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At least 109 records · Page 6

Wind Information Uplink to Aircraft Performing Interval Management Operations

Interval Management (IM) is an ADS-B-enabled suite of applications that use ground and flight deck capabilities and procedures designed to support the relative spacing of aircraft (Barmore et al., 2004, Murdoch et al. 2009, Barmore 2009, Swieringa et al. 2011; Weitz et al. 2012). Relative spacing refers to managing the position of one aircraft to a time or distance relative to another aircraft, as opposed to a static reference point such as a point over the ground or clock time. This results in improved inter-aircraft spacing precision and is expected to allow aircraft to be spaced closer to the applicable separation standard than current operations. Consequently, if the reduced spacing is used in scheduling, IM can reduce the time interval between the first and last aircraft in an overall arrival flow, resulting in increased throughput. Because IM relies on speed changes to achieve precise spacing, it can reduce costly, low-altitude, vectoring, which increases both efficiency and throughput in capacity-constrained airspace without negatively impacting controller workload and task complexity. This is expected to increase overall system efficiency. The Flight Deck Interval Management (FIM) equipment provides speeds to the flight crew that will deliver them to the achieve-by point at the controller-specified time, i.e., assigned spacing goal, after the target aircraft crosses the achieve-by point (Figure 1.1). Since the IM and target aircraft may not be on the same arrival procedure, the FIM equipment predicts the estimated times of arrival (ETA) for both the IM and target aircraft to the achieve-by point. This involves generating an approximate four-dimensional trajectory for each aircraft. The accuracy of the wind data used to generate those trajectories is critical to the success of the IM operation. There are two main forms of uncertainty in the wind information used by the FIM equipment. The first is the accuracy of the forecast modeling done by the weather provider. This is generally a global environmental prediction obtained from a weather model such as the Rapid Refresh (RAP) from the National Centers for Environmental Prediction (NCEP). The weather forecast data will have errors relative to the actual, or truth, winds that the aircraft will encounter. The second source of uncertainty is that only a small subset of the forecast data can be uplinked to the aircraft for use by the FIM equipment. This results in loss of additional information. The Federal Aviation Administration (FAA) and RTCA are currently developing standards for the communication of wind and atmospheric data to the aircraft for use in NextGen operations. This study examines the impact of various wind forecast sampling methods on IM performance metrics to inform the standards development.

Ahmad, Nashat N.↗

The HyRIGHT Project: 700 bar Hydrogen Refueling Interface for Gaseous Heavy-Duty Trucks

Heavy duty truck fueling places additional constraints on the station. The HyRIGHT project was developed to evaluate a subset of key areas around precooling, communications, and safety risks that aims to:  Utilize a dynamic model that includes the relevant station components and vehicle to develop an optimized precooling strategy based on initial precooling status, real time communications that can support fueling protocol development.  Perform a techno economic cost assessment (TEA) related to effects of precooling including station storage and efficiency effects.  Develop a Cyber Vulnerability assessment and framework for refueling of HD vehicles with station communications.  Disseminate the results in support of the HD fueling protocol development to the relevant standards development organizations.

JAMES, Charles W.↗

Optimizing subsystem test programs

The goal of reduction of space system costs is pursued in the areas of standardization of subsystem test requirements as well as overall subsystem test program resource requirements. A number of standard components are being developed by NASA. The rationale for the various environmental tests applicable to future missions and launch vehicles is discussed. The need for and approach to developing standard component specifications is presented. In addition, a method for reduction of test expenditures utilizing indexes of mission effect and hardware history as indicators of test requirements is proposed.

