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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 379 records · Page 21

Modular Stirling Radioisotope Generator

High-efficiency radioisotope power generators will play an important role in future NASA space exploration missions. Stirling Radioisotope Generators (SRGs) have been identified as a candidate generator technology capable of providing mission designers with an efficient, high-specific-power electrical generator. SRGs high conversion efficiency has the potential to extend the limited Pu-238 supply when compared with current Radioisotope Thermoelectric Generators (RTGs). Due to budgetary constraints, the Advanced Stirling Radioisotope Generator (ASRG) was canceled in the fall of 2013. Over the past year a joint study by NASA and the Department of Energy (DOE) called the Nuclear Power Assessment Study (NPAS) recommended that Stirling technologies continue to be explored. During the mission studies of the NPAS, spare SRGs were sometimes required to meet mission power system reliability requirements. This led to an additional mass penalty and increased isotope consumption levied on certain SRG-based missions. In an attempt to remove the spare power system, a new generator architecture is considered, which could increase the reliability of a Stirling generator and provide a more fault-tolerant power system. This new generator called the Modular Stirling Radioisotope Generator (MSRG) employs multiple parallel Stirling convertor/controller strings, all of which share the heat from the General Purpose Heat Source (GPHS) modules. For this design, generators utilizing one to eight GPHS modules were analyzed, which provided about 50 to 450 W of direct current (DC) to the spacecraft, respectively. Four Stirling convertors are arranged around each GPHS module resulting in from 4 to 32 Stirling/controller strings. The convertors are balanced either individually or in pairs, and are radiatively coupled to the GPHS modules. Heat is rejected through the housing/radiator, which is similar in construction to the ASRG. Mass and power analysis for these systems indicate that specific power may be slightly lower than the ASRG and similar to the Multi-Mission Radioisotope Thermoelectric Generator (MMRTG). However, the reliability should be significantly increased compared to ASRG.

Modules↗

System statistical reliability model and analysis

A digital computer code was developed to simulate the time-dependent behavior of the 5-kwe reactor thermoelectric system. The code was used to determine lifetime sensitivity coefficients for a number of system design parameters, such as thermoelectric module efficiency and degradation rate, radiator absorptivity and emissivity, fuel element barrier defect constant, beginning-of-life reactivity, etc. A probability distribution (mean and standard deviation) was estimated for each of these design parameters. Then, error analysis was used to obtain a probability distribution for the system lifetime (mean = 7.7 years, standard deviation = 1.1 years). From this, the probability that the system will achieve the design goal of 5 years lifetime is 0.993. This value represents an estimate of the degradation reliability of the system.

Lekach, V. S.↗

A Systems Engineering Analysis of National Ignition Facility Industrial Controls Systems and Safety Interlock Systems Remote Input/Output Networking Migration from ControlNet to EtherNet/IP

The ControlNet industrial communications protocol and modules used in the Industrial Control System (ICS) and Safety Interlock System (SIS) at the National Ignition Facility (NIF) are no longer necessary and the ICS and SIS would be better served by migrating the communications structure to use EtherNet/Industrial Protocol (IP) and EtherNet bridge modules instead. By the admission of the vendor of ControlNet hardware, Rockwell Automation, in literature by Bill Petro [1], “Moving forward, customers will be able to optimize their asset utilization better using EtherNet/IP protocol than with ControlNet.” The NIF is one of the key elements of the Inertial Confinement Fusion (ICF) program at Lawrence Livermore National Laboratory (LLNL), a federally funded research and development center (FFRDC). The NIF contains the systems and provides the operational capacity to perform ICF, high energy density (HED), and discovery science experiments utilizing 192 individual beamlines, a host of diagnostics, and all the industrial systems required to facilitate these beamlines and diagnostics. The industrial systems are governed by the ICS and SIS, with the ICS providing control and the SIS providing monitoring and permissives. Construction on the NIF began in 1997 and was certified complete in 2009 and, as a result, the ICS and SIS were developed during this time using the tools that were available then. This includes the communications structure and protocols for these systems, much of which was, and still is, ControlNet. ControlNet, particularly during the time that the ICS and SIS were being built, has several attractive features. ControlNet hardware is exclusive to Rockwell Automation, which was the automation hardware chosen for the ICS and SIS. One feature that could be considered an advantage or a disadvantage depending on the communication needs of the system is that ControlNet also utilizes no active network components, excluding repeaters which are not always necessary. According to the architect of the ICS system at the NIF, Gordon Lau, one of the most attractive features of the ControlNet protocol during development of the ICS and SIS was that it is deterministic, providing timing of data transfer that is executed exactly as it is defined by the developer.

