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This report describes specific activities in the Fiscal Year (FY) 2023 associated with the Geologic Disposal Safety Assessment (GDSA) Repository Systems Analysis (RSA) work package funded by the Spent Fuel and Waste Science and Technology (SFWST) Campaign of the U.S. Department of Energy Office of Nuclear Energy (DOE-NE), Office of Spent Fuel and Waste Disposition (SFWD).
Emerging technologies have provided unprecedented opportunities to transform information into knowledge and disseminate them in a much faster, cheaper, and userfriendly mode. We have set up a system to produce and disseminate high level (gridded) ocean surface wind data from the NASA Scatterometer and European Remote Sensing missions. The data system is being expanded to produce real-time gridded ocean surface winds from an improved sensor SeaWinds on the Quikscat Mission. The wind field will be combined with hydrologic parameters from the Tropical Rain Measuring Mission to monitor evolving weather systems and natural hazard in real time. It will form the basis for spacebased Ocean Surface Exchange Data Analysis System (SOSEDAS) which will include the production of ocean surface momentum, heat, and water fluxes needed for interdisciplinary studies of ocean-atmosphere interaction. Various commercial or non-commercial software tools have been compared and selected in terms of their ability in database management, remote data accessing, graphical interface, data quality, storage needs and transfer speed, etc. Issues regarding system security and user authentication, distributed data archiving and accessing, strategy to compress large-volume geophysical and satellite data/image. and increasing transferring speed are being addressed. A simple and easy way to access information and derive knowledge from spacebased data of multiple missions is being provided. The evolving 'knowledge system' will provide relevant infrastructure to address Earth System Science, make inroads in educating an informed populace, and illuminate decision and policy making.
As automation and advanced technologies are introduced into transport systems ranging from the Next Generation Air Transportation System termed NextGen, to the advanced surface transportation systems as exemplified by the Intelligent Transportations Systems, to future systems designed for space exploration, there is an increased need to validly predict how the future systems will be vulnerable to error given the demands imposed by the assistive technologies. One formalized approach to study the impact of assistive technologies on the human operator in a safe and non-obtrusive manner is through the use of human performance models (HPMs). HPMs play an integral role when complex human-system designs are proposed, developed, and tested. One HPM tool termed the Man-machine Integration Design and Analysis System (MIDAS) is a NASA Ames Research Center HPM software tool that has been applied to predict human-system performance in various domains since 1986. MIDAS is a dynamic, integrated HPM and simulation environment that facilitates the design, visualization, and computational evaluation of complex man-machine system concepts in simulated operational environments. The paper will discuss a range of aviation specific applications including an approach used to model human error for NASA s Aviation Safety Program, and what-if analyses to evaluate flight deck technologies for NextGen operations. This chapter will culminate by raising two challenges for the field of predictive HPMs for complex human-system designs that evaluate assistive technologies: that of (1) model transparency and (2) model validation.
Included in the series of screen print-outs illustrates the structure and function of the Man-Machine Integrated Design and Analysis System (MIDAS). Views into the use of the system and editors are featured. The use-case in this set of graphs includes the development of a simulation scenario.
Maturation of intelligent systems technologies and their incorporation into aerial platforms are dictating the development of new analysis tools and incorporation of such tools into existing system analysis methodologies in order to fully capture the trade-offs of autonomy on vehicle and mission success. A first-order "system analysis of autonomy" methodology is outlined in this paper. Further, this analysis methodology is subsequently applied to notional high-altitude long-endurance (HALE) aerial vehicle missions.
Here, direct hydrogen fuel cell electric vehicles (FCEVs) produce only water as a byproduct, thereby eliminating tailpipe carbon and criteria air pollutant emissions associated with internal combustion engine vehicles (ICEVs). However, in order to achieve economic parity with ICEVs, technological challenges must be overcome to lower system cost. The U.S. Department of Energy (DOE) monitors estimated fuel cell (FC) system cost and tracks progress towards milestones by techno-economic analysis based on demonstrated laboratory technologies for a next-generation 80 kWnet automotive FC stack for light-duty vehicles. The findings of the 2017 automotive FC system cost analysis are summarized, including the baseline system characteristics and specifications and the results of Design for Manufacture and Assembly (DFMA ® ) analysis of system manufacturing across a range of annual production rates. The highest volume predictions, for 100,000 and 500,000 units per year, result in a total system cost of 50/kWnet and 45/kWnet, respectively. The assumptions and methodology of the DFMA® analysis of the 2017 baseline FC system were validated by comparison with the FC system in the commercially available Toyota Mirai. One prospective pathway for decreasing system cost to 30/kW net needed for cost competitiveness with ICEVs is outlined.
