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Energy storage technologies that can economically store and provide electricity over multi-day and seasonal timescales are likely to be a critical component of a sustainable and resilient energy system. This analysis performs a broad survey of energy storage technologies to find storage media that are promising for these long-duration energy storage applications.
The Blending Pipeline Analysis Tool for Hydrogen (BlendPATH) is a flexible, open-source Python tool designed to provide users with case-by-case analysis capabilities to identify the necessary modifications to repurpose existing natural gas transmission pipeline networks to transport hydrogen as a blend of a user-specified volume fraction of hydrogen or as a pure stream and to estimate the associated capital and operating expenditures resulting from those modifications. This tool is intended to be applied during the initial screening stage of a prospective project when pipeline developers compile transmission pipeline technical documentation and history but prior to performing detailed pipeline inspections. Performing analysis with BlendPATH during this initial screening stage can provide the user with an understanding of promising opportunities and probable economic outcomes of repurposing their pipeline network for hydrogen before proceeding with detailed pipeline materials testing and pipeline inspections. BlendPATH consists of multiple modules to simulate, assess, and modify existing natural gas transmission pipeline network designs to be compatible with hydrogen as a blend or pure stream. The tool employs an open-source gas network hydraulic model to simulate existing, user-specified transmission pipeline networks, and it applies ASME B31.12 to assess the pipe segments within these networks for compatibility with hydrogen and to modify the networks to achieve compatibility where the existing infrastructure is inadequate. Users can specify ASME B31.12 design options for pipeline assessment and can select from multiple methods for pipeline modification. This report details the functionalities of BlendPATH Version 2.0.2 and demonstrates an example of applying BlendPATH to a case study. Potential and intended users of this framework include natural gas pipeline developers and operators and researchers at both public and private institutions. BlendPATH is publicly available at https://github.com/NREL/BlendPATH.
Analysis performed in the Flight Dynamics Facility by the Earth Radiation Budget Satellite (ERBS) Attitude Determination Support team illustrates the pitch attitude control motion and roll attitude errors induced by Earth infrared (IR) horizon radiance variations. IR scanner and inertial reference unit (IRU) pitch and roll flight data spanning 4 years of the ERBS mission are analyzed to illustrate the changes in the magnitude of the errors on time scales of the orbital period, months, and seasons. The analysis represents a unique opportunity to compare prelaunch estimates of radiance-induced attitude errors with flight measurements. As a consequence of this work the following additional information is obtained: an assessment of an average model of these errors and its standard deviation, a measurement to determine and verify previously proposed corrections to the current Earth IR radiance data base, and the possibility of a mean motion model derived from flight data in place of IRU data for ERBS fine attitude determination.
Analysis performed in the Flight Dynamics Facility by the Earth Radiation Budget Satellite (ERBS) Attitude Determination Support team illustrates the pitch attitude control motion and roll attitude errors induced by Earth infrared (IR) horizon radiance variations. IR scanner and inertial reference unit (IRU) pitch and roll flight data spanning 4 years of the ERBS mission are analyzed to illustrate the changes in the magnitude of the errors on time scales of the orbital period, months, and seasons. The analysis represents a unique opportunity to compare prelaunch estimates of radiance-induced attitude errors with flight measurements. As a consequence of this work the following additional information is obtained: an assessment of an average model of these errors and its standard deviation, a measurement to determine and verify previously proposed corrections to the current Earth IR radiance data base, and the possibility of a mean motion model derived from flight data in place of IRU data for ERBS fine attitude determination.