42 ENGINEERING↗

Expressions Module for the Satellite Orbit Analysis Program

The Expressions Module is a software module that has been incorporated into the Satellite Orbit Analysis Program (SOAP). The module includes an expressions- parser submodule built on top of an analytical system, enabling the user to define logical and numerical variables and constants. The variables can capture output from SOAP orbital-prediction and geometric-engine computations. The module can combine variables and constants with built-in logical operators (such as Boolean AND, OR, and NOT), relational operators (such as >, <, or =), and mathematical operators (such as addition, subtraction, multiplication, division, modulus, exponentiation, differentiation, and integration). Parentheses can be used to specify precedence of operations. The module contains a library of mathematical functions and operations, including logarithms, trigonometric functions, Bessel functions, minimum/ maximum operations, and floating- point-to-integer conversions. The module supports combinations of time, distance, and angular units and has a dimensional- analysis component that checks for correct usage of units. A parser based on the Flex language and the Bison program looks for and indicates errors in syntax. SOAP expressions can be built using other expressions as arguments, thus enabling the user to build analytical trees. A graphical user interface facilitates use.

Edmonds, Karina↗

Development of a 32-bit UNIX-based ELAS workstation

A mini/microcomputer UNIX-based image analysis workstation has been designed and is being implemented to use the Earth Resources Laboratory Applications Software (ELAS). The hardware system includes a MASSCOMP 5600 computer, which is a 32-bit UNIX-based system (compatible with AT&T System V and Berkeley 4.2 BSD operating system), a floating point accelerator, a 474-megabyte fixed disk, a tri-density magnetic tape drive, and an 1152 by 910 by 12-plane color graphics/image interface. The software conversion includes reconfiguring the ELAs driver Master Task, recompiling and then testing the converted application modules. This hardware and software configuration is a self-sufficient image analysis workstation which can be used as a stand-alone system, or networked with other compatible workstations.

Spiering, Bruce A.↗

The Evolution of Volatile Memory Forensics

The collection and analysis of volatile memory is a vibrant area of research in the cybersecurity community. The ever-evolving and growing threat landscape is trending towards fileless malware, which avoids traditional detection but can be found by examining a system’s random access memory (RAM). Additionally, volatile memory analysis offers great insight into other malicious vectors. It contains fragments of encrypted files’ contents, as well as lists of running processes, imported modules, and network connections, all of which are difficult or impossible to extract from the file system. For these compelling reasons, recent research efforts have focused on the collection of memory snapshots and methods to analyze them for the presence of malware. However, to the best of our knowledge, no current reviews or surveys exist that systematize the research on both memory acquisition and analysis. We fill that gap with this novel survey by exploring the state-of-the-art tools and techniques for volatile memory acquisition and analysis for malware identification. For memory acquisition methods, we explore the trade-offs many techniques make between snapshot quality, performance overhead, and security. For memory analysis, we examined the traditional forensic methods used, including signature-based methods, dynamic methods performed in a sandbox environment, as well as machine learning-based approaches. We summarize the currently available tools, and suggest areas for more research.

Nyholm, Hannah↗

Near Real-Time Global Composition Forecasts at 25km Horizontal Resolution

We present a new high-resolution global composition forecast system produced by NASA's Global Modeling and Assimilation Office. The NASA Goddard Earth Observing System (GEOS) model has been expanded to provide global near-real-time 5-day forecasts of atmospheric composition at unprecedented horizontal resolution of 0.25 degrees (~25 km). This composition forecast system (GEOS-CF) system combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12) to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). Satellite observations are assimilated into the system for improved representation of weather and smoke.

