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Advanced instrumentation: Technology database enhancement, volume 4, appendix G

The purpose of this task was to add to the McDonnell Douglas Space Systems Company's Sensors Database, including providing additional information on the instruments and sensors applicable to physical/chemical Environmental Control and Life Support System (P/C ECLSS) or Closed Ecological Life Support System (CELSS) which were not previously included. The Sensors Database was reviewed in order to determine the types of data required, define the data categories, and develop an understanding of the data record structure. An assessment of the MDSSC Sensors Database identified limitations and problems in the database. Guidelines and solutions were developed to address these limitations and problems in order that the requirements of the task could be fulfilled.

Source record↗

EUVE Guest Observer Program Handbook: Extreme Ultraviolet Explorer Guest Observer Documentation: Use with Addendum 1 for 1995 - Appendix G

The Extreme Ultraviolet Explorer (EUVE) is a NASA explorer-class satellite mission devoted entirely to observations in the wavelength range from 70 to 760 Angstroms. The science payload incorporates five separate instruments: four photometric imaging systems and a three-channel EUV spectrometer. During the first phase of the mission, the imaging instruments were used to conduct a complete sky survey in four different bands in the EUV. The survey results are available to the scientific community in the first EUVE sky survey bright source list and the first EUVE all-sky catalog. The second part of the mission is being conducted by NASA as a Guest Observer program, for which pointed spectroscopic observations are conducted for guest scientists under proposals submitted to NASA and supported by the EUVE Guest Observer Center at Berkeley. The mission lifetime will extend through at least a third year of observations. Further extensions of the EUVE mission will be partially contingent upon a review process conducted in September of 1994. To support an extended mission, please contact the chair of the EUVE User 's Committee1 or the EUVE Project Office (address below). The EUVE Guest Observer (EGO) Program is supported by the EUVE Guest Observer Center (EGO Center) at the Center for Extreme Ultraviolet Astrophysics (CEA), at the University of California, Berkeley. The policies of the EGO Program and specified in the NRA. This Handbook is produced by the EGO Center as a guide to choosing appropriate targets for observation and preparing proposals. The rest of this chapter gives a broad overview of the EUVE mission and the EGO Center.

EUVE↗

NuScale Pressure and Temperature Limits Methodology Using Finite Element Analysis

Per 10 CFR 50 Appendix G, the pressure-temperature (P-T) limits curves and minimum temperature must be established to provide adequate margins for ferritic pressure-retaining components of the reactor coolant pressure boundary; this is to protect against brittle failure during any normal operating conditions, including anticipated operational occurrences and system hydrostatic tests, to which the pressure boundary may be subjected over its service lifetime. Specifically, ASME Code Section XI Appendix G procedures must be used for P-T limits calculation considering the pressure and temperature at various operating transient conditions. However, the elastic fracture mechanics solutions in Section XI are only suitable for cylindrical reactor pressure vessel (RPV) beltline without geometric discontinuities. Hence, these solutions are not suitable for postulated flaws near the core support blocks attached to the NuScale RPV inside surface, which is part of the beltline. As a result, NuScale has used finite element analysis to calculate thermal stress and stress intensity factor for the postulated flaws. The solutions using finite-element analysis have been validated using the formulations for straight cylinders for both axial and circumferential flaws. In addition, special considerations are given to the RPV beltline nil-ductility transition temperature (RTNDT) due to neutron irradiation occurring at lower temperatures than conventional plants. The paper summarizes the methodology and finite-element models used to develop P-T limits curves for NuScale RPV at the end of its 60-year design life.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Human Landing System (HLS) Program Extravehicular Activity (EVA) Compatibility Interface Requirements Document (IRD)

The purpose of this document is to establish a set of EVA compatibility design requirements for the HLS Program. This document contains the fundamental information required for building hardware compatible with suited EVA flight crewmembers to perform EVAs. Compatibility requirements are located in section 3.0 with a gravity field applicability table provided in APPENDIX G, Human Landing System Program Applicability Matrix. Each HLS Provider will use the EHP-provided matrix in Appendix G to assess applicability to the awarded mission provider on a per-mission basis. Providers will negotiate applicability with EHP, and this will be documented in the appropriate Annex (reference section 2.2)