Nuclear thermal propulsion (NTP) systems occupy a unique area in the space propulsion technology landscape due to their ability to combine moderate-to-high thrust systems normally seen in chemical propulsion systems with specific impulses that are closer to those observed in some electric propulsion systems. Consequently, NTP systems have the potential to greatly expand access to deep space and can enable a variety of missions that achieve the science goals outlined in NASA’s decadal surveys. This paper leverages previous analysis performed to show the applicability of NTP systems for notional science missions, expanding the analyzed portfolio to encompass additional science mission profiles and demonstrating how the use of NTP affects various mission parameters, such as trip time and delivered mass. This paper also outlines efforts to improve the fidelity of the existing NTP design concepts and vehicles that are utilized by leveraging previous work on nuclear propulsion systems for human-Mars missions. The fidelity of the analysis in this work is improved over previous studies, permitting commensurate improvements in the analyses of previous mission concept studies –the Triton lander, the solar polar orbiter, and the interstellar medium probe missions.
The primary objective of this paper is to demonstrate the use of process-based manufacturing and assembly cost models in a traditional performance-focused multidisciplinary design and optimization process. The use of automated cost-performance analysis is an enabling technology that could bring realistic processbased manufacturing and assembly cost into multidisciplinary design and optimization. In this paper, we present a new methodology for incorporating process costing into a standard multidisciplinary design optimization process. Material, manufacturing processes, and assembly processes costs then could be used as the objective function for the optimization method. A case study involving forty-six different configurations of a simple wing is presented, indicating that a design based on performance criteria alone may not necessarily be the most affordable as far as manufacturing and assembly cost is concerned.
The NASA Space Communications and Navigation (SCaN) Program is responsible for providing communication and navigation services to scientific and human space exploration missions. SCaN's current Space Network provides radio frequency (RF) relay services to near Earth space missions via Tracking and Data Relay Satellites (TDRS). SCaN plans to offer a new generation of relay services beginning in 2025, including the addition of optical communications capabilities and enhanced RF capabilities. The primary drivers behind the development of these next generation relay network services are to enhance communication and navigation services with significantly reduced development and operational costs. Several approaches being considered for implementation of these services are through government owned capabilities, through commercial service providers, or a combination of the two. One approach receiving a great deal of attention is the use of Public-Private Partnerships (PPP) to develop and provide capabilities or services. Utilizing Public-Private Partnerships allows NASA and commercial entities to share the investment, standards, and risks of developing and testing new or enhanced capabilities which can benefit both NASA and the commercial space communication industry. The capabilities developed under the PPP can then be used to support the growth of the commercial satellite communications industry while simultaneously being introduced into NASA operations to provide service to future NASA missions as part of the NASA Next Generation Architecture. Partnerships formed for this purpose can also serve as the basis for further NASA acquisition activities where government and industry can continue to share the cost, risk, and benefits of space communications capability development and operations. This objective is consistent with the 2010 National Space Policy stated principles: "The United States is committed to encouraging and facilitating the growth of a U.S. commercial space sector that supports U.S. needs, is globally competitive, and advances U.S. leadership in the generation of new markets and innovation-driven entrepreneurship." [1]NASA has conducted several internal studies as well as externally funded studies with industry to define the next generation space communication architecture. NASA has approached the commercial industry through a Request for Information (RFI) to define further the next generation architecture and has conducted numerous internal and external studies. The results are promising and are shaping the approach to utilize Public Private Partnership to achieve NASA's objectives while reducing costs. The commercial satellite industry has begun to deploy high performance, high throughput global satellite constellations which have the potential to provide communication services to NASA Missions. Commercial satellite manufacturers have advanced their processes to rapidly design, build, and deliver, reliable communication satellites using minimum government oversight. In this paper, we will 1) describe the NASA Next Generation Architecture, Concept of Operations (ConOps), and salient characteristics; 2) Discuss the rational of Public-Private Partnerships to achieve NASA’s next generation communication architecture; and 3) Summarize the preliminary analysis performed to date and describe the path forward.