The ASAC Airport Capacity Model and the ASAC Airport Delay Model support analyses of technologies addressing airport capacity. NASA's Aviation System Analysis Capability (ASAC) Airport Capacity Model estimates the capacity of an airport as a function of weather, Federal Aviation Administration (FAA) procedures, traffic characteristics, and the level of technology available. Airport capacity is presented as a Pareto frontier of arrivals per hour versus departures per hour. The ASAC Airport Delay Model allows the user to estimate the minutes of arrival delay for an airport, given its (weather dependent) capacity. Historical weather observations and demand patterns are provided by ASAC as inputs to the delay model. The ASAC economic models can translate a reduction in delay minutes into benefit dollars.
The U.S. Department of Energy (DOE) is leading the National effort to manage the back end of the nuclear fuel cycle, encompassing the safe transportation, storage/staging, and/or eventual disposal of used nuclear fuel (UNF) and high-level radioactive waste. The Next Generation System Analysis Model (NGSAM) is DOE’s discrete-event, agent-based simulation tool designed to model the full life cycle of UNF from reactor discharge to final disposal. NGSAM supports the DOE Office of Spent Fuel and High-Level Waste Disposition by enabling a detailed, scenario-based analysis of logistics, infrastructure, and shipping strategies. NGSAM replaces legacy models with a modern, flexible platform built on Repast Simphony and enhanced by the Process Analysis Tool. NGSAM simulates the movement and interaction of individual fuel assemblies with system components such as canisters, casks, railcars, and facilities. The model integrates with the Java Transportation Operations Model to plan and execute transportation scenarios, supporting both constrained and unconstrained resource allocation. Key features include customizable allocation and acceptance algorithms, detailed facility-level operations, and a Quick Edit tool for rapid scenario adjustments. NGSAM supports multimodal transportation modeling (e.g. rail, road, barge) and provides comprehensive cost, schedule, and infrastructure data. NGSAM utilizes data from sources such as DOE’s STANDARDS UNF database and DOE’s Stakeholder Tool for Assessing Radioactive Transportation, while also allowing user-defined inputs for scenario customization. NGSAM enables stakeholders to evaluate complex UNF management strategies, assess system performance under varying assumptions, and inform decision making for future infrastructure investments. Its modular architecture and integration with other Integrated Waste Management System tools make it a critical asset for planning the safe and efficient disposition of the Nation’s growing UNF inventory.
The task of evaluating obstructions in the optical throughput of an optical system requires the use of two disciplines, and hence, two models: optical models for the details of optical propagation, and mechanical models for determining the actual structure that exists in the optical system. Previous analysis methods for creating beam envelopes (or cones of light) for use in this obstruction analysis were found to be cumbersome to calculate and take significant time and resources to complete. A new process was developed that takes less time to complete beam envelope analysis, is more accurate and less dependent upon manual node tracking to create the beam envelopes, and eases the burden on the mechanical CAD (computer-aided design) designers to form the beam solids. This algorithm allows rapid generation of beam envelopes for optical system obstruction analysis. Ray trace information is taken from optical design software and used to generate CAD objects that represent the boundary of the beam envelopes for detailed analysis in mechanical CAD software. Matlab is used to call ray trace data from the optical model for all fields and entrance pupil points of interest. These are chosen to be the edge of each space, so that these rays produce the bounding volume for the beam. The x and y global coordinate data is collected on the surface planes of interest, typically an image of the field and entrance pupil internal of the optical system. This x and y coordinate data is then evaluated using a convex hull algorithm, which removes any internal points, which are unnecessary to produce the bounding volume of interest. At this point, tolerances can be applied to expand the size of either the field or aperture, depending on the allocations. Once this minimum set of coordinates on the pupil and field is obtained, a new set of rays is generated between the field plane and aperture plane (or vice-versa). These rays are then evaluated at planes between the aperture and field, at a desired number of steps perceived necessary to build up the bounding volume or cone shape. At each plane, the ray coordinates are again evaluated using the convex hull algorithm to reduce the data to a minimal set. When all of the coordinates of interest are obtained for every plane of the propagation, the data is formatted into an xyz file suitable for FRED optical analysis software to import and create a STEP file of the data. This results in a spiral-like structure that is easily imported by mechanical CAD users who can then use an automated algorithm to wrap a skin around it and create a solid that represents the beam.