Meyer, W. H.↗

Development of Standardized Lunar Regolith Simulant Materials

Lunar exploration requires studies using standardized testing procedures. Previous lunar simulants focused on physical aspects of the lunar regolith. Renewed lunar exploration requires standardized lunar regolith simulant (SLRS) materials that simulate the physical, chemical, and mineralogical properties of the regolith [l]. A root simulant models an end-member, and a derivative is formed by addition of material [2]. The 2005 Workshop recommended a low-Ti mare basalt and a high-Ca highland anorthosite set of roots. Derivatives involve addition of ilmenite and glassy agglutinates [3]. An ideal SLRS material is homogeneous. Geochemical standards are finely-ground to reduce chemical variability, but lunar simulants have a grain size variation and mineralogy that must match the lunar regolith. The simulant homogeneity is monitored using major, minor, and trace element data of progressively smaller samples compared to bulk material. Both chemical and geotechnical properties depend on the contrast from grain to grain. The variability of simulant material is an inherent property that must be taken into account. Simulant production requires monitoring of adherence to simulant requirements and homogeneity during production. Quality control establishes a traceability to a master set of reference standards.

Carpenter, P.↗

Developing a Standard Method for Link-Layer Security of CCSDS Space Communications

Communications security for space systems has been a specialized field generally far removed from considerations of mission interoperability and cross-support in fact, these considerations often have been viewed as intrinsically opposed to security objectives. The space communications protocols defined by the Consultative Committee for Space Data Systems (CCSDS) have a twenty-five year history of successful use in over 400 missions. While the CCSDS Telemetry, Telecommand, and Advancing Orbiting Systems protocols for use at OSI Layer 2 are operationally mature, there has been no direct support within these protocols for communications security techniques. Link-layer communications security has been successfully implemented in the past using mission-unique methods, but never before with an objective of facilitating cross-support and interoperability. This paper discusses the design of a standard method for cryptographic authentication, encryption, and replay protection at the data link layer that can be integrated into existing CCSDS protocols without disruption to legacy communications services. Integrating cryptographic operations into existing data structures and processing sequences requires a careful assessment of the potential impediments within spacecraft, ground stations, and operations centers. The objective of this work is to provide a sound method for cryptographic encapsulation of frame data that also facilitates Layer 2 virtual channel switching, such that a mission may procure data transport services as needed without involving third parties in the cryptographic processing, or split independent data streams for separate cryptographic processing.

Biggerstaff, Craig↗

Orion GN and C Model Based Development: Experience and Lessons Learned

The Orion Guidance Navigation and Control (GN&C) team is charged with developing GN&C algorithms for the Exploration Flight Test One (EFT-1) vehicle. The GN&C team is a joint team consisting primarily of Prime Contractor (Lockheed Martin) and NASA personnel and contractors. Early in the GN&C development cycle the team selected MATLAB/Simulink as the tool for developing GN&C algorithms and Mathworks autocode tools as the means for converting GN&C algorithms to flight software (FSW). This paper provides an assessment of the successes and problems encountered by the GN&C team from the perspective of Orion GN&C developers, integrators, FSW engineers and management. The Orion GN&C approach to graphical development, including simulation tools, standards development and autocode approaches are scored for the main activities that the team has completed through the development phases of the program.

Jackson, Mark C.↗

Development of Standards for Nondestructive Evaluation of COPVs Used in Aerospace Applications

Composite OverWrapped Pressure Vessels (COPVs) are currently accepted by NASA based on design and qualification requirements and generally not verified by NDE for the following reasons: (1) Manufactures and end users generally do not have experience and validated quantitative methods of detecting flaws and defects of concern (1-a) If detected, the flaws are not adequately quantified and it is unclear how they may contribute to degradation in mechanical response (1-b) Carbon-epoxy COPVs also extremely sensitive to impact damage and impacts may be below the visible detection threshold (2) If damage is detected, this generally results in rejection since the effect on mechanical response is generally not known (3) NDE response has not generally been fully characterized, probability of detection (POD) established, and processes validated for evaluation of vessel condition as manufactured and delivered.

Waller, Jess M.↗

National Unmanned Aerial System Standardized Performance Testing and Rating (NUSTAR)

The overall objective of the NUSTAR Capability is to offer standardized tests and scenario conditions to assess performance of the UAS. The following are goals of the NU-STAR: 1. Create a prototype standardized tests and scenarios that vehicles can be tested against. 2. Identify key performance parameters of all UAS and their standardized measurement strategy. 3. Develop standardized performance reporting method (e.g., consumer report style) to assist prospective buyers. 4. Identify key performance metrics that could be used by judged towards overall safety of the UAS and operations. 5. If vehicle certification standard is made by a regulatory agency, the performance of individual UAS could be compared against the minimum requirement (e.g., sense and avoid detection time, stopping distance, kinetic energy, etc.).

