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The Impact of Demographic Lifecycle States on Time to Vehicle Purchase: Insights from the Panel Study of Income Dynamics

This study examines the impact of demographic lifecycle stages on the timing of vehicle purchases, using data from the Panel Study of Income Dynamics from 1999 to 2021. Survival analysis was employed to model the duration until households purchase vehicles, incorporating key lifecycle variables such as age, employment status, marital status, childbirth, home ownership, and the presence of school-going children. The life table results indicate that early adulthood (ages 20–35) is the prime period for vehicle acquisition, with significant peaks around ages 25 to 30. Additionally, the instantaneous hazard of purchasing a vehicle is highest in the late 40s and early 50s. According to the Cox proportional hazards model, employment, marital status, and home ownership significantly increase the likelihood of purchasing a vehicle, while living in multi-unit dwellings decreases it. Interaction effects reveal that married individuals with employed spouses are substantially more likely to purchase vehicles. In conclusion, this study serves as a steppingstone toward integrating demographic lifecycle analysis into car ownership modeling that better reflects real-world scenarios and increases the accuracy of policy and strategic planning.

Car ownership

Life Cycle Analysis of Natural Gas Extraction and Power Generation: U.S. 2020 Emissions Profile

This analysis expands upon previous life cycle analyses (LCAs) of natural gas systems performed by the National Energy Technology Laboratory (NETL). It provides a complete inventory of emissions to air and water, water consumption, and land use change. These environmental burdens are detailed for all supply chain steps from natural gas production through natural gas distribution. This package includes the report, the NETL Natural Gas Model, and appendices that include several Excel workbooks and a python script to provide transparent access to the calculations and resulting data.<p>To access the NETL Natural Gas Lifecycle model, visit https://doi.org/10.18141/2476250.</p><p>To access the 2020 Report Appendices, visit https://doi.org/10.18141/2438472.</p>

03 NATURAL GAS

Second NASA Technical Interchange Meeting (TIM): Advanced Technology Lifecycle Analysis System (ATLAS) Technology Tool Box (TTB)

The Advanced Technology Lifecycle Analysis System (ATLAS), a spreadsheet analysis tool suite, applies parametric equations for sizing and lifecycle cost estimation. Performance, operation, and programmatic data used by the equations come from a Technology Tool Box (TTB) database. In this second TTB Technical Interchange Meeting (TIM), technologists, system model developers, and architecture analysts discussed methods for modeling technology decisions in spreadsheet models, identified specific technology parameters, and defined detailed development requirements. This Conference Publication captures the consensus of the discussions and provides narrative explanations of the tool suite, the database, and applications of ATLAS within NASA s changing environment.

ONeil, D. A.

NASA Software Estimating Tool (N-SET)

The goals of this project are to: Develop an early lifecycle software cost estimation tool leveraging existing data and capabilities Collect additional software data from: a) Jet Propulsion Laboratory; b) Goddard Space Flight Center; and c) Marshall Space Flight Center. Analyze, normalize, evaluate, stratify, and validate data. Create a calibrated, validated, and documented tool initially using available data and subsequently using newly collected data.

cost estimating tools

Satellite Data Applications for Sustainable Energy Transitions

Transitioning to a sustainable energy system poses a massive challenge to communities, nations, and the global economy in the next decade and beyond. A growing portfolio of satellite data products is available to support this transition. Satellite data complement other information sources to provide a more complete picture of the global energy system, often with continuous spatial coverage over targeted areas or even the entire Earth. We find that satellite data are already being applied to a wide range of energy issues with varying information needs, from planning and operation of renewable energy projects, to tracking changing patterns in energy access and use, to monitoring environmental impacts and verifying the effectiveness of emissions reduction efforts. While satellite data could play a larger role throughout the policy and planning lifecycle, there are technical, social, and structural barriers to their increased use. We conclude with a discussion of opportunities for satellite data applications to energy and recommendations for research to maximize the value of satellite data for sustainable energy transitions.

energy

NASA Technical Interchange Meeting (TIM): Advanced Technology Lifecycle Analysis System (ATLAS) Technology Tool Box

The objective of this Technical Interchange Meeting was to increase the quantity and quality of technical, cost, and programmatic data used to model the impact of investing in different technologies. The focus of this meeting was the Technology Tool Box (TTB), a database of performance, operations, and programmatic parameters provided by technologists and used by systems engineers. The TTB is the data repository used by a system of models known as the Advanced Technology Lifecycle Analysis System (ATLAS). This report describes the result of the November meeting, and also provides background information on ATLAS and the TTB.

ONeil, D. A.