Most reliability analysis techniques and tools assume that a system is used for a mission consisting of a single phase. However, multiple phases are natural in many missions. The failure rates of components, system configuration, and success criteria may vary from phase to phase. In addition, the duration of a phase may be deterministic or random. Recently, several researchers have addressed the problem of reliability analysis of such systems using a variety of methods. A new technique for phased-mission system reliability analysis based on Boolean algebraic methods is described. Our technique is computationally efficient and is applicable to a large class of systems for which the failure criterion in each phase can be expressed as a fault tree (or an equivalent representation). Our technique avoids state space explosion that commonly plague Markov chain-based analysis. A phase algebra to account for the effects of variable configurations and success criteria from phase to phase was developed. Our technique yields exact (as opposed to approximate) results. The use of our technique was demonstrated by means of an example and present numerical results to show the effects of mission phases on the system reliability.
A computer program known as SOLN was developed as an independent segment of the NASA-Ames three-dimensional potential flow analysis systems of linear algebraic equations. Methods used include: LU decomposition, Householder's method, a partitioning scheme, and a block successive relaxation method. Due to the independent modular nature of the program, it may be used by itself and not necessarily in conjunction with other segments of the POTFAN system.
Atmospheric data assimilation is a method of combining observations with model forecasts to produce a more accurate description of the atmosphere than the observations or forecast alone can provide. Data assimilation plays an increasingly important role in the study of climate and atmospheric chemistry. The NASA Data Assimilation Office (DAO) has developed the Goddard Earth Observing System Data Assimilation System (GEOS DAS) to create assimilated datasets. The core computational components of the GEOS DAS include the GEOS General Circulation Model (GCM) and the Physical-space Statistical Analysis System (PSAS). The need for timely validation of scientific enhancements to the data assimilation system poses computational demands that are best met by distributed parallel software. PSAS is implemented in Fortran 90 using object-based design principles. The analysis portions of the code solve two equations. The first of these is the "innovation" equation, which is solved on the unstructured observation grid using a preconditioned conjugate gradient (CG) method. The "analysis" equation is a transformation from the observation grid back to a structured grid, and is solved by a direct matrix-vector multiplication. Use of a factored-operator formulation reduces the computational complexity of both the CG solver and the matrix-vector multiplication, rendering the matrix-vector multiplications as a successive product of operators on a vector. Sparsity is introduced to these operators by partitioning the observations using an icosahedral decomposition scheme. PSAS builds a large (approx. 128MB) run-time database of parameters used in the calculation of these operators. Implementing a message passing parallel computing paradigm into an existing yet developing computational system as complex as PSAS is nontrivial. One of the technical challenges is balancing the requirements for computational reproducibility with the need for high performance. The problem of computational reproducibility is well known in the parallel computing community. It is a requirement that the parallel code perform calculations in a fashion that will yield identical results on different configurations of processing elements on the same platform. In some cases this problem can be solved by sacrificing performance. Meeting this requirement and still achieving high performance is very difficult. Topics to be discussed include: current PSAS design and parallelization strategy; reproducibility issues; load balance vs. database memory demands, possible solutions to these problems.
We designed a mechanism and the accompanying sample holders to transfer between a VEECO 930 oxide molecular beam epitaxy (MBE) and a PHI Versa Probe X-ray photoemission spectroscopy (XPS) chamber within a multiple station growth, processing, and analysis system through ultrahigh vacuum (UHV). The mechanism consists of four parts: (1) a platen compatible with the MBE growth stage, (2) a platen compatible with the XPS analysis stage, (3) a sample coupon that is transferred between the two platens, and (4) the accompanying UHV transfer line. The mechanism offers a robust design that enables transfer back and forth between the growth chamber and the analysis chamber, and yet is flexible enough to allow transfer between standard sample holders for thin film growth and masked sample holders for making electrical contacts and Schottky junctions, all without breaking vacuum. We used this mechanism to transfer a barium strontium titanate thin film into the XPS analysis chamber and performed XPS measurements before and after exposing the sample to the air. After air exposure, a thin overlayer of carbon was found to form and a significant shift ({approx}1 eV) in the core level binding energies was observed.
