incident flux, and model radiation detector response. This software package includes wrapper API code which is utilized in the development of the second (transport) task of the RadSim project. This software package only contains tools to interface RadSim with radiation transport tools (GEANT4 and MCNP) and does not include any part of the transport source code itself. The users will need prior access to the transport tools (GEANT4 and MCNP), and can use this software package to interface with the transport tool of their choice. This software package takes the geometry file for a radiation transport problem and converts it into an input deck for the transport tools (GEANT4 and MCNP). Additionally, it also contains filters that convert the output of the transport tools to a common flux format.
End-of-life (EOL) management of high-activity radioactive sources is made uniquely challenging by the inherent risks associated with storage and transportation of these sources, the complex logistics involved, and the strict requirements for regulatory compliance. Traditional methods lack comprehensive tools for accurate site assessments and precision planning for the transportation of radioactive sources. They also frequently fail to provide the adaptability required to consider diverse operational environments, resulting in inefficiencies and potential safety concerns. This paper introduces a novel software solution developed to address these issues by integrating advanced technologies such as light detection and ranging (LiDAR)-based 3D environment modeling, smart dynamic route planning, and customizable measurement functionalities. This software enables detailed terrain visualizations, facilitating thorough environmental assessments and enabling users to virtually navigate, analyze, and plan site-specific operations. Among the key features are a user-centric interface for virtual navigation, precise site measurement tools for site evaluations, interactive visualizations that highlight potential operational hazards, dynamic route planning capabilities, and real-time collision detection to promote safe workflows. By demonstrating the effectiveness of this tool through real-world application, the present work underscores the tool’s potential to revolutionize radioactive source EOL management by improving operational efficiencies, minimizing risk, and advancing the state of practice to achieve suitable and secure radioactive material handling.
The present activity aims to test the Transportation Tooling (TT) designed for the Cryomodule SSR1 at Fermilab facilities. The tests consisted of road transportation trials of a cryomodule sub-assembly, suspended on a truck using the designed TT. The truck drove along a path inside Fermilab facilities. The trial was performed at an approximate speed of about 25 km/h, which is close to the transportation conditions of the complete Cryomodule. Several accelerometers were mounted on the Transportation Tooling frame and the cryomodule sub-assembly. This allowed comparing the vibration behavior of the inner frame of the TT with the solicitation coming from the truck loading bed, to assess the filtering capabilities of the tooling. Also, the acceleration of the main components could be monitored during the whole transportation, to obtain a validation of the developed numerical model.
In high-performance parallel in situ processing, the term in transit processing refers to those configurations where data must move from a producer to a consumer that runs on separate resources. In the context of parallel and distributed computing on an HPC platform one of the central challenges is to determine a mapping of data from producer ranks to consumer ranks. This problem is complicated by the heterogeneity that arises in producer-consumer pairs, such as when producer and consumer codes have different levels of concurrency, different scaling characteristics, or different data models. The resulting mapping and movement of data from M producer to N consumer ranks can have a significant impact on aggregate application performance, particularly when the data consumer requires only a subset of the overall data for its task. This chapter focuses on the design considerations that underlie SENSEI’s implementation to this challenging problem. These design considerations extend the core SENSEI architecture and include ideas like the need to accommodate flexibility in the choice of different partitioning methods, the ability for a data consumer to request and receive only the subset of data needed for its particular operation, and the ability to leverage any of several different data transport tools. The idea of proximity portability, being able to use different data transport methods as part of an in transit workflow, is illustrated through the use of three different transport layers where switching from one transport tool to another is accomplished with only a configuration file change. Here, the chapter also includes a performance analysis summary showing the performance gains that are possible in terms of multiple metrics, such as memory footprint, time to solution, and amount of data moved, when using optimized partitioners in an in transit setting, gains that are made possible by the implementation shaped by specific design considerations.