Machine Learning Lifecycle for Earth Science Application: A Practical Insight into Production Deployment

Earth science domain presents unique sets of problems that are increasingly being solved using data driven approaches. The availability of big Earth science data offers immense potential for Machine learning (ML) as evident from numerous research publications lately. However, many of these publications are not ending up as production applications mainly because the data scientists who develop the ML models are now expected to complete the ML lifecycle by deploying and scaling the models in production. We introduce ML lifecycle to the Earth science community including the opportunities and challenges that lie ahead in each phase of the lifecycle. We demonstrate the lifecycle using an Earth science problem that we used ML to address and transitioned to production.

Maskey, Manil

PLM Innovation in Far Away Places

This viewgraph presentation reviews Jet Propulsion Laboratory's Product Lifecycle Management (PLM) mission to upgrade to product data management systems.

PLM

A Knowledge Graph Approach to Analyze Systems and Assets Health

Nuclear power plants collect large amounts of equipment reliability data elements that contain information on the statuses of component, assets, and systems. All these data elements precisely record asset and system performance and health throughout the lifecycle of those assets and systems. However, several challenges have proved to be roadblocks to this process. While some of these challenges are technical in nature (i.e., data are often distributed over several physical servers or databases), others are conceptual in nature (i.e., data elements come in different formats, numeric or textual), and measured values have different scales (e.g., vibration spectra and oil temperature). This paper directly focuses on the integration of numeric and textual data elements in order to assist plant system engineers in analyzing equipment reliability data. This task begins with preprocessing the data by extracting knowledge from textual data via natural language processing methods and quantifying system, asset, and component health based on numeric data. We then employed model-based system engineering (MBSE) models of systems and assets to identify their architecture and functional (i.e., cause and effect) relations. Data elements were then associated with a single MBSE graph element, based on their nature. This bonding of MBSE models and data elements constitutes a first-of-its-kind knowledge graph of a nuclear power plants system, with data elements being organized in a structured manner that enables system engineers to identify cause-effect trends in data elements and carry out appropriate actions in response.

97 - MATHEMATICS AND COMPUTING

Developing a Standard for Earth Observation Data Preservation Content - A Path to Future Usability

For datasets to be usable, many pieces of information in addition to the data themselves are essential. During the active parts of the lifecycle of dataset generating projects, the needed information is usually accessible through individuals familiar with the various aspects of the projects. However, the utility of datasets tends to outlive the lives of projects, by several decades in many cases. Thus it is essential to capture all the relevant information about the datasets, data, metadata and associate knowledge that is sufficient to read, understand, interpret and reuse the datasets, while the projects are still active. The capture and preservation should be such that the data are usable when no consultation is available from the original project participants. Identification of specific categories of content through an international standard is beneficial to the user communities of the future, so that projects involving Earth observations and generating data products can consistently plan for preservation and future usability of the project outcomes. While there are existing standards that address archival and preservation in general, there are no existing international standards or specifications today to address what content should be preserved. The standard, ISO 19165-1, titled "Geographic Information - Preservation of digital data and metadata Part 1: Fundamentals" considers geographic information preservation in general. It acknowledges that "specific content items needed to preserve the full provenance and context of the data and associated metadata depend on the needs of the designated community and types of datasets (e.g., maps, remotely sensed data from satellites and airborne instruments, physical samples). Follow-up parts to this standard may be developed detailing content items appropriate to individual disciplines." NASA proposed an extension to this standard, titled "Geographic information -- Preservation of digital data and metadata -- Part 2: Content specifications for Earth observation data and derived digital products." The development of this extension is in progress with participation by an international team representing nine countries. The purpose of this paper is to introduce this standard and report on its status.

Remote Sensing; Data Systems; Open Data;

Sizing and Lifecycle Cost Analysis of an Ares V Composite Interstage

The Interstage Element of the Ares V launch vehicle was sized using a commercially available structural sizing software tool. Two different concepts were considered, a metallic design and a composite design. Both concepts were sized using similar levels of analysis fidelity and included the influence of design details on each concept. Additionally, the impact of the different manufacturing techniques and failure mechanisms for composite and metallic construction were considered. Significant details were included in analysis models of each concept, including penetrations for human access, joint connections, as well as secondary loading effects. The designs and results of the analysis were used to determine lifecycle cost estimates for the two Interstage designs. Lifecycle cost estimates were based on industry provided cost data for similar launch vehicle components. The results indicated that significant mass as well as cost savings are attainable for the chosen composite concept as compared with a metallic option.