A user requirements analysis (URA) was undertaken to determine and appropriate public domain Geographic Information System (GIS) software package for potential integration with NASA's LAS (Land Analysis System) 5.0 image processing system. The necessity for a public domain system was underscored due to the perceived need for source code access and flexibility in tailoring the GIS system to the needs of a heterogenous group of end-users, and to specific constraints imposed by LAS and its user interface, Transportable Applications Executive (TAE). Subsequently, a review was conducted of a variety of public domain GIS candidates, including GRASS 3.0, MOSS, IEMIS, and two university-based packages, IDRISI and KBGIS. The review method was a modified version of the GIS evaluation process, development by the Federal Interagency Coordinating Committee on Digital Cartography. One IEMIS-derivative product, the ALBE (AirLand Battlefield Environment) GIS, emerged as the most promising candidate for integration with LAS. IEMIS (Integrated Emergency Management Information System) was developed by the Federal Emergency Management Agency (FEMA). ALBE GIS is currently under development at the Pacific Northwest Laboratory under contract with the U.S. Army Corps of Engineers' Engineering Topographic Laboratory (ETL). Accordingly, recommendations are offered with respect to a potential LAS/ALBE GIS linkage and with respect to further system enhancements, including coordination with the development of the Spatial Analysis and Modeling System (SAMS) GIS in Goddard's IDM (Intelligent Data Management) developments in Goddard's National Space Science Data Center.
This document contains five papers on coping with ice formation during the operation of aircraft. The first paper uses a pilot survey to identify the desired attributes of future information systems for aircraft icing. The second paper investigates the influence of potential remote ice-detection system features on pilot decision making. The third paper investigates the effectiveness of aviation weather forecasting along aircraft trajectories. The fourth paper applied a human-centered systems analysis to the adverse aircraft weather encounter problem in order to identify desirable functions of weather and icing information. The objective of the fifth paper, a viewgraph presentation, is to propose means to improve aviation weather information, training, and procedures based on a human-centered systems approach.
The Spent Fuel and Waste Science and Technology (SFWST) Campaign of the U.S. Department of Energy Office of Nuclear Energy, Office of Spent Fuel and Waste Disposition (SFWD), has been conducting research and development on generic deep geologic disposal systems (i.e., geologic repositories). This report describes specific activities in the second half of Fiscal Year (FY) 2019 associated with the Geologic Disposal Safety Assessment (GDSA) Repository Systems Analysis (RSA) work package within the SFWST Campaign. The overall objective of the GDSA RSA work package is to develop generic deep geologic repository concepts and system performance assessment (PA) models in several host-rock environments, and to simulate and analyze these generic repository concepts and models using the GDSA Framework toolkit, and other tools as needed.
The Spent Fuel and Waste Science and Technology (SFWST) Campaign of the U.S. Department of Energy Office of Nuclear Energy, Office of Spent Fuel and Waste Disposition (SFWD), has been conducting research and development on generic deep geologic disposal systems (i.e., geologic repositories). This report describes specific activities in the Fiscal Year (FY) 2020 associated with the Geologic Disposal Safety Assessment (GDSA) Repository Systems Analysis (RSA) work package within the SFWST Campaign. The overall objective of the GDSA RSA work package is to develop generic deep geologic repository concepts and system performance assessment (PA) models in several host-rock environments, and to simulate and analyze these generic repository concepts and models using the GDSA Framework toolkit, and other tools as needed.
The Spent Fuel and Waste Science and Technology (SFWST) Campaign of the U.S. Department of Energy Office of Nuclear Energy, Office of Spent Fuel and Waste Disposition (SFWD), has been conducting research and development on generic deep geologic disposal systems (i.e., geologic repositories). This report describes specific activities in fiscal year (FY) 2019 associated with FY19 Geologic Disposal Safety Assessment (GDSA) Repository Systems Analysis (RSA) work package within the SFWST Campaign. The overall objective of the GDSA RSA work package is to develop generic deep geologic repository concepts and system performance assessment (PA) models in several host-rock environments, and to simulate and analyze these generic repository concepts and models using the GDSA Framework toolkit, and other tools as needed.