Testing↗

Holistic and Pragmatic Standards Processes Enable Interdisciplinary Science

Open, interdisciplinary science inevitably relies heavily on standards. Standards are those often unseen agreements that we take for granted when systems and processes are working fine. Yet standards work is perpetual, laborious, and sometimes contentious, especially for standards to work across diverse disciplines. Standards development, maintenance, and implementation is a complex, ongoing socio-technical process. NASA has developed a progressively open science policy and strategy that calls for the establishment of a data standards process reaching across the five diverse divisions of the Science Mission Directorate. This is a delicate exercise. We, therefore, seek to apply a holistic yet pragmatic approach to developing and maintaining a standards process. We adopt an ecological philosophy that focuses on the interactions within the data ecosystem and how standards facilitate those interactions. We couple high-level analysis with on the ground experimentation. We began by 1) mapping information ecosystem components (e.g. data centers, missions, services, protocols, users), 2)establishing how the components interact (e.g. sharing (meta)data, funding, personnel exchange), and 3) modelling system dynamics (e.g. creation of products from multiple data centers, redundant processes, shared services). The goal is to apply understanding of the ecosystem to real world applications (e.g. planning a new mission, implementing new policy requirements, improving process efficiency, etc.). We have also conducted studies of historical standardization efforts, documenting lessons learned and cautionary tales. We then contrast this more abstract work with real examples. We reviewed and assessed multiple existing standards development processes both within and external to NASA. We now work to implement an initial test process which can be further optimized. We seek to define a consistent approach for assigning persistent identifiers for research objects, especially for the purposes of citation. The experience from this relatively ‘simple’ test case adds a pragmatic perspective on how researchers and engineers actually work. This presentation will review the details of this methodology, our initial findings, and how they might apply to other interdisciplinary standardization efforts.

Mark A Parsons↗

NASA Standards Inform Comfortable Car Seats

NASA developed standards, which included the neutral body posture (NBP), to specify ways to design flight systems that support human health and safety. Nissan Motor Company, with US offices in Franklin, Tennessee, turned to NASA's NBP research for the development of a new driver's seat. The 2013 Altima now features the new seat, and the company plans to incorporate the seats in upcoming vehicles.

Source record↗

NASA GeneLab RNASeq Consensus Pipeline: A Nextflow Implementation

The NASA GeneLab project (genelab.nasa.gov) seeks to accelerate space biology research through cataloging and democratizing omics data. Since raw omics data is largely inaccessible to non-bioinformaticians, GeneLab works with the scientific community to develop standard processing pipelines to generate and publish processed data. Unlike raw data, processed data has greater immediate value to a wide range of users with varying technical backgrounds and computational capabilities. Standardizing processing workflows is essential to match the pace of raw data generation, ensure reproducibility, and enable standardized processed data for comparison across datasets. Previously, GeneLab developed a standardized pipeline for processing RNAseq data, referred to as the ‘GeneLab RNAseq Consensus Pipeline (RCP)’, in collaboration with GeneLab’s Analysis Working Groups. The work presented here is a Nextflow implementation of GeneLab’s RCP that automates and accelerates data processing of RNASeq datasets hosted on GeneLab. In addition to the core data processing, the workflow also includes staging of GeneLab raw data and a robust verification and validation (V&V) program that runs after each processing step to identify errors in real-time, stop additional downstream computation, and preserve computational resources. The workflow, including the staging and V&V functionality, is open source for others to reuse and modify at https://github.com/nasa/GeneLab_Data_Processing/tree/master/RNAseq.