Christine N Kovich↗

ANSI/ASHRAE/IES Standard 90.1-2022 Performance Rating Method Reference Manual

This document is intended to be a reference manual for the Appendix G Performance Rating Method (PRM) of ANSI/ASHRAE/IES Standard 90.1-2022 (Standard 90.1-2022). The PRM can be used to demonstrate compliance with the standard and to rate the energy efficiency of commercial and high-rise residential buildings with designs that exceed the requirements of Standard 90.1. Use of the PRM for demonstrating compliance with Standard 90.1 was a new feature of ANSI/ASHRAE/IES Standard 90.1-2016 (Standard 90.1-2016). The procedures and processes described in the PRM reference manual (PRM-RM) are designed to provide consistency and accuracy by filling in gaps and providing additional details needed by users of the PRM.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Columbia Accident Investigation Board Report. Volume Five

Volume V of the Report contains appendices that were not cited in VolumeI. These consist of documents produced by NASA and other organizations, which were provided to the Columbia Accident Investigation Board in support of its inquiry into the February 1, 2003 destruction of the Space Shuttle Columbia The contents include:. Appendix G.1 Requirements and Procedures for Certification of Flight Readiness; Appendix G.2 Appendix R, Space Shuttle Program Contingency Action Plan; Appendix G.3 CAIB Charter, with Revisions; Appendix G.4 Group 1 Matrix Brief on Maintenance, Material, and Management; Appendix G.5 Vehicle Data Mapping(VDM) Team Final Report, Jun 13, 2003; Appendix G.6 SRB Working Group Presentation to CAIB; Appendix G. 7 Starfire Team Final Report, Jun 3, 2003; Appendix G.8 Using the Data and Observations from Flight STS-107, Executive Summary; Appendix G.9 Contracts, Incentives, and Safety/Technical Excellence; Appendix G.10 Detailed Summaries: Rogers Commission Report, ASAP Report, SIAT Report; Appendix G.11 Foam Application and Production Chart; Appendix G.12 Crew Survivability Report; and Appendix G.12 Aero/Aerothermal/ Thermal/Structures Team FinalReport, August 6, 2003.

CAIB (COLUMBIA ACCIDENT INVESTIGATION BOARD)↗

UAM Vision Concept of Operations (ConOps) UAM Maturity Level (UML) 4

This Vision ConOps is intended as a foundation to engage members of the UAM community and provide a consensus on the future vision of UAM operations. It provides a concept for more detailed discussion and a basis for the exploration of ideas using a common framework to inform the continued development and integration of UAM as part of the broader transportation system. Advanced Air Mobility (AAM) encompasses a range of innovative aviation technologies (small drones, electric aircraft, automated air traffic management, etc.) that are transforming aviation’s role in everyday life, including the movement of goods and people. Urban Air Mobility (UAM) represents one of the most exciting and complex AAM concepts with highly automated aircraft, providing commercial services to the public over densely populated cities. This concept has generated tremendous interest and industry investment. UAM envisages a future in which advanced technologies and new operational procedures enable practical, cost-effective air travel as an integral mode of transportation in metropolitan areas. It represents one of the most exciting and complex AAM concepts with highly automated aircraft providing commercial services to the public over densely populated cities. For this reason, the National Aeronautics and Space Administration (NASA) selected UAM as the initial goal of its AAM efforts and the focus of this Vision Concept of Operations (ConOps) document. UAM Community Vision ConOps: This Vision ConOps effort was led by experts from NASA’s Aeronautics Research Mission Directorate (ARMD) in collaboration with the Federal Aviation Administration (FAA) and Deloitte’s Ecosystem Advisory Group (a cohort of advisers with aviation, aerospace, and regulatory expertise). To develop this Vision ConOps, NASA, FAA, and Deloitte built upon the current body of aeronautical research and consulted with more than 100 stakeholder organizations. This UAM community includes entities ranging from legacy aviation leaders to innovators and new market entrants. Stakeholders consulted included the federal government, state and local government, aerospace original equipment manufacturers (OEMs), local transportation organizations, prospective UAM operators, academia, industry standards-setting bodies, airports, service suppliers, and others (as described in Appendix G). This input was captured through the following methods: • A series of more than two dozen interviews with industry experts, federal regulators, state and local governments, and industry trade groups provided insight into the challenges of UAM integration into the National Airspace System (NAS), as well as technology developments and a variety of perspectives as to how UAM systems will integrate. • A series of two-day community workshops enabling active, detailed engagement of nearly 100 industry, academic, federal, and state stakeholder individuals. These workshops, hosted by NASA and Deloitte, explored UAM concepts in detail, and stakeholders were invited to collaboratively analyze and propose solutions to some of the greatest conceptual challenges behind UAM at an intermediate state. • A review of more than 160 sources of UAM literature from across government, industry, and academia, which are listed in Appendix H. • The public sharing of workshop input and document drafts for review and input across the UAM community. Feedback in the form of more than 1,000 comments and inputs on the document was received from industry groups, individual companies, academia, and government (federal, state, and local), among others. Although effort was made to incorporate inputs from across the UAM stakeholder group, not all comments could ultimately be incorporated in this version. The team resolved conflicting comments or ideas while maintaining consistency with the known direction of regulators and ensuring the document was coherent and consistent. It is recognized that this is a rapidly evolving area and that concepts will likely change over time; as such, this Vision ConOps is a living document and is expected to evolve as concepts mature. The ConOps does, however, provide a vision of UAM concepts and solutions based on the broad insights from across the UAM stakeholder community at the time of its publication and is intended to serve as a UAM North Star for continued research and development of UAM. As a broad Vision ConOps, is not a detailed engineering document; rather, it focuses primarily on outlining a broad, high-level vision across all aspects of a UAM transportation system.