Mann, Troy

Applied Space Systems Engineering: Manage Technical Data - Chapter 17

Effective space systems engineering (SSE) is conducted in a fully electronic manner. Competitive hardware, software, and system designs are created in a totally digital environment that enables rapid product design and manufacturing cycles, as well as a multitude of techniques such as modeling, simulation, and lean manufacturing that significantly reduce the lifecycle cost of systems. Because the SSE lifecycle depends on the digital environment, managing the enormous volumes of technical data needed to describe, build, deploy, and operate systems is a critical factor in the success of a project. This chapter presents the key aspects of Technical Data Management (TDM) within the SSE process. It is written from the perspective of the System Engineer tasked with establishing the TDM process and infrastructure for a major project. Additional perspectives are reflected from the point of view of the engineers on the project who work within the digital engineering environment established by the TDM toolset and infrastructure, and from the point of view of the contactors who interface via the TDM infrastructure. Table 17.1 lists the TDM process as it relates to SSE.

Kent, Peter

An Agile-Like Approach to Hardware Development: The Ejectable Data Recorder (EDR) for Orion's Ascent Abort 2 (AA-2) Test Flight

On July 2, 2019, the Ascent Abort 2 (AA-2) Flight Test Vehicle was launched from Cape Canaveral, with the goal of demonstrating the performance of Orion’s Launch Abort System (LAS) and collecting data from hundreds of sensors throughout the vehicle. The data collected during this test flight is of paramount importance, as it will be used to certify the Orion vehicle for human spaceflight. Originally, the data was to be downlinked via a single string network of antennas on the LAS, with the associated risk of potential data dropouts, as well as loss of data once the LAS was jettisoned. Thus, additional antennas were added onto the crew module (CM) to support data downlink post-LAS jettison, a buffer rebroadcast capability was added to fill in any gaps in data downlink transmissions, and an ejectable data recorder (EDR) subsystem was added to the CM as a redundant measure to collect all the instrumentation data. The EDR subsystem was added to the project about one year after the project commenced, which significantly reduced the available development time when compared with the other subsystems of the AA-2 Test Flight. The project was further accelerated by six months, around the critical design review gate. Due to the schedule compression challenge and the fact that the EDR subsystem was a backup system and not flight critical, the EDR subsystem was further challenged to find a new and more efficient way to develop hardware. Thus, the EDR subsystem experimented with different management and systems engineering processes, team sizes, communication methods, and tools. Some examples are novel uses of SharePoint as a Data-centric Project Management & Systems Engineering environment, a continuous testing approach through the lifecycle, and a Skunkworks approach to managing the team. The EDR subsystem blended Commercial Off The Shelf (COTS) hardware with in-house developed hardware and software to create a novel data retrieval capability. The capability evolved rapidly through a hardware in the loop simulation environment that enabled incremental component updates for not only the EDR subsystem but across the entire Crew Module. This paper will present an overview of how the EDR subsystem was managed and compare it to an Agile approach to managing projects. The paper will further provide a recommended approach to future Agile-like hardware development that incorporates lessons learned from the EDR experience.

Agile

NASA Crew Launch Vehicle Approach Builds on Lessons from Past and Present Missions

The United States Vision for Space Exploration, announced in January 2004, outlines the National Aeronautics and Space Administration's (NASA) strategic goals and objectives, including retiring the Space Shuttle and replacing it with a new human-rated system suitable for missions to the Moon and Mars. The Crew Exploration Vehicle (CEV) that the new Crew Launch Vehicle (CLV) lofts into space early next decade will initially ferry astronauts to the International Space Station and be capable of carrying crews back to lunar orbit and of supporting missions to Mars orbit. NASA is using its extensive experience gained from past and ongoing launch vehicle programs to maximize the CLV system design approach, with the objective of reducing total lifecycle costs through operational efficiencies. To provide in-depth data for selecting this follow-on launch vehicle, the Exploration Systems Architecture Study was conducted during the summer of 2005, following the confirmation of the new NASA Administrator. A team of aerospace subject matter experts used technical, budget, and schedule objectives to analyze a number of potential launch systems, with a focus on human rating for exploration missions. The results showed that a variant of the Space Shuttle, utilizing the reusable Solid Rocket Booster as the first stage, along with a new upper stage that uses a derivative of the RS-25 Space Shuttle Main Engine to deliver 25 metric tons to low-Earth orbit, was the best choice to reduce the risks associated with fielding a new system in a timely manner. The CLV Project, managed by the Exploration Launch Office located at NASA's Marshall Space Flight Center, is leading the design, development, testing, and operation of this new human-rated system. The CLV Project works closely with the Space Shuttle Program to transition hardware, infrastructure, and workforce assets to the new launch system . leveraging a wealth of lessons learned from Shuttle operations. The CL V is being designed to reduce costs through a number of methods, ranging from validating requirements to conducting trades studies against the concept design. Innovations such as automated processing will build on lessons learned from the Shuttle, other launch systems, Department of Defense operations experience, and subscale flight tests such as the Delta Clipper-Experimental Advanced (DCXA) vehicle operations that utilized minimal touch labor, automated cryogen ic propellant loading , and an 8-hour turnaround for a cryogenic propulsion system. For the CLV, the results of hazard analyses are contributing to an integrated vehicle health monitoring system that will troubleshoot anomalies and determine which ones can be solved without human intervention. Such advances will help streamline the mission operations process for pilots and ground controllers alike. In fiscal year 2005, NASA invested approximately $4.5 billion of its $16 bill ion budget on the Space Shuttle. The ultimate goal of the CLV Project is to deliver a safe, reliable system designed to minimize lifecycle costs so that NASA's budget can be invested in missions of scientific discovery. Lessons learned from developing the CLV will be applied to the growth path for future systems, including a heavy lift launch vehicle.