Jonathan Dejesus Oribello↗

NASA GeneLab RNASeq Consensus Pipeline: A Nextflow Implementation

The NASA GeneLab project (genelab.nasa.gov) seeks to accelerate space biology research through cataloging and democratizing omics data. Since raw omics data is largely inaccessible to non-bioinformaticians, GeneLab works with the scientific community to develop standard processing pipelines to generate and publish processed data. Unlike raw data, processed data has greater immediate value to a wide range of users with varying technical backgrounds and computational capabilities. Standardizing processing workflows is essential to match the pace of raw data generation, ensure reproducibility, and enable standardized processed data for comparison across datasets. Previously, GeneLab developed a standardized pipeline for processing RNAseq data, referred to as the ‘GeneLab RNAseq Consensus Pipeline (RCP)’, in collaboration with GeneLab’s Analysis Working Groups. The work presented here is a Nextflow implementation of GeneLab’s RCP that automates and accelerates data processing of RNASeq datasets hosted on GeneLab. In addition to the core data processing, the workflow also includes staging of GeneLab raw data and a robust verification and validation (V&V) program that runs after each processing step to identify errors in real-time, stop additional downstream computation, and preserve computational resources. The workflow, including the staging and V&V functionality, is open source for others to reuse and modify at https://github.com/nasa/GeneLab_Data_Processing/tree/master/RNAseq.

Jonathan D Oribello↗

Characterization and Analysis of the Energy-Reporting Accuracy of Connected Devices

Emerging energy-efficient building systems increasingly exhibit greater functionality, often requiring multiple operating modes (e.g. white-tunability for lighting products and data traffic for devices with networked, integrated sensors). This increased functionality makes energy consumption estimates more complex. Given that these functions consume energy, the energy performance of such building systems is dependent on what operating modes they use and how much time they spend in each mode. Devices and systems that can report their own energy consumption mitigate this energy-performance uncertainty. This study explores the energy-reporting accuracy of market-available connected electrical outlets. The study considers two residential-market products (five units each, one outlet per unit) and three commercial-market products (two units each, 18 to 24 outlets per unit) with the ability to report power drawn and/or energy consumed by devices connected to their receptacles. The products were purchased through typical market channels. Pacific Northwest National Laboratory (PNNL) conducted testing in December 2018 at its Connected Lighting Test Bed (CLTB), using a custom-developed test setup and method adapted from industry standards. The setup collected energy-consumption data reported by the outlet devices under test (DUTs) at one-minute intervals and compared that data with measurements taken by a reference meter over a range of test conditions. The residential products reported power draw but not interval or cumulative energy consumption. The commercial products reported both power draw and cumulative energy consumption. Relative reporting error (RRE) was calculated for all measurements, and analysis of the results revealed variations across devices and test conditions. The total number of measurements (50 for each residential product, 60 for each commercial product) offers an appreciable comparison of performance at the make/model level. The average RRE of the residential products derived from reported power draw was -0.02% and -1.20%. The average RRE for two of the three the commercial products derived from reported power draw was worse than those of the residential products (-2.40%, -2.72%, -0.36%). The internal integration of power over time, used to calculate cumulative energy consumption, typically occurs at current and voltage sampling rates much higher than once per minute. This suggests that the average commercial-product RRE derived from reported energy consumption should be very consistent and better than performance based on reported power draw. However, the RRE derived from reported energy consumption varied significantly across the three makes of commercial-market products and was uniformly less accurate than performance based on reported power draw. Subsequent analysis identified a number of root causes for this decrease in performance, most of which were related to reporting resolution. The goals of this study are to generate awareness of building systems capable of reporting their own energy consumption, further interest in the value of energy data for a variety of uses, draw attention to how the accuracy of reported metrics can be characterized, and quantify the performance variation found in marketavailable products. The results of this study and subsequent related work may be relevant to stakeholders in industry-specification and standards-development organizations. The methods this study employs could inform test and measurement procedures and performance classifications for connected outlets, lighting products, and other building systems capable of reporting their own energy consumption. The study concludes with stakeholder recommendations, including the following: • Energy-reporting device and system manufacturers developing products that report energy consumption should characterize the accuracy of reported metrics using a reference meter calibrated by an independent laboratory that was accredited by an ILAC MRA signatory (and whose scope of accreditation explicitly covers energy measurement), and should include this information on product data sheets. • Standards and specification development organizations should develop application-specific performance classifications that end users can understand and relate to their energy-data use needs (e.g., 2% accuracy class for utility streetlight energy billing needs, or 10% accuracy class for ESCO performance verification needs). • Current or potential owners, operators, and specifiers of energy-reporting building systems should rigorously analyze the dependency of current and planned energy-data use cases on accuracy, noting in particular the dependence (or lack thereof) on relative vs. absolute accuracy, and on trueness vs. precision (i.e., repeatability), and should communicate use-case needs to industry standards and specification organizations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Characterization and Analysis of the Energy-Reporting Accuracy of Connected Devices