Human reliability analysis (HRA) is a method for evaluating human errors in a variety of complex systems such as nuclear power plants, military systems, aircraft, and chemical plants. Most HRA methods currently used by regulatory institutes or utilities are called static HRA and are carried out by simple worksheets or simple calculators. To date, there are many unsolved or intrinsic challenges in static HRA. For example, existing static HRA does not realistically model and evaluate human actions as they would be performed at actual systems. There is no method with HRA to objectively estimate the time required for human actions despite being essential to HRA processes. In addition, many HRA methods still rely on a dataset generated prior to the 1980s, from unrelated industry experience or simply from expert judgment. Accordingly, this study attempted to research how to overcome the challenges of existing HRA via dynamic risk assessment (a.k.a., simulation-based or computation-based risk assessment) techniques. First, this study developed a dynamic HRA method, named as PRocedure-based Investigation Method of EMRALD Risk Assessment – HRA (PRIMERA-HRA). The PRIMERA-HRA mainly concentrates on providing HRA analysts with specific guidelines on how to reasonably model human actions, assign human reliability data and evaluate output of simulation within a dynamic probabilistic risk assessment tool, called as Event Modeling Risk Assessment using Linked Diagrams (EMRALD). Second, this study also developed a module for performance shaping factors (i.e., the key concept in HRA quantification) applicable to dynamic HRA, then implemented it based on PRIMERA-HRA within the EMRALD tool. Third, this study developed an HRA data collection framework to support dynamic HRA, called as Simplified Human Error Experimental Program (SHEEP). Originally, the SHEEP study aimed to support static HRA and its data collection, but recently extended the scope to the new technologies such as dynamic HRA or HRA for advanced reactors. SHEEP focuses on the use of data collected from simplified simulators to complement—but not replace—data collection studies using full-scope simulators and actual operators. To date, many experiments were conducted under the SHEEP framework. Multiple analyses, such as human performance analysis, human error analysis, task complexity analysis, learning effect analysis and time distribution analysis, were also carried out using the collected data. Then, based on the major insights, an approach to inferring full-scope data based on simplified simulator data was proposed. The PRIMERA-HRA and SHEEP research are expected to evaluate human actions more realistically than existing static HRA, provide an opportunity to collect more HRA data with reasonable cost and labor, then contribute to enhance the quality of HRA.
Human reliability analysis (HRA) is a method for evaluating human errors in a variety of complex systems such as nuclear power plants, military systems, aircraft, and chemical plants. Most HRA methods currently used by regulatory institutes or utilities are called static HRA and are carried out by simple worksheets or simple calculators. To date, there are many unsolved or intrinsic challenges in static HRA. For example, existing static HRA does not realistically model and evaluate human actions as they would be performed at actual systems. There is no method with HRA to objectively estimate the time required for human actions despite being essential to HRA processes. In addition, many HRA methods still rely on a dataset generated prior to the 1980s, from unrelated industry experience or simply from expert judgment. Accordingly, this study attempted to research how to overcome the challenges of existing HRA via dynamic risk assessment (a.k.a., simulation-based or computation-based risk assessment) techniques. First, this study developed a dynamic HRA method, named as PRocedure-based Investigation Method of EMRALD Risk Assessment – HRA (PRIMERA-HRA). The PRIMERA-HRA mainly concentrates on providing HRA analysts with specific guidelines on how to reasonably model human actions, assign human reliability data and evaluate output of simulation within a dynamic probabilistic risk assessment tool, called as Event Modeling Risk Assessment using Linked Diagrams (EMRALD). Second, this study also developed a module for performance shaping factors (i.e., the key concept in HRA quantification) applicable to dynamic HRA, then implemented it based on PRIMERA-HRA within the EMRALD tool. Third, this study developed an HRA data collection framework to support dynamic HRA, called as Simplified Human Error Experimental Program (SHEEP). Originally, the SHEEP study aimed to support static HRA and its data collection, but recently extended the scope to the new technologies such as dynamic HRA or HRA for advanced reactors. SHEEP focuses on the use of data collected from simplified simulators to complement—but not replace—data collection studies using full-scope simulators and actual operators. To date, many experiments were conducted under the SHEEP framework. Multiple analyses, such as human performance analysis, human error analysis, task complexity analysis, learning effect analysis and time distribution analysis, were also carried out using the collected data. Then, based on the major insights, an approach to inferring full-scope data based on simplified simulator data was proposed. The PRIMERA-HRA and SHEEP research are expected to evaluate human actions more realistically than existing static HRA, provide an opportunity to collect more HRA data with reasonable cost and labor, then contribute to enhance the quality of HRA.