Urban Air Mobility↗

Chilled water temperature set-point reset based on outdoor air temperature and its cooling energy performance in an office building

Here, in this study, the cooling energy performance of two strategies for controlling ChWT (chilled water temperature) are compared: the conventional control strategy of constantly fixing ChWT and the OAT (outdoor air temperature) compensation control strategy that adjusts ChWT according to the changes in OAT. OAT compensation control strategy was modeled and realized based on Appendix G of ASHRAE Standard 90.1. It was confirmed that applying OAT compensation control strategy can significantly reduce chiller energy consumption, which accounts for the largest portion of total cooling energy consumption. It was found that the difference in total cooling energy consumption between applying the conventional control of constantly fixing ChWT to 6 °C and applying the OAT compensation control was approximately 8 % and 3 % during spring (March to May) and summer (June to August), respectively. Additionally, during the fall (September–November) period, about 7 % of total cooling energy consumption could be saved.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

pnnl/ruleset-checking-tool

The Ruleset Checking Tool (RCT) will be a tool for verifying implementation of a ruleset (such as ASHRAE Standard 90.1 Appendix G) in building performance modeling (BPM) tools.

McNeill, James↗

ANSI/ASHRAE/IES Standard 90.1-2019 Performance Rating Method Reference Manual

This document is intended to be a reference manual for the Appendix G Performance Rating Method (PRM) of ANSI/ASHRAE/IES Standard 90.1-2019 (Standard 90.1-2019). The PRM can be used to demonstrate compliance with the standard and to rate the energy efficiency of commercial and high-rise residential buildings with designs that exceed the requirements of Standard 90.1. Use of the PRM for demonstrating compliance with Standard 90.1 was a new feature of ANSI/ASHRAE/IES Standard 90.1-2016 (Standard 90.1-2016). The procedures and processes described in the PRM reference manual (PRM-RM) are designed to provide consistency and accuracy by filling in gaps and providing additional details needed by users of the PRM.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence 8 - Raw Data

Sequences 8 and 9: Downwind Sonics (F,P) and Downwind Sonics Parked (P) This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speed ranged from 5 m/s to 25 m/s. Yaw angles of 0° to 60° were achieved. The blade tip pitch was 3°. The rotor rotated at 72 RPM during Sequence 8, but it was parked during Sequence 9. Blade pressure measurements were collected. The five-hole probes were removed and the plugs were installed. Plastic tape 0.03-mm-thick was used to smooth the interface between the plugs and the blade. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to –99999.99 Nm. The teeter link load cell was pre-tensioned to 40,000 N. During post-processing, the probe channels were set to read -99999.99. Sonic anemometers were mounted on a strut downwind of the turbine. The strut was mounted to the T-frame, which was rotated to align the anemometers aft of the 9% and 49% radius locations at hub height. Because of this configuration, the tunnel balance data are considered invalid. Sequence 9 was designed to compare the downwind sonic anemometer readings with the upwind sonic anemometers without interference from the turbine. The rotor was parked with the instrumented blade at 0° azimuth. All pressure measurements obtained in Sequence 9 are invalid because sufficient time for temperature stabilization did not occur, thus all associated data values were flagged as not applicable by setting the measured values in the data file to 0.0000 Pa. This test is further described in Appendix G.