Irradiation of {sup 237}Np-bearing targets in Oak Ridge National Laboratory's (ORNL) High Flux Isotope Reactor (HFIR) results in the efficient production of {sup 238}Pu, which, in the form of heat source PuO{sub 2}, is used as a reliable power source for deep-space and planetary NASA missions. A technology demonstration subproject was initiated at ORNL in 2011 to develop and implement the technology required to establish a {sup 238}Pu supply chain. A systematic progression of NpO{sub 2}/Al cermet (20 vol.% NpO{sub 2}) activities to date has successfully demonstrated target fabrication, irradiation, and chemical recovery processes. Recent program tasks have included the development of the HFIRCON transport and depletion tool for efficient reactor physics analyses and the evaluation of increased NpO{sub 2} loadings (i.e., beyond 20 vol.%) and NpN-based targets. This paper documents the deployment of the HFIRCON code to assess various Np concentrations in NpO{sub 2}- and NpN-based targets in HFIR's inner small vertical experiment facilities. Results indicate that {sup 238}Pu production and quality can be enhanced with increased Np loadings; however, target conversion rates are reduced. The results recorded in this paper, thermal and material balance evaluations, and testing requirement planning will be used to determine whether increased NpO{sub 2} loadings or NpN-based targets will be further considered. (authors)
The groundwater remedy for hexavalent chromium at the Hanford Site includes operation of five large pump-and-treat systems along the Columbia River. The systems at the 100-HR-3 and 100-KR-4 groundwater operable units treat a total of about 9,840 liters per minute (2,600 gallons per minute) of groundwater to remove hexavalent chromium, and cover an area of nearly 26 square kilometers (10 square miles). The pump-and-treat systems result in large scale manipulation of groundwater flow direction, velocities, and most importantly, the contaminant plumes. Tracking of the plumes and predicting needed system modifications is part of the remedial process optimization, and is a continual process with the goal of reducing costs and shortening the timeframe to achieve the cleanup goals. While most of the initial system evaluations are conducted by assessing performance (e.g., reduction in contaminant concentration in groundwater and changes in inferred plume size), changes to the well field are often recommended. To determine the placement for new wells, well realignments, and modifications to pumping rates, it is important to be able to predict resultant plume changes. In smaller systems, it may be effective to make small scale changes periodically and adjust modifications based on groundwater monitoring results. Due to the expansive nature of the remediation systems at Hanford, however, additional tools were needed to predict the plume reactions to system changes. A computer simulation tool was developed to support pumping rate recommendations for optimization of large pump-and-treat groundwater remedy systems. This tool, called the Pumping Optimization Model, or POM, is based on a 1-layer derivation of a multi-layer contaminant transport model using MODFLOW and MT3D.
This package includes three parts, (1) gov.llnl.math, (2)gov.llnl.utility and (3)gov.llnl.rtk, which are utilized in the development of Radiation Detector Simulator (RadSim) project. RadSim is being developed to provide the capability to: (1) simulate radiation source emissions, (2) interpolate results from radiation transport tools into a common format to prepare incident flux, and (3) model radiation detector response to rapidly produce synthetic radiation measurement templates. RadSim is targeted for open-source release, which will enable researchers and industry partners to model gamma-ray detectors response to simulated flux from the transport tool of their choice. The techniques and implementation will be entirely transparent, which will allow for improvements and boutique modifications by future researchers beyond the lifespan of this specific project. The first tool of the package, gov.llnl.math, includes classes and functions to define and perform basic math operations. Some of the example features available in the package include defining statistical distributions and performing algebra and matrix operations, all of which are already accessible on publicly available software packages such as MATLAB and ROOT. The second package gov.llnl.utility includes tools commonly used to enable optimization and readability of various data structures such as Java lists and external xml files. Lastly, the gov.llnl.rtk package includes classes and functions to implement methods commonly used in radiation physics, such as data structures to represent and characterize photon spectra and tools to apply well-defined and published methods to calibrate a given spectra.
This package includes three parts, (1) gov.bnl.nndc.ensdf, (2) gov.nist.xray and (3) gov.nist.physics.n42, which are utilized in the development of Radiation Detector Simulator (RadSim) project. RadSim is being developed to provide the capability to: (1) simulate radiation source emissions, (2) interpolate results from radiation transport tools into a common format to prepare incident flux, and (3) model radiation detector response to rapidly produce synthetic radiation measurement templates. RadSim is targeted for open-source release, which will enable researchers and industry partners to model gamma-ray detectors response to simulated flux from the transport tool of their choice. The first tool of the package, gov.bnl.nndc.ensdf, includes functionality to parse and split publicly available decay records in ENSDF format, and pull the relevant information from ENSDF libraries. The second tool, gov.nist.xray, provides Xray information using the public NIST database. Lastly, gov.nist.physics.n42, is a tool used to convert an N42 xml file into a Java object that can be interfaced within a Java program.
In this letter, a full band atomistic quantum transport tool is used to predict the performance of double gate metal-oxide-semiconductor field-effect transistors (MOSFETs) over the next 15 years for International Technology Roadmap for Semiconductors (ITRS). As MOSFET channel lengths scale below 20 nm, the number of atoms in the device cross-sections becomes finite. At this scale, quantum mechanical effects play an important role in determining the device characteristics. These quantum effects can be captured with the quantum transport tool. Critical results show the ON-current degradation as a result of geometry scaling, which is in contrast to previous ITRS compact model calculations. Geometric scaling has significant effects on the ON-current by increasing source-to-drain (S/D) tunneling and altering the electronic band structure. By shortening the device gate length from 20 nm to 5.1 nm, the ratio of S/D tunneling current to the overall subthreshold OFF-current increases from 18% to 98%. Despite this ON-current degradation by scaling, the intrinsic device speed is projected to increase at a rate of at least 8% per year as a result of the reduction of the quantum capacitance.