The Molten Salt Nuclear battery (MsNB) is a microreactor based on technology developed and operated at Oak Ridge National Laboratory in the 1960s [1]. But the MsNB has been simplified by removing pumps and valves for improved reliability and safety. The MsNB can safely provide up to 10 MWe of power for up to 10 years and potentially it can be transported by air, truck, and rail thanks due to to its small footprint. A computer model has been developed to represent a prototypical 400-kW MsNB using the ANL system code SAM [2]. The model has been used to produce a reactor thermal-hydraulic performance map and perform analysis of unprotected loss of heat sink accident scenario.
Presented are the results of the cost analysis performed to update and refine the program phase C/D cost estimates for a Shuttle Derived Vehicle (SDV) tanker. The SDV tanker concept is an unmanned cargo vehicle incorporating a set of propellant tanks in the vehicle's payload module. The tanker will be used to meet the demand for a cryogenic propellant supply in orbit. The propellant tanks are delivered to a low Earth orbit or to an orbit in the vicinity of the Space Station. The intent of the economic analysis is to provide NASA with economic justification for the propellant scavenging concept that minimizes the total Space Transportation System life cycle cost. The detailed costs supporting the concept selection process are presented with descriptive text to aid in forecasting the phase C/D project and program planning. Included are all propellant scavenging costs as well as all SDV, STS and Orbital Maneuvering Vehicle charges to deliver the propellants to the Space Station.
This document summarizes the safety analysis performed on a Flight Guidance System (FGS) requirements model. In particular, the safety properties desired of the FGS model are identified and the presence of the safety properties in the model is formally verified. Chapter 1 provides an introduction to the entire project, while Chapter 2 gives a brief overview of the problem domain, the nature of accidents, model based development, and the four-variable model. Chapter 3 outlines the approach. Chapter 4 presents the results of the traditional safety analysis techniques and illustrates how the hazardous conditions associated with the system trace into specific safety properties. Chapter 5 presents the results of the formal methods analysis technique model checking that was used to verify the presence of the safety properties in the requirements model. Finally, Chapter 6 summarizes the main conclusions of the study, first and foremost that model checking is a very effective verification technique to use on discrete models with reasonable state spaces. Additional supporting details are provided in the appendices.
This document summarizes the safety analysis performed on a Flight Guidance System (FGS) requirements model. In particular, the safety properties desired of the FGS model are identified and the presence of the safety properties in the model is formally verified. Chapter 1 provides an introduction to the entire project, while Chapter 2 gives a brief overview of the problem domain, the nature of accidents, model based development, and the four-variable model. Chapter 3 outlines the approach. Chapter 4 presents the results of the traditional safety analysis techniques and illustrates how the hazardous conditions associated with the system trace into specific safety properties. Chapter 5 presents the results of the formal methods analysis technique model checking that was used to verify the presence of the safety properties in the requirements model. Finally, Chapter 6 summarizes the main conclusions of the study, first and foremost that model checking is a very effective verification technique to use on discrete models with reasonable state spaces. Additional supporting details are provided in the appendices.