Dumbacher, Daniel L.

Pumped Storage Hydropower Potential and Opportunities

Pumped storage hydropower (PSH) is a flexible energy storage technology with the potential to improve grid reliability, resiliency, and stability in the electric grid of the future. NREL has developed a range of data and tools to help understand opportunities for new PSH deployment, including nationwide resource assessment data, a bottom-up component-level cost model, and a lifecycle greenhouse gas emissions calculator. These datasets can then be used to inform grid planning models, analysis, and decision making to understand the role PSH can play in the power sector.

cost

Parts Quality Management: Direct Part Marking via Data Matrix Symbols for Mission Assurance

A United States Government Accountability Office (GAO) review of twelve NASA programs found widespread parts quality problems contributing to significant cost overruns, schedule delays, and reduced system reliability. Direct part-marking with Data Matrix symbols could significantly improve the quality of inventory control and parts lifecycle management. This paper examines the feasibility of using 15 marking technologies for use in future NASA programs. A structural analysis is based on marked material type, operational environment (e.g., ground, suborbital, orbital), durability of marks, ease of operation, reliability, and affordability. A cost-benefits analysis considers marking technology (data plates, label printing, direct part marking) and marking types (two-dimensional machine-readable, human-readable). Previous NASA parts marking efforts and historical cost data are accounted for, including in-house vs. outsourced marking. Some marking methods are still under development. While this paper focuses on NASA programs, results may be applicable to a variety of industrial environments.

Moss, Chantrice

Parts Quality Management: Direct Part Marking of Data Matrix Symbol for Mission Assurance

A United States Government Accountability Office (GAO) review of twelve NASA programs found widespread parts quality problems contributing to significant cost overruns, schedule delays, and reduced system reliability. Direct part marking with Data Matrix symbols could significantly improve the quality of inventory control and parts lifecycle management. This paper examines the feasibility of using direct part marking technologies for use in future NASA programs. A structural analysis is based on marked material type, operational environment (e.g., ground, suborbital, Low Earth Orbit), durability of marks, ease of operation, reliability, and affordability. A cost-benefits analysis considers marking technology (label printing, data plates, and direct part marking) and marking types (two-dimensional machine-readable, human-readable). Previous NASA parts marking efforts and historical cost data are accounted for, including inhouse vs. outsourced marking. Some marking methods are still under development. While this paper focuses on NASA programs, results may be applicable to a variety of industrial environments.

Moss, Chantrice

Comparison of GOES16 Data with the TRACER-ESCAPE Field Campaign Dataset for Convection Characterization: A Selection of Case Studies and Lessons Learnt

Convective updrafts are one of the main characteristics of convective clouds, responsible for the convective mass flux and the redistribution of energy and condensate in the atmosphere. During the early stages of their lifecycle, convective clouds experience rapid cloud-top ascent manifested by a decrease in the geostationary IR brightness temperature (𝑇⁢𝐵 𝐼⁢𝑅 ). Under the assumption that the convective cloud top behaves like a black body, the ascent rate of the convective cloud top can be estimated as ($\frac{∂𝑇⁢𝐵_{𝐼⁢𝑅}}{∂𝑡}$), and it can be used to infer the near cloud-top convective updraft. The temporal resolution of the geostationary IR measurements and non-uniform beam-filling effects can influence the convective updraft estimation. However, the main shortcoming until today was the lack of independent verification of the strength of the convective updraft. Here, Doppler radar observations from the ESCAPE and TRACER field experiments provide independent estimates of the convective updraft velocity at higher spatiotemporal resolution throughout the convective core column and can be used to evaluate the updraft velocity estimates from the IR cooling rate for limited samples. Isolated convective cells were tracked with dedicated radar (RHIs and PPIs) scans throughout their lifecycle. Radial Doppler velocity measurements near the convective cloud top are used to provide estimates of convective updrafts. These data are compared with the geostationary IR and VIS channels (from the GOES satellite) to characterize the convection evolution and lifecycle based on cloud-top cooling rates.

TRACER/ESCAPE field campaign