17 WIND ENERGY↗

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence 9 - Raw Data

Sequences 8 and 9: Downwind Sonics (F,P) and Downwind Sonics Parked (P) This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speed ranged from 5 m/s to 25 m/s. Yaw angles of 0° to 60° were achieved. The blade tip pitch was 3°. The rotor rotated at 72 RPM during Sequence 8, but it was parked during Sequence 9. Blade pressure measurements were collected. The five-hole probes were removed and the plugs were installed. Plastic tape 0.03-mm-thick was used to smooth the interface between the plugs and the blade. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to –99999.99 Nm. The teeter link load cell was pre-tensioned to 40,000 N. During post-processing, the probe channels were set to read -99999.99. Sonic anemometers were mounted on a strut downwind of the turbine. The strut was mounted to the T-frame, which was rotated to align the anemometers aft of the 9% and 49% radius locations at hub height. Because of this configuration, the tunnel balance data are considered invalid. Sequence 9 was designed to compare the downwind sonic anemometer readings with the upwind sonic anemometers without interference from the turbine. The rotor was parked with the instrumented blade at 0° azimuth. All pressure measurements obtained in Sequence 9 are invalid because sufficient time for temperature stabilization did not occur, thus all associated data values were flagged as not applicable by setting the measured values in the data file to 0.0000 Pa. This test is further described in Appendix G.

17 WIND ENERGY↗

Measuring Impact: Evaluating Thermal Zoning Simplification on Energy Efficiency Measures Analysis

Building Energy Modeling (BEM) is a versatile tool for designing, retrofitting, ensuring code compliance, obtaining certifications, qualifying for incentives, and enabling real-time building control. However, capturing all the details of building geometry for thermal zoning can be time-consuming, costly, and sometimes computationally challenging. As a result, modelers have been applying zoning simplification based on factors such as space functions and internal loads, as well as relying on their experience and judgment while adhering to zoning rules outlined in industry standards. Despite the prevalence of this common practice, a notable gap exists in the literature regarding studies quantifying the influence of simplified thermal zoning on the evaluation of Energy Efficiency Measures (EEMs). Recognizing this gap, this paper seeks to contribute to the field by enhancing the understanding of how the simplification of thermal zoning influences the evaluation of EEMs against a baseline design. The study utilized a medium office prototype model with a detailed floor plan featuring over 20 zones per floor covering diverse functional spaces with varying internal loads and occupancy schedules. A standard thermal zoning strategy outlined in ASHRAE Standard 90.1 Appendix G was employed as the simplified zoning method. This strategy condenses the zoning into a core zone and four perimeter zones per floor. It was compared with the detailed zoning approach, which involves one zone per space. Common Energy EEMs, such as enhanced envelope, high-efficiency appliances and equipment, and HVAC controls, were individually implemented and evaluated. The results indicate that the performance comparison between the two zoning methods varies depending on the type of measures considered. Basic measures, such as adding wall insulation, demonstrate similar energy impacts, while advanced HVAC control measures, such as static pressure reset, exhibit a more substantial difference that cannot be overlooked.

Xie, Jiarong↗

Time warp operating system version 2.7 internals manual

The Time Warp Operating System (TWOS) is an implementation of the Time Warp synchronization method proposed by David Jefferson. In addition, it serves as an actual platform for running discrete event simulations. The code comprising TWOS can be divided into several different sections. TWOS typically relies on an existing operating system to furnish some very basic services. This existing operating system is referred to as the Base OS. The existing operating system varies depending on the hardware TWOS is running on. It is Unix on the Sun workstations, Chrysalis or Mach on the Butterfly, and Mercury on the Mark 3 Hypercube. The base OS could be an entirely new operating system, written to meet the special needs of TWOS, but, to this point, existing systems have been used instead. The base OS's used for TWOS on various platforms are not discussed in detail in this manual, as they are well covered in their own manuals. Appendix G discusses the interface between one such OS, Mach, and TWOS.

Source record↗

FORTRAN program for analyzing ground-based radar data: Usage and derivations, version 6.2

A postflight FORTRAN program called 'radar' reads and analyzes ground-based radar data. The output includes position, velocity, and acceleration parameters. Air data parameters are also provided if atmospheric characteristics are input. This program can read data from any radar in three formats. Geocentric Cartesian position can also be used as input, which may be from an inertial navigation or Global Positioning System. Options include spike removal, data filtering, and atmospheric refraction corrections. Atmospheric refraction can be corrected using the quick White Sands method or the gradient refraction method, which allows accurate analysis of very low elevation angle and long-range data. Refraction properties are extrapolated from surface conditions, or a measured profile may be input. Velocity is determined by differentiating position. Accelerations are determined by differentiating velocity. This paper describes the algorithms used, gives the operational details, and discusses the limitations and errors of the program. Appendices A through E contain the derivations for these algorithms. These derivations include an improvement in speed to the exact solution for geodetic altitude, an improved algorithm over earlier versions for determining scale height, a truncation algorithm for speeding up the gradient refraction method, and a refinement of the coefficients used in the White Sands method for Edwards AFB, California. Appendix G contains the nomenclature.

Haering, Edward A., Jr.↗