Different learning channels (i.e., learning from upstream actors, local network, global codified knowledge, etc.) coexist in firms’ technological innovation processes. Although firms are exposed to globalization and convenient communication and transportation tools, researchers still argue about the role of geography in technology innovation. Geographic proximity can facilitate knowledge spillover and network-building. Localized learning and the significance of geography indicate the importance of local knowledge in innovative activities. Local knowledge tends to be more closely aligned with local firms’ technological demand and easier to understand and absorb, because they are created and applied in the same context. However, following Schumpeter, innovation researchers believe that diverse knowledge, especially knowledge from external industries and geographically distant places, is a valuable source for innovation, especially disruptive innovation. Therefore, firms must balance different learning channels, especially between localized learning and global learning. However, it is still unclear about the extent to which localized learning is important for technology innovations and which factors influence the degree of localized learning. Meanwhile, most studies in the area of localized learning usually take no account of the international dimension and the interdependent of knowledge at different geographic scales. Different learning channels (i.e., learning from upstream actors, local network, global codified knowledge, etc.) coexist in firms’ technological innovation processes. Although firms are exposed to globalization and convenient communication and transportation tools, researchers still argue about the role of geography in technology innovation. Geographic proximity can facilitate knowledge spillover and network-building. Localized learning and the significance of geography indicate the importance of local knowledge in innovative activities. Local knowledge tends to be more closely aligned with local firms’ technological demand and easier to understand and absorb, because they are created and applied in the same context. However, following Schumpeter, innovation researchers believe that diverse knowledge, especially knowledge from external industries and geographically distant places, is a valuable source for innovation, especially disruptive innovation. Therefore, firms must balance different learning channels, especially between localized learning and global learning. However, it is still unclear about the extent to which localized learning is important for technology innovations and which factors influence the degree of localized learning. Meanwhile, most studies in the area of localized learning usually take no account of the international dimension and the interdependent of knowledge at different geographic scales. To address this research gap, this paper empirically investigated firms’ learning and innovation processes in relation to the geography. The aim is to answer the following three questions: 1) how does geographic distance influence knowledge spillover; 2) how technological characteristics influence knowledge acquisition choices as regards local vs. non-local knowledge? and 3) how do local and non-local knowledge affect the quality of innovation? The subject of our empirical inquiry is photovoltaic balance-of-systems (PV BOS) components. This choice is primarily motivated by two factors: (1) large-scale deployment of distributed solar PV technologies is widely considered to be an important piece in addressing the environmental impacts of the electricity sector, making PV an important technology to study; furthermore, there is a general consensus that the biggest barrier for a wider deployment of PV is the high price of non-module components, and (2) technological aspects of non-module components of PV systems make local conditions (climate, regulation, learning networks, etc.) salient, thus affording a rich empirical setting to explore the geography-innovation-economy interactions at the local level. We find that the localization effect of technological learning in the solar PV BOS industry is at state level, the number of citations-based linkages decreases with distance, and we also find that international knowledge significantly contributes to the quality of patents, which suggests that state border might be a barrier of current knowledge spillover, and only focusing on local innovation networks is not sufficient for promoting PV BOS innovation.
Abstract not provided.
The groundwater remedy for hexavalent chromium at the Hanford Site includes operation of five large pump-and-treat systems along the Columbia River. The systems at the 100-HR-3 and 100-KR-4 groundwater operable units treat a total of about 9,840 liters per minute (2,600 gallons per minute) of groundwater to remove hexavalent chromium, and cover an area of nearly 26 square kilometers (10 square miles). The pump-and-treat systems result in large scale manipulation of groundwater flow direction, velocities, and most importantly, the contaminant plumes. Tracking of the plumes and predicting needed system modifications is part of the remedial process optimization, and is a continual process with the goal of reducing costs and shortening the time frame to achieve the cleanup goals. While most of the initial system evaluations are conducted by assessing performance (e.g., reduction in contaminant concentration in groundwater and changes in inferred plume size), changes to the well field are often recommended. To determine the placement for new wells, well realignments, and modifications to pumping rates, it is important to be able to predict resultant plume changes. In smaller systems, it may be effective to make small scale changes periodically and adjust modifications based on groundwater monitoring results. Due to the expansive nature of the remediation systems at Hanford, however, additional tools were needed to predict the plume reactions to system changes. A computer simulation tool (the Pumping Optimization Model, or POM) was developed to support pumping rate recommendations for optimization of large pump-and-treat groundwater remedy systems. (authors)