Emerging energy-efficient building systems increasingly exhibit greater functionality, often requiring multiple operating modes (e.g. white-tunability for lighting products and data traffic for devices with networked, integrated sensors). This increased functionality makes energy consumption estimates more complex. Given that these functions consume energy, the energy performance of such building systems is dependent on what operating modes they use and how much time they spend in each mode. Devices and systems that can report their own energy consumption mitigate this energy-performance uncertainty. This study explores the energy-reporting accuracy of market-available connected electrical outlets. The study considers two residential-market products (five units each, one outlet per unit) and three commercial-market products (two units each, 18 to 24 outlets per unit) with the ability to report power drawn and/or energy consumed by devices connected to their receptacles. The products were purchased through typical market channels. Pacific Northwest National Laboratory (PNNL) conducted testing in December 2018 at its Connected Lighting Test Bed (CLTB), using a custom-developed test setup and method adapted from industry standards. The setup collected energy-consumption data reported by the outlet devices under test (DUTs) at one-minute intervals and compared that data with measurements taken by a reference meter over a range of test conditions. The residential products reported power draw but not interval or cumulative energy consumption. The commercial products reported both power draw and cumulative energy consumption. Relative reporting error (RRE) was calculated for all measurements, and analysis of the results revealed variations across devices and test conditions. The total number of measurements (50 for each residential product, 60 for each commercial product) offers an appreciable comparison of performance at the make/model level. The average RRE of the residential products derived from reported power draw was -0.02% and -1.20%. The average RRE for two of the three the commercial products derived from reported power draw was worse than those of the residential products (-2.40%, -2.72%, -0.36%). The internal integration of power over time, used to calculate cumulative energy consumption, typically occurs at current and voltage sampling rates much higher than once per minute. This suggests that the average commercial-product RRE derived from reported energy consumption should be very consistent and better than performance based on reported power draw. However, the RRE derived from reported energy consumption varied significantly across the three makes of commercial-market products and was uniformly less accurate than performance based on reported power draw. Subsequent analysis identified a number of root causes for this decrease in performance, most of which were related to reporting resolution. The goals of this study are to generate awareness of building systems capable of reporting their own energy consumption, further interest in the value of energy data for a variety of uses, draw attention to how the accuracy of reported metrics can be characterized, and quantify the performance variation found in marketavailable products. The results of this study and subsequent related work may be relevant to stakeholders in industry-specification and standards-development organizations. The methods this study employs could inform test and measurement procedures and performance classifications for connected outlets, lighting products, and other building systems capable of reporting their own energy consumption. The study concludes with stakeholder recommendations, including the following: • Energy-reporting device and system manufacturers developing products that report energy consumption should characterize the accuracy of reported metrics using a reference meter calibrated by an independent laboratory that was accredited by an ILAC MRA signatory (and whose scope of accreditation explicitly covers energy measurement), and should include this information on product data sheets. • Standards and specification development organizations should develop application-specific performance classifications that end users can understand and relate to their energy-data use needs (e.g., 2% accuracy class for utility streetlight energy billing needs, or 10% accuracy class for ESCO performance verification needs). • Current or potential owners, operators, and specifiers of energy-reporting building systems should rigorously analyze the dependency of current and planned energy-data use cases on accuracy, noting in particular the dependence (or lack thereof) on relative vs. absolute accuracy, and on trueness vs. precision (i.e., repeatability), and should communicate use-case needs to industry standards and specification organizations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