Knowland, K. Emma↗

Near Real-Time Air Quality Forecasts Using the NASA GEOS Model

We present a new high-resolution global composition forecast system produced by NASA's Global Modeling and Assimilation Office. The NASA Goddard Earth Observing System (GEOS) model has been expanded to provide global near-real-time 5-day forecasts of atmospheric composition at unprecedented horizontal resolution of 0.25 degrees (~25 km). This composition forecast system (GEOS-CF) system combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12) to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). Satellite observations are assimilated into the system for improved representation of weather and smoke.

Knowland, K. Emma↗

Near Real-Time Air Quality Forecasts Using the NASA GEOS Model

We present a new high-resolution global composition forecast system produced by NASA's Global Modeling and Assimilation Office. The NASA Goddard Earth Observing System (GEOS) model has been expanded to provide global near-real-time 5-day forecasts of atmospheric composition at unprecedented horizontal resolution of 0.25 degrees (~25 km). This composition forecast system (GEOS-CF) system combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12) to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). Satellite observations are assimilated into the system for improved representation of weather and smoke.

Knowland, K. Emma↗

Air Pollution Forecasts Using the NASA GEOS Model: A Unified Tool from Local to Global Scales

We present a new high-resolution global composition forecast system produced by NASA's Global Modeling and Assimilation Office. The NASA Goddard Earth Observing System (GEOS) model has been expanded to provide global near-real-time 5-day forecasts of atmospheric composition at unprecedented horizontal resolution of 0.25 degrees (~25 km). This composition forecast system (GEOS-CF) system combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12) to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). Satellite observations are assimilated into the system for improved representation of weather and smoke.

Knowland, K. Emma↗

Technoeconomic Analysis of Changing PV System Layout and Convection Heat Transfer

This work includes analysis of potential economic improvements for PV systems for changing system parameters such as ground coverage ratio that alter the convective cooling consideration on PV modules through a newly proposed convective curve fit. Accounting for the spatial layout of the system in the convection heat transfer calculations allows for more accuracy in convective cooling load and subsequent module temperature calculations. The changing heat transfer considerations can be shown to improve system LCOE along with improved incident irradiance from increased row spacing despite the additional system costs incurred with increased module spacing. State-level analyses show that the impact of decreasing system GCR is greatest for climates with cold average annual ambient temperatures and moderate to high average annual wind speeds. Further waterfall analysis of changing system parameters reveals that the changing heat transfer dynamics have a non-negligible impact on system LCOE when compared to the changes in incident irradiance that serve as the primary driver of annual energy performance changes.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗

Reactive, Safe Navigation for Lunar and Planetary Robots

When humans return to the moon, Astronauts will be accompanied by robotic helpers. Enabling robots to safely operate near astronauts on the lunar surface has the potential to significantly improve the efficiency of crew surface operations. Safely operating robots in close proximity to astronauts on the lunar surface requires reactive obstacle avoidance capabilities not available on existing planetary robots. In this paper we present work on safe, reactive navigation using a stereo based high-speed terrain analysis and obstacle avoidance system. Advances in the design of the algorithms allow it to run terrain analysis and obstacle avoidance algorithms at full frame rate (30Hz) on off the shelf hardware. The results of this analysis are fed into a fast, reactive path selection module, enforcing the safety of the chosen actions. The key components of the system are discussed and test results are presented.

Utz, Hans↗

Time-domain Modulation of HD 189733 Activities by Its Planet

Star–planet interaction can be studied by analyzing exoplanetary orbit and stellar rotation modulations of the transit emissions from exoplanetary systems. Here we carry out a time-domain analysis of the multiband activities of the HD 189733 star–planet system observed in X-ray, atomic lines, and broadband spectra reported in the literature. We find that the number of activities occuring at beat angles (of the planetary orbit and the stellar rotation) concentrating on a sector with a width of 108° are significantly larger than expected from a uniform distribution of activities, which indicates the existence of a major stellar active magnetic field region. The concentration of activities in this active magnetic field region shows their possible origins from the magnetic field interaction between HD 189733 and its close planet HD 189733 b.