This report documents comparisons between Fuel Model (PARFUME) model predictions versus Bison for selected compacts from the second irradiation test of the Advanced Gas Reactor (AGR) program that occurred from June 2010 to October 2013 in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). PARFUME is a fuel performance analysis and modeling code, used for evaluating gas-reactor tristructural isotropic (TRISO) coated particle fuel for prismatic, pebble bed, plate, and cylindrical type fuel geometries. PARFUME is an integrated mechanistic computer code that evaluates the thermal, mechanical, and physico-chemical behavior of TRISO coated-fuel particles and the probability for fuel failure given the particle-to-particle statistical variations in physical dimensions and material properties that arise during the fuel fabrication process. Bison is a nuclear fuel performance application built using the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element library (Permann 2020). Bison is capable of modeling multiple fuel forms in a wide variety of dimensions and geometries. It solves coupled nonlinear partial differential equations, including heat conduction, mechanics, fission product species transport etc., in a fully implicit manner. Comparisons between PARFUME and Bison were performed using four compacts from the AGR-2 experiment. Selected outputs were chosen based on their impact on the probability of the SiC layer failing. In general there was good agreement between PARFUME and Bison with the exception of predicting the gap formed between the buffer and IPyC. Further comparisons between PARFUME and Bison are planned to further develop Bison’s capabilities.
The Optical Communications Demonstrator (OCD) is a laboratory-based lasercom demonstration terminal designed to validate several key technologies, including beacon acquisition, high bandwidth tracking, precision bearn pointing, and point-ahead compensation functions. It has been under active development over the past few years. The instrument uses a CCD array detector for both spatial acquisition and high-bandwidth tracking, and a fiber coupled laser transmitter. The array detector tracking concept provides wide field-of-view acquisition and permits effective platform jitter compensation and point-ahead control using only one steering mirror. This paper describes the detailed design and characterization of the digital control loop system which includes the Fast Steering Mirror (FSM), the CCD image tracker, and the associated electronics. The objective is to improve the overall system performance using laboratory measured data. The. design of the digital control loop is based on a linear time invariant open loop model. The closed loop performance is predicted using the theoretical model. With the digital filter programmed into the OCD control software, data is collected to verify the predictions. This paper presents the results of the, system modeling and performance analysis. It has been shown that measurement data closely matches theoretical predictions. An important part of the laser communication experiment is the ability of FSM to track the laser beacon within the. required tolerances. The pointing must be maintained to an accuracy that is much smaller than the transmit signal beamwidth. For an earth orbit distance, the system must be able to track the receiving station to within a few microradians. The failure. to do so will result in a severely degraded system performance.
Results of a computer simulation of the performance of a solar flat plate collector powered electrical generation system are presented. The simulation was configured to include locations in New Mexico, North Dakota, Tennessee, and Massachusetts, and considered a water-based heat-transfer fluid collector system with storage. The collectors also powered a Rankine-cycle boiler filled with a low temperature working fluid. The generator was considered to be run only when excess solar heat and full storage would otherwise require heat purging through the collectors. All power was directed into the utility grid. The solar powered generator unit addition was found to be dependent on site location and collector area, and reduced the effective solar cost with collector areas greater than 400-670 sq m. The sites were economically ranked, best to worst: New Mexico, North Dakota, Massachusetts, and Tennessee.
The feasibility of conducting a statistical analysis of simulation experiments to study airport capacity is investigated. First, the form of the distribution of airport capacity is studied. Since the distribution is non-Gaussian, it is important to determine the effect of this distribution on standard analysis of variance techniques and power calculations. Next, power computations are made in order to determine how economic simulation experiments would be if they are designed to detect capacity changes from condition to condition. Many of the conclusions drawn are results of Monte-Carlo techniques.
NASA Ames and Langley are partnering with DLR to propose a comprehensive instrumentation suite known as the Dragonfly Entry Aerosciences Measurements (DrEAM). DrEAM will provide key aerothermodynamic data and performance analysis for Dragonfly’s forebody and backshell Thermal Protection System (TPS), and also includes a DLR-provided Data Acquisition System (DAS). Titan's atmosphere predominantly consists of nitrogen (~ 98% by mole) with small amounts of methane (~ 2% by mole). CN is a strong radiator and is found in nonequilibrium concentrations for Titan entry, the modeling of which has proven to be a difficult task. The DrEAM instrumentation suite will significantly advance the state-of-the-art not only by documenting the environment and performance of Dragonfly’s entry system but also by making key measurements in Titan’s atmosphere for the first time, thus providing new benchmark data applicable to entry science more generally.