47 OTHER INSTRUMENTATION↗

Analysis of Alternative Core Designs for Fission Surface Power Capability Demonstration Mission (V.1.0)

NASA’s Space Technology Mission Directorate (STMD) intends to demonstrate a 10 kWe fission surface power (FSP) system on the surface of the Moon as part of a Capability Demonstration Mission. STMD tasked a joint NASA-DOE team to ‘outline an FSP reactor concept that can be readied for 2027 launch,’ and serves ‘as a pathfinder for future power modules for Mars.’ Tables 1 and 2 respectively list FSP performance requirements and design guidance provided for the study. DOE is the leading agency for the reactor module, reactor controls and radiation shielding, and shares joint responsibility for the overall FSP system. This report summarizes an analysis of alternative reactor classes and shielding configurations carried out by the DOE national laboratories. Representative reactor and shielding configurations were based on heritage and are in alignment with the industry initiatives. This report presents no recommendations on the appropriate choice of fuel or class of reactor that NASA should pursue. Instead the focus here is to provide a summary and findings of analyses carried out by DOE national laboratory personnel.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

FARM User Guidance and Instructions

The FARM (Feasible Actuator Range Modifier) module is a component of the RAVEN-based FORCE framework for the analysis of Integrated Energy Systems (IES). FARM aids HERON in the solution of the power dispatch problem by evaluating feasible set-point signals to be issued to the control systems of the different IES unit components. Set-points need to satisfy limits on both production variables (i.e., the variables to be optimized such as the electrical power, etc.) and process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.). To enforce all these limits, a two-stage approach is adopted. First, the power dispatcher algorithm in HERON module estimates set-points that meet the constraints on the production variables, e.g., power levels and power ramp rate limits. These constraints are called explicit constraints. Then, if necessary, FARM adjusts these set-points to ensure the respect of the limits on the process variables of interest, given the knowledge of the system dynamics acquired through machine learning algorithms. These constraints are called implicit constraints. From this standpoint, FARM constitutes a bridge between the HERON power dispatcher that adopts a simplified description of the IES unit (low-resolution physics) and the HYBRID high-fidelity models (high-resolution physics). In this report, the general workflow and the software requirements of FARM module are summarized, and the detailed instructions for installing FARM software, running built-in example cases, deriving Linear Parameter-Varying (LPV) state-space models, and using FARM for user-defined power dispatch problems are provided.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

FARM supervisory capabilities for thermal energy storage

The FARM (Feasible Actuator Range Modifier) module is a component of the RAVEN-based FORCE framework for the analysis of Integrated Energy Systems (IES). FARM aids HERON in the solution of the power dispatch problem by evaluating feasible set-point signals to be issued to the control systems of the different IES unit components. Set-points need to satisfy limits on both production variables (i.e., the variables to be optimized such as the electrical power, etc.) and process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.). To enforce all these limits, a two-stage approach is adopted. First, the power dispatcher algorithm in HERON module estimates set-points that meet the constraints on the production variables, e.g., power levels and power ramp rate limits. These constraints are called explicit constraints. Then, if necessary, FARM adjusts these set-points to ensure the respect of the limits on the process variables of interest, given the knowledge of the system dynamics acquired through machine learning algorithms. These constraints are called implicit constraints. From this standpoint, FARM constitutes a bridge between the HERON power dispatcher that adopts a simplified description of the IES unit (low-resolution physics) and the HYBRID high-fidelity models (high-resolution physics). In this report, an overview of the major capabilities of the latest release of FARM is provided, along with a summary of the tool demonstration campaign conducted at the Dynamic Energy Technology and Integration Laboratory (DETAIL) facility. These results assess the performance of the control system architecture embedding FARM both as a Validator of the HERON power dispatcher and as a real time Supervisory control scheme. Additionally, the report outlines the areas that FARM might benefit from, along with proposed solutions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Manned space flight nuclear system safety. Volume 3: Reactor system preliminary nuclear safety analysis. Part 2A: Accident model document, appendix

The detailed abort sequence trees for the reference zirconium hydride (ZrH) reactor power module that have been generated for each phase of the reference Space Base program mission are presented. The trees are graphical representations of causal sequences. Each tree begins with the phase identification and the dichotomy between success and failure. The success branch shows the mission phase objective as being achieved. The failure branch is subdivided, as conditions require, into various primary initiating abort conditions.

Source record↗